A simulation optimization approach-based genetic algorithm for lot sizing problem in a MTO sector

Author

Ammeri, Ahmed ; Dammak, Mohamed Chedly ; Chabchoub, Habib ; Hachicha, Walid ; Masmoudi, Faouzi

Author_Institution

Unit of Logistic, Ind. & Quality Manage. (LOGIQ), Higher Inst. of Ind. Manage., Sfax, Tunisia

fYear

2013

fDate

29-31 May 2013

Firstpage

476

Lastpage

481

Abstract

In this paper, a combined simulation and Genetic Algorithm (GA) optimization model is developed to solve the Lot Sizing Problem (LSP) in a Make to Order (MTO) supply chain. The simulation model is performed using ARENA software. GA model is implemented using Visual Basic for Application (VBA) language, because it ensures exchanges between ARENA software and Ms Excel. The GA and simulation models operate in parallel over time with interactions. The case study´s objective is to determine a fixed optimal lot size for each manufactured product type that will ensure order mean flow time target for each finished product. The comparative results with OptQuest software, which is used a global search method, to illustrate the efficiency and effectiveness of the proposed approach.

Keywords

Visual BASIC; genetic algorithms; lot sizing; order processing; product customisation; production engineering computing; search problems; spreadsheet programs; supply chains; ARENA software; GA; LSP; MTO sector; Ms Excel; OptQuest software; VBA; Visual Basic for application language; global search method; lot sizing problem; make to order supply chain; manufactured product type; order mean flow time target; simulation optimization approach-based genetic algorithm; Computational modeling; Genetic algorithms; Object oriented modeling; Optimization; Sociology; Statistics; Supply chains; Case study; Genetic Algorithm; Lot sizing problem; Make to order supply chain; Simulation Optimization; VBA;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Logistics and Transport (ICALT), 2013 International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4799-0314-6

Type

conf

DOI

10.1109/ICAdLT.2013.6568505

Filename

6568505