S. Mallah, Alaf Aloullal, Oualid Kamach, K. Kouiss, N. Najid, L. Deshayes
{"title":"A novel integration approach for a complex supply chain optimization problem in an export bulk port","authors":"S. Mallah, Alaf Aloullal, Oualid Kamach, K. Kouiss, N. Najid, L. Deshayes","doi":"10.1109/CoDIT49905.2020.9263911","DOIUrl":null,"url":null,"abstract":"Supply chain management is the art and science of delivering the right product in good quality, to the right customer, in the right place and at the right time. Bringing about the emergence of this much-wanted value is carried out by a synergic integration of an optimization tool within the control system rather than developing an isolated optimization solution. Then, if we move to the optimal planning tool in particular, it is believed that, the integration of planning and scheduling decisions of storage, routing and loading together making up an integrated optimization plan without contradictory goals, is vital for an efficient use of the three aforementioned bulk port operations. In this paper, we present an architecture to get the optimization tool fit into the industrial control system to consider disturbances, feedback cycles and dynamics. Then, we propose a novel approach of the integration of the three sub-optimizers using the systems engineering method. The novel aspect of this contribution is twofold. First, rather than only describing the problem before formulating the mathematical model. The systems engineering method, allowed to specify the problem with an in-depth scientific analysis, in order to get a complete and consistent mastery of the problem. Therefore, the problem formulation will not miss important use cases of the complex supply chain. Second, the resulting specified planning integration helps the whole planning tool converge in a reasonable time by avoiding quasi-infinite interaction loops.","PeriodicalId":355781,"journal":{"name":"2020 7th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th International Conference on Control, Decision and Information Technologies (CoDIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoDIT49905.2020.9263911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Supply chain management is the art and science of delivering the right product in good quality, to the right customer, in the right place and at the right time. Bringing about the emergence of this much-wanted value is carried out by a synergic integration of an optimization tool within the control system rather than developing an isolated optimization solution. Then, if we move to the optimal planning tool in particular, it is believed that, the integration of planning and scheduling decisions of storage, routing and loading together making up an integrated optimization plan without contradictory goals, is vital for an efficient use of the three aforementioned bulk port operations. In this paper, we present an architecture to get the optimization tool fit into the industrial control system to consider disturbances, feedback cycles and dynamics. Then, we propose a novel approach of the integration of the three sub-optimizers using the systems engineering method. The novel aspect of this contribution is twofold. First, rather than only describing the problem before formulating the mathematical model. The systems engineering method, allowed to specify the problem with an in-depth scientific analysis, in order to get a complete and consistent mastery of the problem. Therefore, the problem formulation will not miss important use cases of the complex supply chain. Second, the resulting specified planning integration helps the whole planning tool converge in a reasonable time by avoiding quasi-infinite interaction loops.