An iterated local search algorithm for flexible flow lines with sequence dependent setup times to minimize total weighted completion

摘要

This paper explores flexible flow lines where setup times are sequence dependent. The optimization criterion is the minimization of total weighted completion time. We propose an An iterated local search algorithm (ILS) is proposed to tackle the problem. Among different meta-heuristics, the iterated greedy algorithm (IGA) has shown high performance for simpler problems such as flowshops. This paper looks at applying an adapted IGA to a much more complex problem where a well-known algorithm is adapted and evaluated. In this adaptation, a completely different decoding operator is applied, and hybridized with an effective local search and another temperature calculation procedure. Performance is also assessed using a comparison with a well-known random key genetic algorithm. A benchmark is set to evaluate the proposed algorithm, and the obtained ILS results are compared against some other algorithms. The effectiveness of ILS is demonstrated through this comparison.