Raytheon

Principal Engineer

- Technical lead for analytics thrust of R&D project; developed technologies to perform situation assessment, awareness, and understanding in the cyber domain.

- Technical lead of information fusion thrust of R&D project; developed technologies for the determination of abnormal behavior, predictive modeling, trend analysis, situation assessment, awareness, and understanding, adversarial intent, ontological modeling, machine learning, and optimal resource allocation.

- Principal investigator for Office of Naval Research CR&D project; developed intelligent, optimal strategies for the exchange of information across a network.

Raytheon

Senior Principal Scientist

- Chief technologist for R&D project developing collaborative tasking technologies for space mission management.

- Chief scientist for R&D project; developed corporate technology roadmap for autonomous technologies; developed autonomous technologies to reduce manning and improve mission effectiveness across multiple mission domains.

- Principal investigator for cooperative control R&D project; formulated rigorous mathematical models and created algorithms allowing heterogeneous vehicles to autonomously collaborate in a dynamic environment and achieve mission goals.

Stetson University

Visiting Professor

Taught a variety of mathematics and computer science courses, including operations research and business calculus.

Stetson University

Adjunct Professor

Taught business calculus in the Spring 2014 semester.

ISEA TEK

President

Industrial & Systems Engineering Analysis Technologies (ISEA TEK, LLC) provides research and development consulting services for government and commercial clients. ISEA TEK has expertise in: Information Fusion, Situation Awareness, Resource Allocation, Cooperative Control, Autonomous Systems, Mathematical Programming, Optimization Theory, Heuristic Development, Modeling & Simulation, Decision Support Systems, and Analytics.

Visit the company website at: http://www.iseatek.com/

St. Petersburg College

Adjunct Faculty

- Taught pre-calculus and calculus I to undergraduate students.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Enabling connectivity for tactical networks in mountainous areas by aerial relays

To appear in Telecommunication Systems

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Enabling connectivity for tactical networks in mountainous areas by aerial relays

To appear in Telecommunication Systems

Multi-depot vessel routing problem in a direction dependent wavefield

Journal of Combinatorial Optimization, vol. 28, no. 1, pp 38–57.

Considerable research has been done on the vehicle routing problem and its variants; however only limited amount of existing work deals with possible environmental conditions and their effects on the vehicle routes. This paper presents the multiple-depot vehicle routing problem for surface vessels, where the vehicles must traverse a time-invariant direction-dependent medium. Our model captures environmental effects and vessel dynamics on the considered paths. Three heuristic solution methods are developed and tested on simulated scenarios. The first approach exactly solves an approximate formulation of the problem, the second approximately solves an approximate problem formulation, while the third approximately solves the exact problem. Performance of the algorithms are compared to assess the tradeoff between computational cost and quality of the found solutions.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Enabling connectivity for tactical networks in mountainous areas by aerial relays

To appear in Telecommunication Systems

Multi-depot vessel routing problem in a direction dependent wavefield

Journal of Combinatorial Optimization, vol. 28, no. 1, pp 38–57.

Considerable research has been done on the vehicle routing problem and its variants; however only limited amount of existing work deals with possible environmental conditions and their effects on the vehicle routes. This paper presents the multiple-depot vehicle routing problem for surface vessels, where the vehicles must traverse a time-invariant direction-dependent medium. Our model captures environmental effects and vessel dynamics on the considered paths. Three heuristic solution methods are developed and tested on simulated scenarios. The first approach exactly solves an approximate formulation of the problem, the second approximately solves an approximate problem formulation, while the third approximately solves the exact problem. Performance of the algorithms are compared to assess the tradeoff between computational cost and quality of the found solutions.

On the minimization of traffic congestion in road networks with tolls

Annals of Operations Research, vol. 249, no. 1, pp. 119–139.

Population growth and the massive production of automotive vehicles have lead to the increase of traffic congestion problems. Traffic congestion today is not limited to large metropolitan areas, but is observed even in medium-sized cities and highways. Traffic engineering can contribute to lessen these problems. One possibility, explored in this paper, is to assign tolls to streets and roads, with the objective of inducing drivers to take alternative routes, and thus better distribute traffic across the road network. This assignment problem is often referred to as the tollbooth problem and it is NP-hard. In this paper, we propose mathematical formulations for two versions of the tollbooth problem that use piecewise-linear functions to approximate congestion cost. We also apply a biased random-key genetic algorithm on a set of real-world instances, analyzing solutions when computing shortest paths according to two different weight functions. Experimental results show that the proposed piecewise-linear functions approximate the original convex function quite well and that the biased random-key genetic algorithm produces high-quality solutions.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Enabling connectivity for tactical networks in mountainous areas by aerial relays

To appear in Telecommunication Systems

Multi-depot vessel routing problem in a direction dependent wavefield

Journal of Combinatorial Optimization, vol. 28, no. 1, pp 38–57.

Considerable research has been done on the vehicle routing problem and its variants; however only limited amount of existing work deals with possible environmental conditions and their effects on the vehicle routes. This paper presents the multiple-depot vehicle routing problem for surface vessels, where the vehicles must traverse a time-invariant direction-dependent medium. Our model captures environmental effects and vessel dynamics on the considered paths. Three heuristic solution methods are developed and tested on simulated scenarios. The first approach exactly solves an approximate formulation of the problem, the second approximately solves an approximate problem formulation, while the third approximately solves the exact problem. Performance of the algorithms are compared to assess the tradeoff between computational cost and quality of the found solutions.

On the minimization of traffic congestion in road networks with tolls

Annals of Operations Research, vol. 249, no. 1, pp. 119–139.

Population growth and the massive production of automotive vehicles have lead to the increase of traffic congestion problems. Traffic congestion today is not limited to large metropolitan areas, but is observed even in medium-sized cities and highways. Traffic engineering can contribute to lessen these problems. One possibility, explored in this paper, is to assign tolls to streets and roads, with the objective of inducing drivers to take alternative routes, and thus better distribute traffic across the road network. This assignment problem is often referred to as the tollbooth problem and it is NP-hard. In this paper, we propose mathematical formulations for two versions of the tollbooth problem that use piecewise-linear functions to approximate congestion cost. We also apply a biased random-key genetic algorithm on a set of real-world instances, analyzing solutions when computing shortest paths according to two different weight functions. Experimental results show that the proposed piecewise-linear functions approximate the original convex function quite well and that the biased random-key genetic algorithm produces high-quality solutions.

Optimization Algorithms for Decentralized Planning and Control

Raytheon Technology Today Magazine, no. 1, pp. 32–35.

Minimizing Time Delay of Information Routed Across Dynamic Temporal Sensor Networks

Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 327-340, 2018.

In this research we address the problem of routing information across dynamic temporal sensor networks. The goal is to determine which information, generated by sensors on resources at various times, is able to be routed to other resources, consumer resources, within the given information time window, while being constrained by temporally dynamic bandwidth limitations across the sensor network, and storage limitations on the resources. A mathematical model of the problem is derived, and used to find solutions to the problem. In addition, a heuristic is developed to efficiently find good quality solutions. Monte-Carlo simulations are performed comparing solutions found by commercial software with the heuristic.

Information Supply Chain Optimization with Bandwidth Limitations

International Transactions in Operational Research, vol. 24, no. 5, pp. 993–1022.

Workflow management systems allow for visibility, control, and automation of many business processes. Recently, non-business domains have taken an interest in the management of workflows, and the optimal assignment and scheduling of workflow tasks to users across a network. This research aims at developing a rigorous mathematical programming formulation of the workflow optimization problem. The resulting formulation is nonlinear, but a linearized version is produced. Three heuristics are developed to find solutions efficiently. Computational experiments are presented and analyzed, comparing solutions to the original linearized formulation with the three heuristics.

On the Decentralized Cooperative Control of Multiple Autonomous Vehicles

Handbook of Unmanned Aerial Vehicles, K.P. Valavanis and G. Vachtsevanos (eds.), Springer, pp. 1577–1600.

End-to-End Applications and Algorithm Integration Method and Architecture

IEEE Proc. of the Military Communications Conference, pp. 686 – 691, San Diego, CA., U.S.A.

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Shortest Paths for Routing Information over Temporally Dynamic Communication Networks

IEEE Proc. of the Military Communications Conference, pp. 587 – 591, Baltimore, MD.

There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for the proper making of decisions. For military applications, routing of information across a communication network has typically been accomplished using fixed, a priori defined, routing paths. When bandwidth between resources is unlimited, this presents no problems. However, in bandwidth constrained environments, when not all information is able to be routed across the network, then fixed routing paths presents limitations in information reaching appropriate consumers. In this research, we consider the advantages to using dynamic shortest temporal path routes for the information, as opposed to fixed routing paths. Multiple metrics show empirically the benefit to dynamic shortest path routes.

Enabling connectivity for tactical networks in mountainous areas by aerial relays

To appear in Telecommunication Systems

Multi-depot vessel routing problem in a direction dependent wavefield

Journal of Combinatorial Optimization, vol. 28, no. 1, pp 38–57.

Considerable research has been done on the vehicle routing problem and its variants; however only limited amount of existing work deals with possible environmental conditions and their effects on the vehicle routes. This paper presents the multiple-depot vehicle routing problem for surface vessels, where the vehicles must traverse a time-invariant direction-dependent medium. Our model captures environmental effects and vessel dynamics on the considered paths. Three heuristic solution methods are developed and tested on simulated scenarios. The first approach exactly solves an approximate formulation of the problem, the second approximately solves an approximate problem formulation, while the third approximately solves the exact problem. Performance of the algorithms are compared to assess the tradeoff between computational cost and quality of the found solutions.

On the minimization of traffic congestion in road networks with tolls

Annals of Operations Research, vol. 249, no. 1, pp. 119–139.

Population growth and the massive production of automotive vehicles have lead to the increase of traffic congestion problems. Traffic congestion today is not limited to large metropolitan areas, but is observed even in medium-sized cities and highways. Traffic engineering can contribute to lessen these problems. One possibility, explored in this paper, is to assign tolls to streets and roads, with the objective of inducing drivers to take alternative routes, and thus better distribute traffic across the road network. This assignment problem is often referred to as the tollbooth problem and it is NP-hard. In this paper, we propose mathematical formulations for two versions of the tollbooth problem that use piecewise-linear functions to approximate congestion cost. We also apply a biased random-key genetic algorithm on a set of real-world instances, analyzing solutions when computing shortest paths according to two different weight functions. Experimental results show that the proposed piecewise-linear functions approximate the original convex function quite well and that the biased random-key genetic algorithm produces high-quality solutions.

Optimization Algorithms for Decentralized Planning and Control

Raytheon Technology Today Magazine, no. 1, pp. 32–35.

Risk constraints for portfolio optimization with fixed-fee transaction cost

Journal of Investment Strategies, vol. 6, no. 2, pp. 91–112.

Depending on the size of the initial investment, transaction costs are an important consideration when it comes to smartly investing money and growing a portfolio for retirement. In addition, different risk models significantly affect the growth rate of a portfolio. Many investment brokerages (e.g., Fidelity, T. Rowe Price, etc) now employ fixed-fee transaction costs for individual investors. In this research, we investigate how fixed-fee transaction costs affect portfolio rebalancing. We use two risk measures, conditional value-at-risk and mean absolute deviation. Historical Standard & Poor’s 500 data is used for a computational study in which we compare the two risk measures and investigate how influential transaction costs are on the value of a portfolio at each investment opportunity.

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