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Showing 2 results for Moghadam

Maria Moghadam, Iraj Mahdavi, Ali Tajdin, Babak Shirazi,
Volume 0, Issue 0 (IN PRESS 2025)
Abstract

Addressing the complex challenges of supply chain management requires integrating sustainable practices, advanced technologies, and innovative solutions. This review article explores the concept of sustainable closed-loop supply chains as a means to balance economic, social, and environmental goals. We examine the relationship between sustainable closed-loop supply chains and advanced technologies such as artificial intelligence, machine learning, game theory, and metaheuristic algorithms. Various aspects of supply chain models, sustainability, and the integration of innovative solutions are analyzed to identify key challenges and opportunities in the implementation of sustainable closed-loop supply chains. We highlight the potential benefits of adopting such practices, including cost savings, enhanced brand reputation, and increased customer loyalty. The article also discusses the importance of managing risks associated with cost, environment, social issues, and operations. Our review emphasizes the need for ongoing research and collaboration among stakeholders to address existing research gaps and foster a comprehensive understanding of sustainable closed-loop supply chains. This includes empirical studies on real-world implementation, advanced optimization techniques, sustainable business models, and policy frameworks. Ultimately, this article aims to contribute to the development of more resilient, efficient, and sustainable supply chains that benefit businesses and society alike.

R. Tavakolimoghadam, M. Vasei,
Volume 19, Issue 4 (IJIE 2008)
Abstract

  In this paper, a single machine sequencing problem is considered in order to find the sequence of jobs minimizing the sum of the maximum earliness and tardiness with idle times (n/1/I/ETmax). Due to the time complexity function, this sequencing problem belongs to a class of NP-hard ones. Thus, a special design of a simulated annealing (SA) method is applied to solve such a hard problem. To compare the associated results, a branch-and-bound (B&B) method is designed and the upper/lower limits are also introduced in this method. To show the effectiveness of these methods, a number of different types of problems are generated and then solved. Based on the results of the test problems, the proposed SA has a small error, and computational time for achieving the best result is very small.



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