2017
DOI: 10.1016/j.ijpe.2016.06.026
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Production and setup policy optimization for hybrid manufacturing–remanufacturing systems

Abstract: Hybrid systems that use both raw materials (manufacturing mode) and returned products (remanufacturing mode) as a supply for their production process are considered. The system studied consists of one facility that necessitates setup for switching from one production mode to another. As in industrial practice, the flow rate of returned products is usually below the market demand, switching from one mode to another is unavoidable for meeting the demand. Therefore, determining the optimal production and setup po… Show more

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Cited by 36 publications
(9 citation statements)
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“…Responsiveness, robustness, and resilience (known as "Triple R") become more and more important in logistics and material handling [72] because customer satisfaction is based on "Triple R"-based performance of manufacturing and related logistics operations [73]. The objective functions and constraints are based on the problems of typical material handling related problems, like facility location [74], allocation [75], lot sizing [76][77][78], shortage planning [79], scheduling [80], inventory planning [81], and ergonomic [82] and trade policy aspects [83]. Integrated approaches [52], multi-objective optimization problems [53] can be solved with other effective optimization methods, like teaching-learning based optimization [54], force generated graph algorithms [55], agent-based optimization methods [56], or TOPSIS [57].…”
Section: Content Analysismentioning
confidence: 99%
“…Responsiveness, robustness, and resilience (known as "Triple R") become more and more important in logistics and material handling [72] because customer satisfaction is based on "Triple R"-based performance of manufacturing and related logistics operations [73]. The objective functions and constraints are based on the problems of typical material handling related problems, like facility location [74], allocation [75], lot sizing [76][77][78], shortage planning [79], scheduling [80], inventory planning [81], and ergonomic [82] and trade policy aspects [83]. Integrated approaches [52], multi-objective optimization problems [53] can be solved with other effective optimization methods, like teaching-learning based optimization [54], force generated graph algorithms [55], agent-based optimization methods [56], or TOPSIS [57].…”
Section: Content Analysismentioning
confidence: 99%
“…Khoury (2016) extracted optimal production rate for a single-machine and single-product FPMS to minimize sum of holding and shortage costs when times between failures have exponential distribution and the repair time has general distribution via analytical method. Polotski et al (2017) determined optimal production rate for failure-prone manufacturing systems considering rework operations on the returned products from the quality control unit. In this article, setup time cost as well as holding and shortage costs was considered and HPP was obtained for this problem by numerical solution of HJB equation.…”
Section: Failure-prone Manufacturing Systemsmentioning
confidence: 99%
“…Bazan et al [2] presented an outstanding review of mathematical inventory models for reverse logistics. Polotski et al [23] devised optimal production and setup policies for hybrid production-remanufacturing systems. Recently, Singh and Sharma [29] proposed a supply chain model under reverse logistics and inflation.…”
Section: Introductionmentioning
confidence: 99%