A multi-compartment capacitated arc routing problem with intermediate facilities for solid waste collection using hybrid adaptive large neighborhood search and whale algorithm

• Published in: Waste management & research Vol. 37; no. 1; pp. 38 - 47
• Main Authors: Mofid-Nakhaee, Elham, Barzinpour, Farnaz
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2019; Sage Publications Ltd
• Subjects: Adaptive algorithms; Algorithms; Animals; Automotive parts; Carp; Cities; Developing countries; Garbage collection; Iran; LDCs; Municipal solid waste; Municipal waste management; Optimization; Optimization algorithms; Population growth; Refuse Disposal; Search algorithms; Solid Waste; Solid waste management; Vehicles; Waste Management; Waste management industry; Waste sorting; Whales; Iran; Cities; adaptive large neighborhood search; multi-compartment vehicle; separation of waste; municipal solid waste; Arc routing problem; whale optimization algorithm
• ISSN: 0734-242X; 1096-3669; 1096-3669
• DOI: 10.1177/0734242X18801186

Municipal solid waste collection is an increasingly difficult task and has the highest operation cost in the solid waste management process; thus, finding the optimal routes for the waste collection is a most tactically significant decision that should be focused on due to the population growth. This research investigated the multi-compartment capacitated arc routing problem with intermediate facilities (MCCARPIF) in the context of solid waste collection. This problem has been researched rarely in the past in the real world. The MCCARPIF develops the capacitated arc routing problem (CARP) by considering both the multi-compartment vehicles and intermediate facilities together. In case of waste separation, the fleet of vehicles should have multiple parts to avoid mixing waste together. In developing countries, the process of separating the wastes is not carried out comprehensively, so this subject is almost new and research about it can improve their waste collection process. Due to the complexity of this model, two algorithms are developed to solve it: an adaptive large neighborhood search algorithm (ALNS) and the hybrid ALNS with whale optimization algorithm. Results showed that hybrid ALNS with whale optimization algorithm got higher quality solutions in comparison to ALNS. A real case study in one of the districts of Tehran municipality has been considered and the results obtained show that the use of multi-compartment vehicles is more cost-effective than the use of single-compartment vehicles, reducing the total distance traveled.