An Adaptive Genetic Algorithm for Production Scheduling on Manufacturing Systems with Simultaneous Use of Machines and A
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An Adaptive Genetic Algorithm for Production Scheduling on Manufacturing Systems with Simultaneous Use of Machines and AGVs Danilo Sipoli Sanches1 · Josimar da Silva Rocha1 · Marcelo Favoretto Castoldi1 · Orides Morandin Jr.2 · Edilson Reis Rodrigues Kato2
Received: 13 November 2014 / Revised: 22 February 2015 / Accepted: 4 March 2015 © Brazilian Society for Automatics–SBA 2015
Abstract The problem of production scheduling of manufacturing systems involves the system modeling task and the application of a technique to solve it. This kind of scheduling is characterized by the large number of possible solutions, where several researches have been using the genetic algorithms as a search method to solve this problem, since these algorithms have the capacity of globally exploring the search space and to find good solutions quickly. This paper proposes the use of adaptive genetic algorithm to solve this kind of scheduling problem. The aim of this paper was to obtain a good production schedule considering simultaneous use of machines and automated guided vehicles that minimize the makespan with low running time. The results of this paper were validated in large scenarios and compared with other approach. These results are presented and discussed in this paper. Keywords Scheduling · Evolutionary computing · Control theory · Heuristic methods · Flexible manufacturing system
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Danilo Sipoli Sanches [email protected]; [email protected] Josimar da Silva Rocha [email protected] Marcelo Favoretto Castoldi [email protected] Orides Morandin Jr. [email protected] Edilson Reis Rodrigues Kato [email protected]
1
Federal Technological University of Parana, Av. Alberto Carazzai, Cornelio Procopio, PR, Brazil
2
Federal University of Sao Carlos, Via. Washington Lus, Sao Carlos, SP, Brazil
1 Introduction Manufacturing systems with shared resources such as machines and transport systems have been used for production automation, and they allow flexibility consistent with the needs of a good share of manufactures in the market. This flexibility occurs because the machines can be used to several different operations and the products can be processed by several different machines. The problem generated by this flexibility is the considerable effort to define the production scheduling and the use of available resources over time, in order to reach certain performance criteria (Tay and Ho 2008; Zhang et al. 2012; Naderi et al. 2009). One of the difficulties in production scheduling of a manufacturing system with shared resources is the product scheduling with simultaneous use of machines and transport systems. Among the existing transportation systems, the automated guided vehicles (AGVs) stand out. AGVs are small and stand-alone vehicles, which move materials to and from value aggregate operations. Typically, products in a manufacturing system with shared resources visit different machines for different operations, requiring a transport system to transport the products among the machines at its processing rou
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