A multi-day waste collection and transportation problem with selective collection and split delivery

Abstract

This paper addresses a multi-day waste collection and transportation problem with selective collection and split delivery (MDWCTP-SCSD). Rather than emptying waste according to a fixed schedule, garbage trucks only visit community waste collection sites whose waste level reaches a predetermined threshold, reducing collection costs but increasing overflow risk. Collection sites likely to overflow the next day if unvisited today are also selected for preventive collection. Split delivery is permitted. The MDWCTP-SCSD is formulated as a mixed integer linear programming model. To solve this NP-hard problem, a heuristic combining variable neighborhood search and simulated annealing is proposed. In addition to classical operators, three new operators are developed to handle split delivery. Experiments demonstrate the proposed algorithm is competitive in solving two split delivery vehicle routing benchmark sets; outperforms CPLEX in solving small-scale instances within an hour; and quickly solves large-scale instances with high quality. Noteworthy findings indicate fleet costs and size can be reduced by approximately 50% if only visiting sites whose waste level reaches 80%.