Optimization of product line considering compatibility and reliability via discrete imperialist competitive algorithm

In the era of mass customization, designing optimal products is one of the most critical decision-making for a company to stay competitive. More and more customers like customized products, which will bring challenges to the product line design and the production. If a company adopts consumers' favorite levels, this may lead to lower product reliability, or incompatibility among the components that make up the product. Moreover, it is worth outsourcing certain attribute levels so as to reduce production cost, but customers may dislike these levels because of their delivery delay. If managers consider the compatibility issue, the quality issue, outsource determination, and the delivery due date in the product design and production stages, it will avoid unreasonable product configuration and many unnecessary expenses, thereby bringing benefits to the company. To solve this complicated problem, we establish a nonlinear programming model to maximize a metric about profit, termed as Per-capita-contribution Margin considering Reliability Penalty (PMRP). Since the integrated product line design and production problem is NP-hard, we propose an improved Discrete Imperialist Competitive Algorithm (DICA) that can find a most powerful imperialist (i.e., solution) by the competition among all countries in the world. The proposed DICA is compared with genetic algorithm (GA) and simulated annealing (SA) through extensive numerical experiment, and the results show that DICA has more attractive performance than GA and SA.

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A revised imperialist competition algorithm for cellular manufacturing optimization based on product line design

Journal of Industrial and Management Optimization ◽

10.3934/jimo.2021175 ◽

2021 ◽

Vol 0 (0) ◽

pp. 0

Author(s):

Chunfeng Liu ◽

Yuanyuan Liu ◽

Jufeng Wang

Keyword(s):

Cellular Manufacturing ◽

Market Competition ◽

Imperialist Competitive Algorithm ◽

Product Line ◽

Discrete Problem ◽

Solution Quality ◽

Product Line Design ◽

Competitive Algorithm ◽

Manufacturing Optimization ◽

Line Design

<p style='text-indent:20px;'>Due to the fierce market competition, enterprises try to satisfy customers' requirements for personalized products in order to maximize profit or market share of their products. This not only needs to determine the product variants through product line design, but also needs to pay attention to resource allocation in the manufacturing process. This paper proposes a cellular manufacturing optimization model that considers the market and production. If the company excessively pursues the satisfaction of customers' personalized needs, the manufacturing time and cost may increase accordingly. Of course, with the restriction of production capacity in manufacturing cells and the expectation of reducing cost, managers cannot design attributes' levels of a product line casually, which may result in its unstable marketing share and profit. Therefore, the product demand influenced by customers' preferences could be a key factor to link market and production. The objective of propose model is to maximize product profit which consists of revenue and miscellaneous costs (material, processing, transportation, final assembly and fixed costs). A revised imperialist competitive algorithm (RICA) is developed to optimize the discrete problem. Extensive numerical experiments and t-test are carried out to verify the effect of this method. The results demonstrate the proficiency of RICA over another imperialist competitive algorithm based method and genetic algorithm in terms of solution quality.</p>

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