بهینه سازی شبیه سازی برای مسئله برنامه ریزی اقتصادی تصادفی با زمان نصب وابسته به توالی

We consider the stochastic economic lot scheduling problem (SELSP) with lost sales and random demand where switching between products is subject to sequence-dependent setup times. We propose a solution based on simulation optimization using an iterative two-step procedure which combines global policy search with local search heuristics for the traveling salesman sequencing subproblem. To optimize the production cycle, we compare two criteria: minimizing total setup times and evenly distributing setups to obtain a more regular production cycle. Based on a numerical study, we find that a policy with a balanced production cycle leads to lower cost than other policies with unbalanced cycles.