arXiv subjects

Goutam Sen

Publications and source records attributed to Goutam Sen.

2 recordsLinked to original sources

arXiv2025

Rich Vehicle Routing Problem in Disaster Management enabling Temporally-causal Transhipments across Multi-Modal Transportation Network

A rich vehicle routing problem is considered, allowing multiple trips of heterogeneous vehicles stationed at geographically distributed vehicle depots having access to different modes of transportation. The problem arises from the real-world requirement of optimizing the disaster response time by minimizing the makespan of vehicular routes. Multiple diversely-functional vertices are considered, including Transhipment Ports as inter-modal resource transfer stations. Both simultaneous and split pickup and delivery are considered, for multiple cargo types, along with Vehicle-Cargo and Transhipment Port-Cargo compatibilities. The superiority of the proposed cascaded minimization approach is demonstrated over the existing makespan minimization approaches through our developed Mixed-Integer Linear Programming formulation. To solve the problem quickly for practical implementation in a Disaster Management-specific Decision Support System, an extensive Heuristic Algorithm is devised which utilizes Decision Tree based structuring of possible routes; the Decision Tree approach helps to inherently capture the compatibility issues, while also explore the solution space through stochastic weights. Preferential generation of small route elements is performed, which are integrated into route clusters; we consider multiple different logical integration approaches, as well as shuffling the logics to simultaneously produce multiple independent solutions. Finally, perturbations of the different solutions are done to find better neighbouring solutions. The computational performance of the PSR-GIP Heuristic, on our created novel datasets, indicates that it is able to give good solutions swiftly for practical problems involving large integer instances that the MILP is unable to solve.

math.OC↗

arXiv2023

Performance assessment of vehicle interdiction strategies in a simulation based environment on a complex transportation network

We consider the escape interdiction problem in a transportation network. In the absence of traffic in the network, the criminal/attacker tries to escape from the city using any of the shortest paths from the crime scene to any randomly chosen exit point. In the presence of traffic, the attacker chooses the optimal path, which takes minimum time to reach his destination. On the contrary, police/defenders try to interdict the criminal on his escape route. This is a challenging task for police with limited resources. Again, a real city road network is also complex in nature. First, we develop a simulation-based model for the optimal allocation of resources using the SUMO simulator. Next, we focus on developing a more advanced search strategy like routing with optimal resource allocation. We develop a novel meta-heuristic approach in a simulation environment to interdict the attacker in a dynamic crime scenario. Like the previous approach, the attacker follows the path with optimal time to escape from the city. In contrast, defenders try to catch the attacker regardless of the path which the attacker takes. The defenders aim is to maximize the interdiction probability. As time plays a vital role, we choose a meta-heuristic approach to provide quality solutions in a time-efficient manner. We test the developed meta-heuristic with a case study on the IIT Kharagpur map, India. We analyze the performance of the mentioned approaches using the SUMO simulator both in the presence of traffic and without traffic. We develop a linear regression model to generate optimal path in the presence of traffic. Here traffic is generated randomly in the whole network using the SUMO simulator.

physics.soc-ph↗