دانلود مقاله ISI انگلیسی شماره 78974
ترجمه فارسی عنوان مقاله

استفاده از الگوریتم خوشه بندی مبتنی بر الگوریتمهای فراابتکاری به انتساب آیتم را در یک سیستم چیدن سفارش منطقه هماهنگ شده

عنوان انگلیسی
Application of metaheuristics-based clustering algorithm to item assignment in a synchronized zone order picking system
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78974 2016 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 46, September 2016, Pages 143–150

ترجمه کلمات کلیدی
آنالیز خوشه ای؛ انتساب ذخیره سازی - انبارداری؛ بهینه سازی ازدحام ذرات؛ الگوریتم ژنتیک
کلمات کلیدی انگلیسی
Cluster analysis; Storage assignment; Warehousing; Particle swarm optimization; Genetic algorithm
پیش نمایش مقاله
پیش نمایش مقاله  استفاده از الگوریتم خوشه بندی مبتنی بر الگوریتمهای فراابتکاری به انتساب آیتم را در یک سیستم چیدن سفارش منطقه هماهنگ شده

چکیده انگلیسی

Warehousing management policy is a crucial issue in logistic management. It must be managed effectively and efficiently to reduce the production cost as well as the customer satisfaction. Synchronized zoning system is a warehousing management policy which aims to increase the warehouse utilization and customer satisfaction by reducing the customer waiting time. This policy divides a warehouse into several zones where each zone has its own picker who can work simultaneously. Herein, item assignment plays an important role since it influences the order processing performance. This study proposes an application of metaheuristic algorithms, namely particle swarm optimization (PSO) and genetic algorithm (GA), for item assignment in synchronized zoning system. The original PSO and GA algorithms are modified so that it is suitable for solving item assignment problem. The datasets with different sizes are used for method validation. Results obtained by PSO and GA are then compared with the result of an existing algorithm. The experimental results showed that PSO and GA can perform better than the existing algorithm. These results also show that PSO has better performance than GA, especially for bigger problems. It proves that item assignment policy obtained by PSO and GA has higher utilization rates than the existing algorithm.