Solving Multiple Vehicle Routing Problems with Time Constraintsby Flower Pollination Algorithm Optimization

Abstract

The multiple vehicle routing problem (MVRP) with the time constraint is one of the most importantreal-world problems in industrial and logistic engineering. The MVRP problems can be considered as a class ofthe non-polynomial (NP) time-complete combinatorial optimization problem. Such the MVRP problems aim tofind the set of routes with the shortest total distance for overall minimum route cost serving all the givendemands by the fleet of vehicles. Based on modern optimization, the MVRP problems can be optimally solvedby the potential metaheuristic optimization techniques. The flower pollination algorithm (FPA) is one of themost efficient metaheuristic optimizers proposed for solving the combinatorial optimization problems. Withfew searching parameters, the algorithm of the FPA is not complex and ease of use. In this paper, the FPA isapplied to solve five selected benchmark MVRP problems with the time constraints consisting of 50-100destinations. Results obtained by the FPA will be compared with those obtained by genetic algorithm (GA), tabusearch (TS) and particle swarm optimization (PSO). From results, the FPA can provide optimal solutions of allfive selected problems. Optimal results obtained by the FPA are superior to PSO, TS and GA, respectively,with shorter total distance and computational time consumed

Evolutionary Algorithm to Support Field Architecture Scenario Screening Automation and Optimization Using Decentralized Subsea Processing Modules

“…In addition, there is still a high potential for improvement of the proposed method within the EA domain considering the future works suggested above. However, evaluations and comparisons against alternative relevant metaheuristic optimization methods, such as particle swarm optimization [54][55][56][57] and flower pollination [58,59], should also be considered for future works, as well as hybrid optimization methods.…”