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Lagrangian heuristic algorithm for green multi-product production routing problem with reverse logistics and remanufacturing
Journal of Manufacturing Systems ( IF 12.1 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.jmsy.2020.11.013 A. Parchami Afra , J. Behnamian
Journal of Manufacturing Systems ( IF 12.1 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.jmsy.2020.11.013 A. Parchami Afra , J. Behnamian
Abstract Today, due to increased market competition, the integration of production and distribution decisions into the supply chain leads to efficiency improvements. Therefore, production routing models have been developed to optimize production and distribution, simultaneously. In recent years, since, the product life cycle has become shorter than in the past, product return policies with fast response times, emphasis on return management, deformation and restorage of finished goods have become very significant. In this paper, the multi-product production routing problem with startup costs and environmental considerations has been studied. Furthermore, reverse logistics and remanufacturing decisions have been integrated. After modeling the problem as mixed-integer linear programming, due to its NP-hardness and the successful application of the Lagrangian Relaxation algorithm (LR) in solving complex supply chain problems, this algorithm has been chosen as the solution method. After applying the standard LR algorithm and the improved LR algorithm that its subgradient optimization method was modified, as a heuristic algorithm, the feasiblizer algorithm is also proposed for feasibilization of the solution obtained from the LR algorithms. To validate the model and solution method, firstly, test problems are solved by GAMS, and then the proposed algorithm is applied to test problems. The numerical results show the good performance of the LR algorithm in medium-size test problems. Finally, based on the computational experiments, managerial insights on the problem have been provided.
中文翻译:
具有逆向物流和再制造的绿色多产品生产路线问题的拉格朗日启发式算法
摘要 今天,由于市场竞争的加剧,将生产和分销决策整合到供应链中可以提高效率。因此,已经开发了生产路线模型以同时优化生产和分销。近年来,由于产品生命周期比以往更短,响应速度快、重视退货管理、成品变形和恢复的产品退货政策变得非常重要。在本文中,研究了具有启动成本和环境因素的多产品生产路线问题。此外,逆向物流和再制造决策已经整合。将问题建模为混合整数线性规划后,由于其 NP-hardness 和拉格朗日松弛算法 (LR) 在解决复杂供应链问题中的成功应用,该算法已被选为解决方法。在应用标准LR算法和改进其次梯度优化方法的改进LR算法后,作为一种启发式算法,还提出了可行化算法对LR算法得到的解进行可行性化。为了验证模型和求解方法,首先用GAMS求解测试问题,然后将提出的算法应用于测试问题。数值结果表明 LR 算法在中等规模的测试问题中具有良好的性能。最后,基于计算实验,提供了对该问题的管理见解。
更新日期:2021-01-01
中文翻译:
具有逆向物流和再制造的绿色多产品生产路线问题的拉格朗日启发式算法
摘要 今天,由于市场竞争的加剧,将生产和分销决策整合到供应链中可以提高效率。因此,已经开发了生产路线模型以同时优化生产和分销。近年来,由于产品生命周期比以往更短,响应速度快、重视退货管理、成品变形和恢复的产品退货政策变得非常重要。在本文中,研究了具有启动成本和环境因素的多产品生产路线问题。此外,逆向物流和再制造决策已经整合。将问题建模为混合整数线性规划后,由于其 NP-hardness 和拉格朗日松弛算法 (LR) 在解决复杂供应链问题中的成功应用,该算法已被选为解决方法。在应用标准LR算法和改进其次梯度优化方法的改进LR算法后,作为一种启发式算法,还提出了可行化算法对LR算法得到的解进行可行性化。为了验证模型和求解方法,首先用GAMS求解测试问题,然后将提出的算法应用于测试问题。数值结果表明 LR 算法在中等规模的测试问题中具有良好的性能。最后,基于计算实验,提供了对该问题的管理见解。