A hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement

Wang, Jufeng; Liu, Chunfeng; Li, Kai

doi:10.1080/00051144.2019.1603264

Cited by 12 publications

(4 citation statements)

References 26 publications

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“…Liu and Wang [27] studied an integrated problem of cell formation and task scheduling considering multi-functional resource and part movement using hybrid simulated annealing. Wang et al [45] further investigated worker movement for this kind of problem. Kamalakannan and Pandian [17] identified machine cells and part family to establish production cells for reducing cell load changes.…”

Section: 1mentioning

confidence: 99%

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

Liu

Wang

2023

JIMO

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<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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Section: 1mentioning

confidence: 99%

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

Liu

Wang

2023

JIMO

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“…Wang J proposed TLBO to solve the flexible job shop scheduling problem with fuzzy processing time. In order to solve the fuzzy flexible job shop scheduling problem, Liu C proposed a hybrid genetic tabu search algorithm [15]. Gao Kaizhou used an improved artificial population algorithm to solve the flexible job shop scheduling problem with fuzzy processing time.…”

Section: Related Workmentioning

confidence: 99%

Super Heuristic Genetic Algorithm for Fuzzy Flexible Job Shop Scheduling

2022

IJMC

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The purpose of this paper is to propose a hybrid super heuristic genetic algorithm for solving a class of fuzzy flexible job shop scheduling problems of work pieces processing time represented by using triangular fuzzy numbers, to minimize the optimization goal and reduce the fuzzy completion time. At the same time, under the conditions of product customization trend, diversified development of process routes, provide enterprises with a small-scale customized production that can be realized in time and a solution to improve the flexible operation of production systems .This paper first considers the practical problems in the production process of fuzzy flexible job shop and establishes a multi-objective optimization model. Then carried out a lot of research and analysis on traditional genetic algorithm, finding that the standard genetic algorithm is easy to fall into the problems of local optimum, low search efficiency and infeasible solution when solving the problem of shop scheduling. Came up with the hybrid heuristic algorithm for this problem, the algorithm incorporates methods such as hybrid heuristics, making the generated initial population as much as possible in the solution space of the whole problem, and to ensure the diversity of solution. Finally, through a series of improvements to the traditional genetic algorithm, improve the way of coding and genetic operators based on the super heuristic genetic algorithm, combine elite retention strategies and niche technologies to further optimize the convergence and diversity of algorithms. Calculates the fitness of the chromosome by weight coefficient change method. Therefore, the results of experimental analysis show that the proposed algorithm can verify the effectiveness of the proposed sorting criterion and super heuristic genetic algorithm, and can play a good role in the actual production process, it can also fully reflect the target requirements of fuzzy flexible job shop scheduling in production.

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“…Genetic Algorithm (GA) and Simulated Annealing (SA) have been proven to be effective algorithms, and are often used to act as comparison benchmark [49,50,51,52,53].…”

Section: Genetic Algorithm and Simulated Annealingmentioning

confidence: 99%

Optimization of product line considering compatibility and reliabilityviadiscrete imperialist competitive algorithm

2021

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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 hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement

Cited by 12 publications

References 26 publications

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

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

Super Heuristic Genetic Algorithm for Fuzzy Flexible Job Shop Scheduling

Optimization of product line considering compatibility and reliabilityviadiscrete imperialist competitive algorithm

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