A fuzzy logic-genetic algorithm for full truckload transportation problem

Abstract

This work addresses a full truckload commodity selection and multiple depot vehicle routing problem with time windows (FTSMDVRPTW). The goal of the problem is to design a set of selective truck routes that maximize overall profit subject to time window constraints. Each truck route is an arrangement of full truckload transportation commodities that begins at a departure point and ends at an arrival point. It is unnecessary to serve all commodities; only those that provide a higher profit are chosen. We introduce a meta-heuristic based on a combination of fuzzy logic controller (FLC) and genetic algorithm (GA) to solve the FTSMDVRPTW, where the crossover and mutation rates are adjusted during the GA’s evolutionary process using an FLC. We demonstrate the effectiveness and efficiency of the proposed FLC+GA through experimental results on randomly generated instances for the considered problem.