Searching for the Optimum Number of Capacitated Materialistic Cars for an Automotive Manufacturing Cell Using a Shuffled Frog Leap Algorithm

Searching for the Optimum Number of Capacitated Materialistic Cars for an Automotive Manufacturing Cell Using a Shuffled Frog Leap Algorithm

Denise Barzaga (Corporación Mexicana de Investigación en Materiales S.A. de C.V., Mexico) and Elías Carrum (Corporación Mexicana de Investigación en Materiales S.A. de C.V., Mexico)
DOI: 10.4018/978-1-5225-8131-4.ch020

Abstract

Due to the worldwide strengthening of the automotive sector, it presents itself as a challenge for the companies that comprise it to immerse themselves in processes of continuous improvement that contribute to increasing the satisfaction of the needs of its customers, as well as achieving a better positioning in the market. This goal is impossible to reach without proper design and management of the supply chain, consideration of issues related to logistics and inclusion of innovative techniques. In the chapter, the authors considered a manufacturing cell responsible for making the assembly of seats for the automotive industry. Waiting times and blocking of machines are incurred by not using the optimum number of vehicles to be used for the transfer of materials and the capacity with which they should count. The objective of this research is to know near-optimum quantities and capacities of the vehicles, materialistic cars, to avoid this situation. The use of mathematical formulations, simulation, and optimization techniques will be used to solve the problem.
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Literature Review

Analyzing previous investigative works related to the problematic treated, different approaches are appraised to determine the amount of vehicles necessary to realize the distribution of products or materials.

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