Bayesian hierarchical multi-objective optimization for vehicle parking route discovery
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Bayesian hierarchical multi-objective optimization for vehicle parking route discovery Romit S. Beed1 · Sunita Sarkar2 · Arindam Roy3 Received: 15 March 2020 / Accepted: 21 August 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Discovering an optimal route to the most feasible parking lot has been a matter of apprehension for any driver. Selecting the most optimal route to the most favorable lot aggravates further during peak hours of the day and at congested places. This leads to a considerable wastage of resources specifically time and fuel. This work proposes a Bayesian hierarchical technique for obtaining this optimal route. The route selection is based on conflicting objectives, and hence, the problem belongs to the domain of multi-objective optimization. A probabilistic data-driven method has been used to overcome the inherent problem of weight selection in the popular weighted sum technique. The weights of these conflicting objectives have been refined using a Bayesian hierarchical model based on multinomial and Dirichlet prior. Genetic algorithm has been used to obtain optimal solutions. Simulated data have been used to obtain routes which are in close agreement with real-life situations. Statistical analyses have shown the superiority of the weights obtained using the proposed algorithm based on Bayesian technique over the existing frequentist technique. Keywords Bayesian · Genetic algorithm · Multi-objective · Optimization · Weighted sum technique
1 Introduction Vehicle routing problems (VRPs) are popular combinatorial optimization problems present in transport sector which generally include allotting resources and scheduling in constrained environments from a depot to different locations having considerable financial implications. VRPs have gained popularity in the recent past because of their diverse applicability and commercial importance in defining effective distribution tactics to shrink operative costs in distribution networks. A typical VRP involves designing minimum cost
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Sunita Sarkar [email protected] Romit S. Beed [email protected] Arindam Roy [email protected]
1
Department of Computer Science, St. Xavier’s College (Autonomous), Kolkata, India
2
Department of Computer Science and Engineering, Assam University, Silchar, India
3
Department of Computer Science, Assam University, Silchar, India
routes from a principal warehouse to a set of physically distributed locations having varying requirements. Each such location needs to be serviced precisely once by a single van, and each van has a fixed carrying capacity. Vehicle parking route determination may be considered as an extension of a typical VRP. Instead of considering only distance as a parameter for determining the most appropriate parking lot, the time it takes to reach the particular lot and the availability of empty space may also be conflicting factors while determining the most suitable lot. Hence, this problem may be treated as a multi-objective optimization problem
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