ctrlnum 3888621
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Seifbarghy, Mehdi</creator><creator>Esfandiari, Nima</creator><date>2011-07-08</date><description>Suppliers' evaluation is a subject, which has attracted the attention of many researchers. The performance of potential suppliers is evaluated against multiple criteria rather than considering a single factor such as cost or quality. One of the major objectives of suppliers' evaluation is to determine the optimal quota assigned to each supplier while needing to replenish an order. This problem has been studied by many researchers as a multi-objective problem. The usual objectives are minimizing the purchasing cost, rejected units, and late delivered units. However, in a few researches maximizing the evaluation scores of the selected suppliers is considered as fourth objective. In this paper, we present a model with five objectives including minimizing the transaction costs of purchasing from suppliers as well as the four addressed objectives. We convert the model to a single objective one using the well-known weighting method, solve it utilizing two meta-heuristic algorithms, and analyze the efficiency of the heuristics. The reason why we utilize the meta-heuristic algorithms is that the problem is proved to be an NP-hard one</description><identifier>https://zenodo.org/record/3888621</identifier><identifier>10.1007/s10845-011-0555-z</identifier><identifier>oai:zenodo.org:3888621</identifier><language>eng</language><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/2.0/legalcode</rights><source>Journal of Intelligent Manufacturing 24(1) 201-209</source><subject>Supplier selection, Quota allocation, Transaction costs, Multi-objective, Meta-heuristic algorithms.</subject><subject>Closed-loop supply chain network design, Competitive location, Contract design, Facility disruptions, Fuzzy logic, Genetic Algorithm, Heuristic algorithm, Location-allocation problem, Lost sales, Maximal covering location problem, Multi-echelon, NSGA-II, Quota allocation, SCOR, Social responsibility, Supplier selection, Supply chain management, Sustainable supply chain network design, Tabu search, Vendor Managed Inventory</subject><title>Modeling and solving a multi-objective supplier quota allocation problem considering transaction costs</title><type>Journal:Article</type><type>Journal:Article</type><recordID>3888621</recordID></dc>
language eng
format Journal:Article
Journal
author Seifbarghy, Mehdi
Esfandiari, Nima
title Modeling and solving a multi-objective supplier quota allocation problem considering transaction costs
publishDate 2011
isbn 108450110555
topic Supplier selection
Quota allocation
Transaction costs
Multi-objective
Meta-heuristic algorithms
Closed-loop supply chain network design
Competitive location
Contract design
Facility disruptions
Fuzzy logic
Genetic Algorithm
Heuristic algorithm
Location-allocation problem
Lost sales
Maximal covering location problem
Multi-echelon
NSGA-II
SCOR
Social responsibility
Supply chain management
Sustainable supply chain network design
Tabu search
Vendor Managed Inventory
url https://zenodo.org/record/3888621
contents Suppliers' evaluation is a subject, which has attracted the attention of many researchers. The performance of potential suppliers is evaluated against multiple criteria rather than considering a single factor such as cost or quality. One of the major objectives of suppliers' evaluation is to determine the optimal quota assigned to each supplier while needing to replenish an order. This problem has been studied by many researchers as a multi-objective problem. The usual objectives are minimizing the purchasing cost, rejected units, and late delivered units. However, in a few researches maximizing the evaluation scores of the selected suppliers is considered as fourth objective. In this paper, we present a model with five objectives including minimizing the transaction costs of purchasing from suppliers as well as the four addressed objectives. We convert the model to a single objective one using the well-known weighting method, solve it utilizing two meta-heuristic algorithms, and analyze the efficiency of the heuristics. The reason why we utilize the meta-heuristic algorithms is that the problem is proved to be an NP-hard one
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