Reza Ramezanian , Mohammad Hosein Mahdavi , Shahrooz Shahparvari
{"title":"Integrated mobile facility production and distribution scheduling planning; A synchronized solution framework","authors":"Reza Ramezanian , Mohammad Hosein Mahdavi , Shahrooz Shahparvari","doi":"10.1016/j.amc.2025.129277","DOIUrl":null,"url":null,"abstract":"<div><div>This research explores supply chain modeling for mobile production facilities, emphasizing distribution and manufacturing processes. The focus is on a fleet of production-equipped trucks that manufacture orders during transit to customer locations. A mixed-integer linear programming (MILP) model is proposed to address the production and delivery planning problem, minimizing total costs, including production, transportation, and driver expenses. The computational strategy integrates Benders Decomposition with a Rolling Horizon heuristic. The accelerated Benders Decomposition reduced computational time by 25–35 % across large-scale scenarios. Numerical experiments demonstrated that the hybrid method achieved optimal or near-optimal solutions with cost savings of 12–18 % compared to standalone methods. For example, in scenarios with 15 mobile facilities and 10 products, the methodology outperformed CPLEX in solution time and quality. The results highlight the practical applicability of the proposed framework, enabling e-commerce enterprises to enhance customer service levels by reducing delivery times by 10–15 %. This study provides a robust and efficient approach to optimizing synchronized production and delivery operations while eliminating the costs associated with fixed manufacturing facilities.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"494 ","pages":"Article 129277"},"PeriodicalIF":3.5000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325000049","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
This research explores supply chain modeling for mobile production facilities, emphasizing distribution and manufacturing processes. The focus is on a fleet of production-equipped trucks that manufacture orders during transit to customer locations. A mixed-integer linear programming (MILP) model is proposed to address the production and delivery planning problem, minimizing total costs, including production, transportation, and driver expenses. The computational strategy integrates Benders Decomposition with a Rolling Horizon heuristic. The accelerated Benders Decomposition reduced computational time by 25–35 % across large-scale scenarios. Numerical experiments demonstrated that the hybrid method achieved optimal or near-optimal solutions with cost savings of 12–18 % compared to standalone methods. For example, in scenarios with 15 mobile facilities and 10 products, the methodology outperformed CPLEX in solution time and quality. The results highlight the practical applicability of the proposed framework, enabling e-commerce enterprises to enhance customer service levels by reducing delivery times by 10–15 %. This study provides a robust and efficient approach to optimizing synchronized production and delivery operations while eliminating the costs associated with fixed manufacturing facilities.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.