汽車和新型產(chǎn)業(yè)裝備的應(yīng)用于制造(文件)
【正文】 manufacturing and logistic systems along global supply chains. As first steps, a mathematical program of the integrated scheduling problem is developed and tested. Obtained results and the limited size of putationally manageable scenarios are both motivation and starting point for the development of forthing heuristics.Article Outline1. Introduction2. Global manufacturing chains3. Integration of production and logistics . Production and transport scheduling problem. Collaborative planning4. Enabling collaboration5. Investigative framework . Adaptation of PTSP . Nomenclature: sets. Nomenclature: parameters. Nomenclature: positive variables. Nomenclature: binary variables. Model assumptions. Mathematical model. Test scenario and putational analysis6. OutlineAcknowledgementsReferences全球供應(yīng)鏈競爭與合作中，制造系統(tǒng)和物流系統(tǒng)集成方式研究Indirect predictive monitoring in flexible manufacturing systemsOriginal Research ArticleJournal of Materials Processing TechnologyReliability analysis of an automated pizza production lineOriginal Research ArticleSpill Science amp。Original Research ArticleJournal of Food EngineeringDevelopment of a National Marine Oil Transportation System ModelOriginal Research ArticleRobotics and ComputerIntegrated ManufacturingThe requirements and possibilities balance method used for production planning in the manufacturing assembly systemsReview ArticleEuropean Journal of Operational ResearchIntegrating manufacturing and logistic systems along global supply chainsOriginal Research ArticlePowder TechnologyGraphical abstractA robust and pletely reliable syngas cleaning technology has not been developed especially for gas cleaning over 600Original Research ArticleJournal of Manufacturing SystemsScheduling belongs to the special class of NPhard problems for which no polynomial time algorithm has been found. Therefore, a schedule that is the best possible nearoptimal solution is often acceptable. This paper presents a scheduling approach, based on Genetic Algorithms (GAs), developed to address the scheduling problem in manufacturing systems constrained by both machines and workers. This genetic algorithm utilizes a new chromosome representation, which takes into account machine and worker assignments to jobs. A set of experiments
醫(yī)療健康相關(guān)推薦
鄂ICP備17016276號-1