Pub Date : 2013-10-01DOI: 10.1016/j.ejor.2015.05.006
J. Framiñan, P. Perez-Gonzalez
{"title":"On heuristic solutions for the stochastic flowshop scheduling problem","authors":"J. Framiñan, P. Perez-Gonzalez","doi":"10.1016/j.ejor.2015.05.006","DOIUrl":"https://doi.org/10.1016/j.ejor.2015.05.006","url":null,"abstract":"","PeriodicalId":243849,"journal":{"name":"Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM)","volume":"2 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117412160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tarik Zouadi, A. Yalaoui, Mohamed Reghioui, Kamal Eddine El Kadiri
This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations. We investigate here a lot-sizing problem in which the demand for items can be satisfied by both the new and the remanufactured products. We assume that produced and recovered (repaired or remanufactured) items are of the same quality. Two types of inventories are involved in this problem. The manufactured and remanufactured items are stored in the first inventory. The returned products are collected in the second inventory and then remanufactured. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the holding, the set up and preparation costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The paper proposes an extension of the reverse Wagner/Whitin dynamic production planning and inventory control model, an adaptation of the well-known Silver and Meal (SM) and Part Period Balancing (PPB) heuristics, a memetic algorithm (MA) and a greedy randomized adaptive search procedure (GRASP). In this later, an exact resolution was used as a local search to find the best production rates for the periods determined by the randomized heuristics. Numerical experiments were conducted on a set of 300 instances with up to 48 periods. The results show that both metaheuristics give high-quality solutions in moderate computational time.
{"title":"Lot-sizing for production planning in a recovery system with returns","authors":"Tarik Zouadi, A. Yalaoui, Mohamed Reghioui, Kamal Eddine El Kadiri","doi":"10.1051/ro/2014044","DOIUrl":"https://doi.org/10.1051/ro/2014044","url":null,"abstract":"This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations. We investigate here a lot-sizing problem in which the demand for items can be satisfied by both the new and the remanufactured products. We assume that produced and recovered (repaired or remanufactured) items are of the same quality. Two types of inventories are involved in this problem. The manufactured and remanufactured items are stored in the first inventory. The returned products are collected in the second inventory and then remanufactured. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the holding, the set up and preparation costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The paper proposes an extension of the reverse Wagner/Whitin dynamic production planning and inventory control model, an adaptation of the well-known Silver and Meal (SM) and Part Period Balancing (PPB) heuristics, a memetic algorithm (MA) and a greedy randomized adaptive search procedure (GRASP). In this later, an exact resolution was used as a local search to find the best production rates for the periods determined by the randomized heuristics. Numerical experiments were conducted on a set of 300 instances with up to 48 periods. The results show that both metaheuristics give high-quality solutions in moderate computational time.","PeriodicalId":243849,"journal":{"name":"Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115636278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Two objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic; this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.
{"title":"Multi-objective optimization using genetic algorithms of multi-pass turning process","authors":"A. Jabri, A. E. Barkany, A. E. Khalfi","doi":"10.4236/ENG.2013.57072","DOIUrl":"https://doi.org/10.4236/ENG.2013.57072","url":null,"abstract":"In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Two objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic; this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.","PeriodicalId":243849,"journal":{"name":"Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132225105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：