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An improved immune clonal selection algorithm for bi-objective robotic assemble line balancing problems considering time and space constraints

Binghai Zhou (School of Mechanical Engineering, Tongji University, Shanghai, China)
Qiong Wu (School of Mechanical Engineering, Tongji University, Shanghai, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 8 July 2019

Abstract

Purpose

The extensive applications of the industrial robots have made the optimization of assembly lines more complicated. The purpose of this paper is to develop a balancing method of both workstation time and station area to improve the efficiency and productivity of the robotic assembly lines. A tradeoff was made between two conflicting objective functions, minimizing the number of workstations and minimizing the area of each workstation.

Design/methodology/approach

This research proposes an optimal method for balancing robotic assembly lines with space consideration and reducing robot changeover and area for tools and fixtures to further minimize assembly line area and cycle time. Due to the NP-hard nature of the considered problem, an improved multi-objective immune clonal selection algorithm is proposed to solve this constrained multi-objective optimization problem, and a special coding scheme is designed for the problem. To enhance the performance of the algorithm, several strategies including elite strategy and global search are introduced.

Findings

A set of instances of different problem scales are optimized and the results are compared with two other high-performing multi-objective algorithms to evaluate the efficiency and superiority of the proposed algorithm. It is found that the proposed method can efficiently solve the real-world size case of time and space robotic assembly line balancing problems.

Originality/value

For the first time in the robotic assembly line balancing problems, an assignment-based tool area and a sequence-based changeover time are took into consideration. Furthermore, a mathematical model with bi-objective functions of minimizing the number of workstations and area of each station was developed. To solve the proposed problem, an improved multi-objective immune clonal selection algorithm was proposed and a special coding scheme is designed.

Keywords

Acknowledgements

This research is supported by the National Natural Science Foundation of China under the Grant 71471135.

Citation

Zhou, B. and Wu, Q. (2019), "An improved immune clonal selection algorithm for bi-objective robotic assemble line balancing problems considering time and space constraints", Engineering Computations, Vol. 36 No. 6, pp. 1868-1892. https://doi.org/10.1108/EC-11-2018-0512

Publisher

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Emerald Publishing Limited

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