Collection-disassembly-delivery problem of disassembly centers in a reverse logistics network

Disassembly centers are essential in a reverse logistics network for breaking end-of-life products and recycling valuable materials. This paper studies a collection-disassembly-delivery problem for a disassembly center, which collects products from collection centers, disassembles products into materials and delivers materials to remanufacturing plants. A set of homogenous vehicles are available for collecting products and delivering materials. The disassembly center makes the best decision on disassembly, inventory, and vehicle routing for collecting products and delivering materials. We propose a mixed-integer linear programming model to formulate the problem, and then improve the two-phase iterative heuristic approach and adaptive large neighborhood search heuristic to solve the problem. This method introduces a tabu search procedure, a learning mechanism, and four new removal operators. A real case and three generated datasets are used to evaluate its computational performance. The results demonstrate that the method can quickly obtain high-quality solutions.