The two-echelon multi-objective location routing problem inspired by realistic waste collection applications: The composable model and a metaheuristic algorithm

Abstract

Waste collection has always been a major research area in waste management. It plays an important role in social development and environmental sustainability. However, the past research often makes great efforts to formulate dedicated models to some specific waste collection applications, and relatively speaking, fewer efforts have been devoted to relevant method development. Inspired by these issues, in this work, we first develop a more general two-echelon multi-objective location routing problem model (2E-MOLRP) in consideration of the inherent similarities of many realistic waste collection applications. In the model, various commonly-seen and potential costs are classified in a straightforward way and different objectives can hence be flexibly defined to satisfy different requirements. Furthermore, to solve the model, an improved non-dominated sorting genetic algorithm with directed local search (INSGA-dLS) is proposed. In order to validate its effectiveness, experiments are conducted in comparison with existing representative metaheuristics and the results show that our proposed algorithm can achieve better performance even without using local search. Also, we prove that the specially-designed directed locate search is able to further improve our algorithm’s performance significantly in experiments.