Abstract The production routing problem seeks to simultaneously optimize production, routing, and inventory decisions for the plant and the suppliers. In this article an integrated multi-objective sustainable pricing-production-workforce-routing problem is presented for perishable products. Total profit, workforce planning, and vehicle fuel consumption are considered as objective functions due to the importance of operational performance, social, and environmental concerns. The application of the proposed approach is investigated using real case data from a dairy product supply chain. Furthermore, a new solution approach, called Fuzzy Domination Self-Learning Non-Dominated Sorting Algorithm (FDSL-NSGA-II), is developed to solve the problem. The results show that the Pareto solutions of FDSL-NSGA-II outperform those of the classic NSGA-II. Moreover, the findings show that the proposed model can create a surpassing tradeoff between the various aspects of a supply chain, including production, distribution, and workforce planning. In addition, it concurrently optimizes the selling price and protects the environment from the negative impacts of greenhouse gas emissions (GHGs). A comprehensive analysis of the results reveals several managerial insights for decision makers in the logistics industry.

中文翻译：

---

考虑需求不确定性的易腐产品的可持续定价-生产-劳动力-路由问题；乳制品行业的案例研究

摘要 生产路径问题旨在同时优化工厂和供应商的生产、路径和库存决策。在本文中，针对易腐产品提出了一个集成的多目标可持续定价-生产-劳动力-路径问题。由于运营绩效、社会和环境问题的重要性，总利润、劳动力规划和车辆燃料消耗被视为目标函数。使用来自乳制品供应链的真实案例数据研究了所提出方法的应用。此外，还开发了一种新的解决方法，称为模糊支配自学习非支配排序算法 (FDSL-NSGA-II) 来解决该问题。结果表明，FDSL-NSGA-II 的帕累托解优于经典的 NSGA-II。此外，研究结果表明，所提出的模型可以在供应链的各个方面（包括生产、分销和劳动力规划）之间创造出超越性的权衡。此外，它同时优化了销售价格并保护环境免受温室气体排放 (GHG) 的负面影响。对结果的综合分析揭示了物流行业决策者的一些管理见解。它同时优化了销售价格并保护环境免受温室气体排放 (GHG) 的负面影响。对结果的综合分析揭示了物流行业决策者的一些管理见解。它同时优化了销售价格并保护环境免受温室气体排放 (GHG) 的负面影响。对结果的综合分析揭示了物流行业决策者的一些管理见解。