Capacitated multi-objective disassembly scheduling with fuzzy processing time via a fruit fly optimization algorithm.

This work proposes a capacitated fuzzy disassembly scheduling model with cycle time and environmental cost as parameters, which has broad applications in remanufacturing and many other production systems. Disassembly scheduling is not always given accurately as a time quota in a production system, particularly in the obsolete product remanufacturing process. It is important to study novel models and algorithms based on uncertainty processing time to solve uncertainty disassembly scheduling problems. In this paper, a mixed-integer mathematical programming model is proposed to minimize the cycle time and environmental cost, whilst a metaheuristic approach based on a fruit fly optimization algorithm (FOA) is developed to find a fuzzy disassembly scheduling scheme. To estimate the effectiveness of the proposed method, the proposed algorithm is tested with different size cases of product disassembly scheduling. Furthermore, experiments are conducted to compare with other multi-objective optimization algorithms. The computational results demonstrate the proposed algorithm outperforms other algorithms on computational efficiency and applicability to different problems. Finally, a case study is described to illustrate the proposed method. The main contribution of this current work shows the proposed algorithm to solve the problem of disassembly scheduling in an uncertain environment practically and efficiently.