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Product design-time optimization using a hybrid meta-heuristic algorithm
Computers & Industrial Engineering ( IF 6.7 ) Pub Date : 2021-02-11 , DOI: 10.1016/j.cie.2021.107177
Ming Zhao , Mahdi Ghasvari

Production management is a function including a process of planning, directing, controlling, and organizing ongoing activities to convert inputs into the product. Industrial production management systems allow users to manage all aspects of mass processing in a centralized and decentralized environment. They focus on the overall process of production and distribution of goods and services. The purpose of this paper is to continuously improve the flow of materials so that the quality of the product and the final services are increased, and at the same time, the cost for the consumer is reduced. Since a crucial step in the process of managing the production is the product design phase, therefore, there are always many efforts to optimize and reduce product design time. In this paper, a new algorithm for scheduling design tasks has been suggested to minimize design time in production management systems using a hybrid algorithm. Considering that the scheduling of design tasks and allocating them to engineers concerning prioritizing tasks, skill levels, and preferences of designers is an NP-hard issue, many evolutionary and meta-heuristic approaches to solve this problem have been proposed. Therefore, the offered technique in this paper utilizes a Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for task allocation to designers. The proposed method is simulated via a MATLAB programming tool. The results of the experiments on a set of real-world data and random data indicate that the method improves the time of product design. Considering the different design processes for different kinds of products to improve the performance of designers is not done in this research.



中文翻译:

使用混合元启发式算法的产品设计时优化

生产管理是一项功能,包括计划,指导,控制和组织进行中的活动以将输入转换为产品的过程。工业生产管理系统允许用户在集中和分散的环境中管理大规模处理的各个方面。他们着重于产品和服务的生产和分配的整个过程。本文的目的是不断改善物料流向,从而提高产品质量和最终服务,同时降低消费者的成本。由于在生产管理过程中的关键步骤是产品设计阶段,因此,总会有很多努力来优化和减少产品设计时间。在本文中,已经提出了一种用于调度设计任务的新算法,以使用混合算法来最小化生产管理系统中的设计时间。考虑到设计任务的调度并将其分配给工程师以优先考虑任务的优先级,技能水平和设计师的偏好是一个NP难题,因此提出了许多进化和元启发式方法来解决此问题。因此,本文提供的技术利用遗传算法(GA)和粒子群优化(PSO)将任务分配给设计人员。通过MATLAB编程工具对提出的方法进行了仿真。对一组实际数据和随机数据进行的实验结果表明,该方法可以缩短产品设计时间。

更新日期:2021-02-19
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