A multi-objective centralised agent-based optimisation approach for vehicle routing problem with unique vehicles

Motivated by heterogeneous service suppliers in crowd shipping routing problems, vehicles’ similarity assumption is questioned the well-known logistical Vehicle Routing Problems (VRP) considering different start/end locations, capacities, as well shifts Time Window variant (VRPTW). In order to tackle this problem, a new agent-based metaheuristic architecture proposed capture uniqueness of vehicles modelling them agents while governing search with centralised agent cooperation. This cooperation aims generate near optimum routes minimising number used, total travelled distance, and waiting times. The innovative encapsulates three individual core modules flexible implementation. First, problem modelled an module that includes its components representing, evaluating, altering solutions. A second then designed integrated, followed multi-objective introduced sort solutions generated based on Pareto dominance. Tests benchmark instances were run, resulting better times, average reduction 2.21-time units, at expense other objectives. Benchmark are modified unique vehicle’s randomising operating tested justify model’s applicability.