Optimizing a Disassembly Sequence Planning With Success Rates of Disassembly Operations via a Variable Neighborhood Search Algorithm

Hongyu Liu,Linsheng Zhang

doi:10.1109/access.2021.3101221

Abstract

Disassembly planning is an effective way to recycle valuable parts or materials from end-of-life products. Due to the parts are easily affected by some unpredictable factors in the real disassembly process (such as defective parts and human factors), there may be failure operations that cannot successfully disassemble the corresponding parts in the real world. Therefore, a partial disassembly sequence planning with uncertainty is proposed in the paper, where the success rates of disassembly operations are formulated to model an expected profit-based disassembly sequence planning. Also, a general variable neighborhood search algorithm is developed to optimize the mathematical model. Meanwhile, in the approach, a heuristic procedure is utilized to obtain a high-quality initial solution, and four different neighborhood structures are introduced to improve the disassembly solution. Its superiority and effectiveness are well illustrated by two case studies and comparison with two existing metaheuristics, i.e., artificial bee colony algorithm and genetic algorithm.

Highlights

With the development and advancement of technology, the product life cycle is getting shorter, increasing the number of end-of-life (EOL) products sent to the landfill [1, 2]
PROBLEM STATEMENT A new Disassembly sequence planning (DSP) problem considering the uncertainty of the success rates of disassembly operations is studied in our work
COMPUTATIONAL EXAMPLES AND ANALYSIS This paper presents two cases modified by the previous works [30, 43] since no actual research instances have been found yet

Summary

INTRODUCTION

With the development and advancement of technology, the product life cycle is getting shorter, increasing the number of end-of-life (EOL) products sent to the landfill [1, 2]. Wang et al construct a stochastic multi-objective partial DLBP model considering the uncertainty, economic benefits, and environmental protection They design a new discrete flower pollination algorithm to acquire a high-quality disassembly sequence [23]. To better reflect the real disassembly process, a new optimization DSP model with a success rate of disassembly operations subject to the precedence and cycle time constraints is established, the purpose of which is to determine a feasible disassembly sequence with profit maximization. PROBLEM STATEMENT A new DSP problem considering the uncertainty of the success rates of disassembly operations is studied in our work. A. PRECEDENCE RELATIONSHIP CONSTRAINTS In the process of performing part disassembly, precedence relationships between tasks of a product need to be followed, which can determine the feasibility of the disassembly sequence. Some complicated precedence relationships exist in DSP, including OR within AND and AND within OR, and the AND precedence, OR precedence as well as inserting dummy tasks can be used expressing these complicated precedence relationships, which are represented by the dotted circle as Fig. 1 shows

OR within AND

COMPUTATIONAL EXAMPLES AND ANALYSIS

CONCLUSION