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Combinatorial optimization methods for disassembly line balancing

机译:拆卸线平衡的组合优化方法

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Disassembly takes place in remanufacturing, recycling, and disposal with a line being the best choice for automation. The disassembly line balancing problem seeks a sequence which: minimizes workstations, ensures similar idle times, and is feasible. Finding the optimal balance is computationally intensive due to factorial growth. Combinatorial optimization methods hold promise for providing solutions to the disassembly line balancing problem, which is proven to belong to the class of NP-complete problems. Ant colony optimization, genetic algorithm, and H-K metaheuristics are presented and compared along with a greedy/hill-climbing heuristic hybrid. A numerical study is performed to illustrate the implementation and compare performance. Conclusions drawn include the consistent generation of optimal or near-optimal solutions, the ability to preserve precedence, the speed of the techniques, and their practicality due to ease of implementation.
机译:拆卸是在重新制造,回收和处置中进行的,生产线是自动化的最佳选择。拆装线平衡问题寻求一个顺序:最大程度地减少工作站,确保类似的闲置时间,并且可行。由于阶乘增长,找到最佳平衡需要大量的计算工作。组合优化方法有望为拆卸线平衡问题提供解决方案,事实证明,该问题属于NP完全问题类。提出并比较了蚁群优化,遗传算法和H-K元启发式算法以及贪婪/爬坡启发式混合算法。进行了数值研究,以说明实现方式并比较性能。得出的结论包括一致生成最佳或接近最佳的解决方案,保留优先级的能力,技术的速度以及由于易于实现而具有的实用性。

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