Optimization of Capacitated Vehicle Routing Problem for Recyclable Solid Waste Collection Using Genetic and Seed Genetic Algorithms Hybridized With Greedy Algorithm

Abstract

There has been a growing interest in collecting recyclable waste to reduce total carbon emissions, generate economic growth, and promote total lifecycle sustainability. This paper studies capacitated vehicle routing problem (CVRP) related to recyclable solid waste collection. The problem differs from the classical CVRP in terms of considering a separate recycling station in addition to the main depot. Genetic Algorithm (GA) and Seed Genetic Algorithm (SGA) hybridized with Greedy Algorithm are proposed. The objective of this study is to determine the optimal routes for the collection and delivery of recyclable solid waste. Hybrid GA and hybrid SGA are used to find the optimal solution while minimizing the total traveling distance. In addition, a web-crawling bot is developed to generate the matrix of real distances rather than considering the Euclidean distances. A real case of collecting recyclable waste in Yerevan, Armenia by an NGO has been studied to evaluate the effectiveness of the proposed approach. The results show that SGA provides better solutions than GA, and that these algorithms are better than the solution adopted by the NGO.