Hybrid Whale-fish swarm algorithm to optimize disassembly line balancing problem

Nadir Siddig, Zhang Ze Qiang, Abdallah Mokhtar, Ahmed Abualnor
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Abstract

The disassembly of waste products positively affects the environment, reduces the risk of environmental pollution, reduces the risk of spreading dangerous parts to the life of living entities, and provides the continuity of life on this planet.This research aims to contribute to the aforementioned of maintaining a clean environment by developing algorithms that help solve the problems of dismantling waste products and polluting the environment. In previous literature, researchers developed algorithms for artificial fish, improved artificial fish, and artificial whales to search for solutions with higher evidence instead From the local evidence, in this paper the artificial fish algorithm has been hybridized with the artificial whale algorithm for the purpose of developing solutions, and this method depends on the artificial fish flock first searching for food and here representing global solutions and avoiding predating traps (hooks with trap food), and after finding a flock The artificial swarm is the real food. The artificial whale sends bubbles to collect the swarm of artificial fish in the place of global high solutions, and gets them at once. The proposed algorithm was compared with the algorithms in the previous literature, and the results were as follows:Workstation was decreased by 0.5\% to 22.2\%, idle time was reduced by 82.5\% to 84.0\%, the demand index was reduced by 15\% to 24.2\%, and the hazardous index was reduced by 1.7\% to 3.4\%.
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混合鲸鱼群算法优化拆解线平衡问题
废品的拆解对环境产生了积极的影响,减少了环境污染的风险,减少了危险部件传播给生物生命的风险,为这个星球上的生命提供了连续性。本研究旨在通过开发有助于解决废品拆解和污染环境问题的算法,为维护清洁环境的上述目标做出贡献。在之前的文献中,研究人员开发了人工鱼、改进人工鱼和人工鲸的算法,以寻找具有更高证据的解,而不是从局部证据出发,本文将人工鱼算法与人工鲸算法杂交,以开发解。这种方法依赖于人工鱼群首先寻找食物,这里代表全局解决方案,避免预先陷阱(陷阱食物的钩子),找到鱼群后,人工鱼群才是真正的食物。人造鲸发出气泡,收集全球高溶液处的人造鱼群,并立即获得它们。将提出的算法与已有文献中的算法进行比较,结果表明:工作站减少0.5%至22.2%,空闲时间减少82.5%至84.0%,需求指数减少15%至24.2%,危险指数减少1.7%至3.4%。
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