A Discrete Teaching-Learning-Based Optimization Algorithm for the Capacitated Vehicle Routing Problem

Teaching-learning-based optimization (TLBO) is a recently proposed population based algorithm which si- mulates the teaching-learning process of the class room. In order to solve the capacitated vehicle routing problem, a discrete teaching-learning-based optimization algorithm (DTLBO) is proposed with a new solution representation and decoding method in this paper. An elitist strategy is introduced in the TLBO algorithm to preserve the best individuals from generation to generation. At the same time, duplicate solutions are modified by mutation on randomly selected dimensions of the duplicate solutions to keep the diversity of the population. Then the 2-OPT local search is combined to improve the local search ability of the hybrid discrete teaching-learning-based optimization. Tested on the several benchmarking capacitated vehicle routing problems, the hybrid discrete teaching-learning-based optimization can achieve the optimal solutions of all selected instances.