With the emergence of advanced manufacturing and Industry 4.0 technologies, there is a growing interest in coordinating the production and distribution in supply chain management. This paper addresses the production and distribution problems with sequence dependent setup time for multiple customers in flow shop environments. In this complex decision-making problem, an efficient scheduling approach is required to optimize the trade-off between the total cost of tardiness and batch delivery. To achieve this, three new metaheuristic algorithms such as Differential Evolution with different mutation strategy variation and a Moth Flame Optimization, and Lévy-Flight Moth Flame Optimization algorithm are proposed and presented. In addition, a design-of-experiment method is used to identify the best possible parameters for the proposed approaches for the problem under study. The proposed algorithms are validated on a set of problem instances. The variants of differential evolution performed better than the other compared algorithms and this demonstrates the effectiveness of the proposed approach. The algorithms are also validated using an industrial case study.

随着先进的制造业和工业4.0技术的出现，人们对在供应链管理中协调生产和分销的兴趣日益浓厚。本文针对流水车间环境中的多个客户，以顺序依赖的设置时间解决了生产和分销问题。在这个复杂的决策问题中，需要一种有效的调度方法来优化延迟总成本和批次交付之间的折衷。为此，提出并提出了三种新的元启发式算法，如具有不同突变策略变异的差异进化和飞蛾火焰优化，以及Lévy-Flight飞蛾火焰优化算法。此外，实验设计方法用于确定所研究问题的拟议方法的最佳可能参数。所提出的算法在一组问题实例上得到了验证。差分进化的变体比其他比较算法表现更好，这证明了该方法的有效性。还使用工业案例研究对算法进行了验证。