A Cooperative Coevolution Algorithm for the <italic>Seru</italic> Production With Minimizing Makespan

Abstract

Seru production can be used to enhance productivity, such as makespan reduction and manpower saving. Seru system operation includes two NP-hard problems, i.e., seru formation and seru scheduling. The exact solution cannot be obtained by solving only one of seru formation and seru scheduling. We develop a cooperative coevolution algorithm for the Seru production with minimizing makespan by solving the seru formation and seru scheduling simultaneously. The cooperative coevolution algorithm includes two evolution algorithms, i.e., the algorithm combining generic algorithm and local search, and the ant colony optimization algorithm. The former algorithm is used to deal with the evolution of seru formation. The latter is used to find a better seru scheduling. In the cooperative mechanism, the two algorithms cooperate to seek a better solution of seru system operation. Finally, extensive-tested experiments show that the proposed cooperative coevolution algorithm can obtain a better solution than all the existing algorithms and, even, can obtain the exact solution for some medium-and-small instances.INDEX TERMS Cooperative coevolution, manufacturing, makespan, Seru production. I. INTRODUCTIONTo minimize makespan is a widely-used objective in the problems of flow shop, open shop and job shop [1]- [6]. Seru Production can be used to greatly reduce the makespan. Seru Production has been successfully applied by many leading Japanese companies such as Sony, Canon, Panasonic, NEC, Fujitsu, Sharp and Sanyo [4]. Seru Production is based on at least a seru system. A seru system contains one or more serus. Seru, conceived by Sony and Canon in Japan, is lean and agile. Seru is an assembly unit including some simple equipment and one or more multi-skilled workers. Workers in a seru are cross-trained [5] and implement most or all of tasks in the seru. Seru system can obtain a better performance by the reconfiguration of workers than the traditional convey assembly line. Moreover, Seru Production can reduce makespan, setup time, required workers, cost, and shop floor space. A detailed introduction of the seru system and its managerial mechanism can be found in Yin et al. [7], Tekin et al. [8], and Stecke et al. [9]. Some previous researches focused on how seru system to reduce makespan [10]-[13], manpower [14], and training cost [15]. Kaku et al. [10] established a model to investigate

A cooperative coevolution algorithm for complex hybrid seru-system scheduling optimization

“…Heuristic algorithms usually cannot get satisfactory solutions for large-scale instances. Comparatively, evolutionary algorithms can gain satisfactory solutions in limited time and have been successfully applied to pure seru-system [14][15][16][17][18]. Thus, it motivates us to develop an effective evolutionary algorithm to solve the HSSOP with makespan minimization criterion.…”

“…Liu et al [14] designed an algorithm based on NSGA-II to minimize the carbon dioxide emission and makespan. Sun et al [15] developed a cooperative coevolution algorithm by combining GA, local search and ant colony algorithm for the seru production with the minimization of makespan. Yılmaz [16] built a mathematical model for the workforce scheduling problem in seru-system and designed an NSGA-II to minimize the makespan and workload imbalance.…”

Seru üretim sistemlerinde yükleme problemi için karışık tamsayılı bir matematiksel model ve mat-sezgisel çözüm yaklaşımı

“…Sun vd. [24] tarafından yapılan çalışma da iki problemi birlikte ele almaktadır. Yazarlar çalışmalarında iki problem tipinin başlı başına NPzor problem tipi olduğunu söyledikten sonra dikkate alınan problemlerin tek başına çözülmelerinin, seru sistemini uygulayan işletme için kesin bir çözüm sağlamayacağını belirtmişlerdir.…”

Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems

“…Lian et al (2018) [21] considered a multi-skilled worker assignment problem with worker heterogeneity in seru systems. Sun et al (2019) [41] developed a cooperative coevolution algorithm which combining generic algorithm and local search, and the ant colony optimization algorithm for solving seru formulation and seru scheduling problem at the same time with the objective of minimizing makespan. Sun et al (2019) [42] used a cooperative coevolution algorithm to solve seru production problem aim at reducing the total tardiness.…”

“…Sun et al (2019) [41] developed a cooperative coevolution algorithm which combining generic algorithm and local search, and the ant colony optimization algorithm for solving seru formulation and seru scheduling problem at the same time with the objective of minimizing makespan. Sun et al (2019) [42] used a cooperative coevolution algorithm to solve seru production problem aim at reducing the total tardiness. Although the researches above took worker assignment into account, few researches has considered the hierarchy of worker assignment decision and production allocation decision.…”