Solving Manufacturing Cell Design Problems Using an Artificial Fish Swarm Algorithm

• Published in: Advances in Artificial Intelligence and Soft Computing Vol. 9413; pp. 282 - 290
• Main Authors: Soto, Ricardo, Crawford, Broderick, Vega, Emanuel, Paredes, Fernando
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2015; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Artificial fish swarm algorithm; Artificial intelligence; Computer vision; Health & safety aspects of computing; Manufacturing cell design problem; Metaheuristic
• ISBN: 9783319270593; 3319270591
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-27060-9_23

The design of manufacturing cells is a manufacturing strategy that involves the creation of an optimal design of production plants, whose main objective is to minimize movements and exchange of material between these cells. Optimal solution of large scale manufacturing cell design problems (MCDPs) are often computationally unfeasible and only heuristic and approximate methods are able to handle such problems. Artificial fish swarm algorithm (AFSA) belongs to the swarm intelligence algorithms, which based on population search, are able to solve complex optimization problems. In this paper we present an AFSA-based approach to solve the MCDP by using the classic Boctor’s mathematical model. The obtained results show that the proposed algorithm produces optimal solutions for all the 50 studied instances.