نوع مقاله : مقاله پژوهشی
نویسندگان
1 عضو هیات علمی دانشگاه ولی عصر رفسنجان
2 دانشجوی کارشناسی ارشد مدیریت بازرگانی دانشگاه ایلام
3 دانشجوی کارشناسی ارشد مدیریت صنعتی دانشگاه ولی عصر رفسنجان
چکیده
طبق هبندى موجودى یکى از تکنی کهاى مهم در حوز هى مدیریت موجودى است. ب هدلیل تنوع و
حجم بالاى اقلام موجودى در یک شرکت، مدیران ناگزیر هستند آنها را طبق هبندى کنند. بنابراین،
بخشى از تلاش پژوهشگران ب همنظور یافتن رو شهایى بوده است که با تعیین تعداد طبقات موجودى،
توان کنترل مدیریت را افزایش دهند. در این مقاله، از الگوریتم بهین هسازى جمعى را هح لهاى چن دهدفه
در سال 2008 ارائه شده است. 4 « سو ویى » و « چى یانگ » استفاده م ىشود. این الگوریتم از سوى
الگوریتم بهین هسازى جمعى را هح لهاى چن دهدفه نوعى الگوریتم تکاملى است که چن دهدف هبودن تابع
آن، به مدیریت این امکان را م ىدهد تا ه مزمان ب هدنبال بهین هسازى اهداف متعددى باشد. حداق لکردن
هزین ههاى نگهدارى و سفار شدهى و حداکث رکردن نرخ گردش موجودى در این مدل مد نظر هستند.
1تایى مورد آزمون قرار دادیم. نتایج پس از نوشتن برنام هى نر مافزارى مدل، آن را روى یک نمون هى 00
نشان م ىدهد که این الگوریتم، م ىتواند هزین ههاى نگهدارى و سفار شدهى را ب هطور قابل ملاحظ هاى
کاهش داده و نرخ گردش موجودى را افزایش دهد.
کلیدواژه‌ها
عنوان مقاله [English]
Inventory classification by multiple objective particles swarm optimization
نویسندگان [English]
- Mansour Esmaeilzadeh 1
- Amin Hoseinpoor 2
- Mohammad Reza Namdar 3
1 Department of Industrial Management, Faculty of Management and Economics Vali-e- Asr University of Rafsanjan
2 Master student Department of Business Administration, Ilam University
3 Bachelor student Department of Industrial Management, Faculty of Management and Economics Vali-e-Asr University of Rafsanjan
چکیده [English]
Inventory classification is one of important techniques in inventory control
context. Managers have to classify inventories because of their variety and
high volume. So a stream of research has been to attempt to find methods
that increase the management control by determining the number of inventory
classes. In this paper the multiple objective particle swarm optimization
algorithm has been used. This algorithm has been presented by Chi-Yang Tsai
and Szu-Wei Yeh in 2008. Multiple objective particle swarm optimization algorithm
is an evolutionary algorithm that enables the management to optimize
multiple objectives simultaneously. Minimizing costs of inventory holding
and ordering and maximizing inventory turnover ratios are this model’s objectives.
We write the software program of this model and then test it on a sample
of 100 items. Results show that this algorithm can decrease costs of holding &
ordering and also increase the inventory turnover ratios significantly.
کلیدواژه‌ها [English]
- Multi Objective Optimization Problems
- Multi Objective Particle Swarm Optimization Algorithm
- Inventory Classification
.149-133 1387 57
ABC [2]
.22- 1 1388 17
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