Analysis of the usage of the Iterated Greedy on the integrated production-distribution problem

• Grant number: 16/09080-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2016
• End date: October 31, 2017
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Roberto Fernandes Tavares Neto
• Grantee: Guilherme Sproesser Ferreira
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

For decades, the problems about scheduling and routing has been the target ofhighly relevant research, both from a theoretical point of view and its application. Of abusiness point of view, both the problems of optimization techniques are relevant toenhance cost indicators, Delivery Times, among others. For the theoretical point of view,these studies are explained by the existence of a virtually unlimited number ofproblems characterized as NP-Hard. Recently, there has been a growing numberpublications that deal with integrated planning between the decisions of production anddistribution (IPDP). In these studies, we see the practical relevance - in which the applicationintegrated planning techniques results in significant financial gains - and relevancetheoretical - in which it is realized that there are few studies for these relevant problems NP-Difficult. In this scenario, this project proposes a search on search techniquesbased on optimization for interactive greedy method to enable integrated planningbetween production and distribution. It is intended to study a production environment based on aflowshop environment with two machines. The distribution is carried out by a finite set oflimited capacity vehicles, which can perform one or more routes. We seek to minimize themakespan of the system as a whole, ie, the time when the last vehicle returns to the origin.Both the manufacturing environment and distribution are known to be NP problemsDifficult. Thus, it is understood that the combination of them is an NP-Hard problem. Hopingthat this research generates a set of benchmarks to be made available to the communityscientific about how IG techniques may be useful in planning integrated production-distribution.