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An efficient preference learning method based on ELECTRE TRI model for multi-criteria inventory classification | ||
| Industrial Management Journal | ||
| مقاله 4، دوره 8، شماره 2، مهر 2016، صفحه 191-216 اصل مقاله (508.84 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2016.60655 | ||
| نویسندگان | ||
| Masoud ZarrinSadaf* 1؛ Amir Daneshvar2 | ||
| 1MSc. Student in Industrial Management, Islamic Azad University, Tehran, Iran | ||
| 2Assistant Prof., Islamic Azad University E-Campus, Tehran, Iran | ||
| چکیده | ||
| The multi-criteria ABC analysis is a well known inventory management method for classifying inventory. In the most ABC classification applications, it has been considered fully compensatory approaches, i.e. items have been privilege badly in one or more criteria could be placed in good classes, so it is necessary non-compensatory approach to be noticed. ELECTRE TRI is an outranking relations based model that consider non-compensatory approach, although suffers from the complexity and cost of determining the large number of decision-makers preferences (parameters). In this paper we propose a new method which learns all the decision-makers' preferences from assignment example at the same time using the Particle Swarm Optimization(PSO) algorithm, and will be applied in ABC classification. Against the data mining standard techniques that classify items in nominal way, this model has the ability to categorize items into ordinal classes. The evaluation of proposed method on the illustrated inventory datasets shows high quality and competitive results compared with several standard classification models. | ||
| کلیدواژهها | ||
| ABC Analysis؛ ELECTRE TRI؛ Multi-criteria inventory classification؛ Particle Swarm Optimization (PSO)؛ Swarm Algorithms | ||
| مراجع | ||
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