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Analysis of the use of IG (Iterated Greedy) in the problem of minimizing the flow time of finished products in an integrated production-distribution system

Grant number: 17/20294-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2017
Effective date (End): July 31, 2018
Field of knowledge:Engineering - Production Engineering
Principal Investigator:Roberto Fernandes Tavares Neto
Grantee:Milena Vannuchi Magnani
Home Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Associated research grant:16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings, AP.TEM

Abstract

Currently there are researches of great relevance that address problems of both routing and scheduling in the theoretical and practical spheres. From the theoretical point of view, there is a virtually unlimited number of problems characterized as NP-Difficult and from the business point of view, the optimization techniques developed through such research allow to improve cost indicators, delivery time, Makespan, among others. In view of such a scenario, the present project proposes a research that seeks to study and develop optimization techniques by the greedy iterative method, allowing integrated planning between production and distribution. The environment studied will be a flowshop composed of two machines. The distribution is performed by a finite set of vehicles with limited capacity, which can carry out one or more routes. It seeks to minimize the flow time of finished products, that is, from the moment they are ready and are stocked, until the moment they are delivered to their final destination. Both the manufacturing environment and distribution are known to be NP-Difficult problems. Thus, it is understood that the combination thereof is an NP-Difficult problem. It is hoped that this research will generate a set of benchmarks that will be made available to the scientific community as to how GI techniques can be useful in integrated production-distribution planning. (AU)