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Showing 14 results for Supplier Selection

A. Amid, S.h. Ghodsypour,
Volume 19, Issue 4 (12-2008)
Abstract

  Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. Supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision making complicated. Simultaneously, in this model, vagueness of input data and varying importance of criteria are considered. In real cases, where Decision- Makers (DMs) face up to uncertain data and situations, the proposed model can help DMs to find out the appropriate ordering from each supplier, and allows purchasing manager(s) to manage supply chain performance on cost, quality, on time delivery, etc. An additive weighted model is presented for fuzzy multi objective supplier selection problem with fuzzy weights. The model is explained by an illustrative example.


F. Bagheri , M. J. Tarokh,
Volume 21, Issue 1 (6-2010)
Abstract

Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes the decision-maker to be able to solve this problem with different criteria and different weight for each criterion with respect to the purchasing strategy. Finally, the proposed model is illustrated by an example.
Mohammad Najafi Nobar, Mostafa Setak,
Volume 21, Issue 1 (6-2010)
Abstract

In nowadays world competitive market, on account of the development of electronic media and its influence on shortening distances, companies require some core competencies in order to be able to compete with numerous competitors in industry and sustain their situation in such a market. In addition companies achieve this target are those which their processes perform great and exploit from competitive price, quality, guarantee, etc. Since some parameters such as price and quality are so dependent on the performance of company supply chain management, so the results can highly impress the final price and quality of products. One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article two layers of suppliers have been considered as a chain of suppliers. First layer suppliers are evaluated by two groups of criteria which the first one encompasses criteria belongs to first layer suppliers features and the second group contains criteria belong to the characteristics of second layer suppliers. One of the criteria is the performance of second layer suppliers against environmental issues. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second layer suppliers features as a criteria for selecting the best supplier.
Behin Elahi, Seyed Mohammad Seyed-Hosseini, Ahmad Makui,
Volume 22, Issue 2 (6-2011)
Abstract

 

  Supplier selection,

  Multi-objective decision making,

  Fuzzy Compromise programming,

  Supply chain management,

  Quantity discount .

 

Supplier selection is naturally a complex multi-objective problem including both quantitative and qualitative factors. This paper deals with this issue from a new view point. A quantity discount situation, which plays a role of motivator for buyer, is considered. Moreover, in order to find a reasonable compromise solution for this problem, at first a multi-objective modeling is presented. Then a proposed fuzzy compromise programming is utilized to determine marginal utility function for each criterion. Also, group decision makers’ preferences have taken into account and the weight of each criterion has been measured by forming pair-wise comparison matrixes. Finally the proposed approach is conducted for a numerical example and its efficacy and efficiency are verified via this section. The results indicate that the proposed method expedites the generation of compromise solution .


Iman Nosoohi, Naser Mollaverdi,
Volume 22, Issue 2 (6-2011)
Abstract

 

  Capacity Reservation,

  Option Contract,

  Supplier Selection

A key issue for manufacturing firms is planning for outsourced components. In this research, we have considered a manufacturer in a Make-to-Order production environment who has to outsource a special component from a set of suppliers. One selling season is considered and the manufacturer faces uncertain demand during the selling season. A good strategy for the manufacturer to balance both holding and lost sale costs is to initiate capacity reservation contracts with his suppliers. Thus, unlike the previous researches we have presented a mathematical model based on option mechanism that will help the manufacturer to select appropriate suppliers and order allocation, simultaneously. The considered option mechanism has a two part contract fee structure (option price and exercise price) and it is at the foundation of practical contracts used by different industries. A numerical example is used to illustrate the model and to investigate how option mechanism improves manufacturer's expected profit in comparison with the situation without applying the option mechanism .


Mostafa Setak, Samaneh Sharifi,
Volume 22, Issue 4 (12-2011)
Abstract

In recent years, Supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. The Mixed integer multi-Objective non-Linear programming model (MIMONLP) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in addition to selecting the first layer's suppliers which relate directly to the organization, analyses the characteristics of second-layers suppliers, and design a network to determine the flow rate of products and materials between buyers and best suppliers in both layers. Another important feature of this model is considering holding costs of different products over the planning horizon and quantity discounts for the first layer's suppliers at the same time. Finally, the model is solved by using goal programming approach and numerical examples are presented to test the performance of proposed model.


Mostafa Shirinfar, Hassan Haleh,
Volume 22, Issue 4 (12-2011)
Abstract

In this study, an outsourcer evaluation and management system is developed for a manufacturing company by use of Fuzzy goal programming (FGP). A first phase of the methodology evaluation criteria for outsources and the objectives of the company are determined. Considering the fuzziness in the decision data, linguistic variables that can be expressed in generalized fuzzy number are used. The propose approach is utilized from fuzzy sets, Analytic Network Process (ANP), fuzzy TOPSIS and Preference Ranking Organization method for enrichment evaluations (PROMETHEE) approaches. Evaluation criteria for this problem are weighted by Fuzzy ANP approach then in the Fuzzy TOPSIS and Fuzzy PROMETHEE approaches. At the second phase the FGP model developed selects the most appropriate outsourcers suitable to be strategic partners with the company and simultaneously allocates the quantities to be ordered to them. At the end, gives the computational results .


Ali Mohaghar, Mojtaba Kashef, Ehsan Kashef Khanmohammadi,
Volume 25, Issue 2 (5-2014)
Abstract

Considering the major change occurred in business cells from plant to “chain” and the critical need to choose the best partners to form the supply chain for competing in today’s business setting, one of the vital decisions made at the early steps of constructing a business is supplier selection. Given the fact that the early decisions are inherently strategic and therefore hard and costly to change, it’s been a point of consideration for industries to select the right supplier. It’s clear that different criteria must be investigated and interfered in deciding on the best partner(s) among the alternatives. Thereupon the problem might be regarded as a multiple criteria decision making (MCDM) problem. There are a variety of techniques to solve a MCDM problem. In this paper we propose a novel technique by combination of decision making trial and evaluation laboratory and graph theory and matrix approach techniques. Eventually, the results are compared to SAW technique and discussed to come to a conclusion.
Ali Morovati Sharifabadi, Alireza Naser Sadrabadi, Fetemeh Dehghani Bezgabadi, Saeid Peirow,
Volume 27, Issue 2 (6-2016)
Abstract

Efficiency and effectiveness of the organization is result ofmanagement performance and supply chain structure.Today, several factors in selection the supplier or the best combination of suppliers have been identified that this issue would increase the complexity of suplier selecting.This study investigates the application of Fuzzy Delphi in order to identify the important factors in selecting a supplier in the steel industry and then provide a comprehensive and holistic model of supplier selection to overcome the complexity.In this context, Interpretive Structural Modeling (ISM) unlike other methods, the holistic, dealing with supplier selection to prioritize components-surfacing and identifying key components, so industry leaders will provide comperhensive map to select the best combination based on their.The results of this study indicate that "technically possible", "financial health" and "geography situation" are the basic components to the selection of suppliers.


Mohammad Mahdi Paydar, Zahra Hassanzadeh, Ali Tajdin,
Volume 27, Issue 3 (9-2016)
Abstract

Currently, due to increased competition in the services and manufacturing, many companies are trying to lower price and good quality products offer to the market. In this paper, the multi-criteria decision-making techniques to evaluate and select the best supplier from among the existing suppliers. The first, hierarchical structure for selecting suppliers of raw materials used and the analytic hierarchy process to obtain the relative importance of quantitative and qualitative criteria related to green supply chain is applied.  Then, a fuzzy TOPSIS technique any raw material suppliers is ranked according to the relevant criteria. Finally, with regard to the weight of suppliers and demand of raw material and resource constraints by a multi-objective mathematical model, optimum order is determined. The objectives are to minimize the total cost, maximize amount of purchases of desirable suppliers and minimize of raw materials required are not provide. The proposed method in a case study used Food Company and the relevant results are expressed.


Mohammad Mahdi Paydar, Amir Arabsheybani, Abdul Sattar Safaei,
Volume 28, Issue 1 (3-2017)
Abstract

Recently, sustainable supply chain management (SSCM) has become one of the important subjects in the industry and academia. Supplier selection, as a strategic decision, plays a significant role in SSCM. Researchers use different multi-criteria decision making (MCDM) methods to evaluate and select sustainable suppliers. In the previous studies, evaluation is solely based on the desirable features of suppliers and their risks are neglected. Therefore, current research uses failure mode and effects analysis (FMEA) as a risk analysis technique to consider supplier's risk in combination with the MCDM method. Practically, this study operated in two main stages. In the first stage, the score of the suppliers obtains by integration Fuzzy MOORA and FMEA. In the second stage, the output of the previous stage used as input parameters in developed mix-integer linear programming to select suppliers and order optimum quantity. Finally, to demonstrate the effectiveness of the proposed approach, a case study in a chemical industry and sensitivity analysis is presented.  


Mohammad Khalilzadeh, Alborz Hajikhani, Seyed Jafar Sadjadi,
Volume 28, Issue 1 (3-2017)
Abstract

The present paper aims to propose a fuzzy multi-objective model to allocate order to supplier in uncertainty conditions and for multi-period, multi-source, and multi-product problems at two levels with wastages considerations.  The cost including the purchase, transportation, and ordering costs, timely delivering or deference shipment quality or wastages which are amongst major quality aspects, partial coverage of suppliers in respect of distance and finally, suppliers weights which make the products orders more realistic are considered as the measures to evaluate the suppliers in the proposed model. Supplier's weights in the fifth objective function are obtained using fuzzy TOPSIS technique. Coverage and wastes parameters in this model are considered as random triangular fuzzy number. Multi-objective imperial competitive optimization (MOICA) algorithm has been used to solve the model,. To demonstrate applicability of MOICA, we applied non-dominated sorting genetic algorithm (NSGA-II). Taguchi technique is executed to tune the parameters of both algorithms and results are analyzed using quantitative criteria and performing parametric. 


- S. Ali Torabi, - Abtin Boostani,
Volume 29, Issue 1 (3-2018)
Abstract

This paper addresses supplier selection and order allocation problem while considering the losses arising from the risk of sanction in Iran’s Oil & Gas Drilling Industry. In the proposed study, two general classes of items and two different classes of suppliers are considered. AHP is first used to rank the potential suppliers. Then, a multi-objective linear programming model is proposed to determine the best suppliers and their allocated orders. A numerical example is presented to demonstrate the applicability of the proposed model.


Mostafa Ekhtiari, Mostafa Zandieh, Akbar Alem-Tabriz, Masood Rabieh,
Volume 29, Issue 1 (3-2018)
Abstract

Supplier selection is one of the influential decisions for effectiveness of purchasing and manufacturing policies under competitive conditions of the market. Regarding the fact that decision makers (DMs) consider conflicting criteria for selecting suppliers, multiple-criteria programming is a promising approach to solve the problem. This paper develops a nadir compromise programming (NCP) model for decision-making under uncertainty on the selection of suppliers within the framework of binary programming. Depending on the condition of uncertainty, three statuses are taken into consideration and a solution approach is proposed for each status. A pure deterministic NCP model is presented for solving the problem in white condition (certainty of data) and a solution approach resulted from combination of NCP and stochastic programming is introduced to solve the model in black (uncertainty of data) situation. The paper also proposes a NCP model under certainty and uncertainty for solving problem under grey (a combination of certainty and uncertainty of data) conditions. The proposed approaches are illustrated for a real problem in steel industry with multiple objectives. Also, a simulation approach has been designed in order to examine the results obtained and also verifies capabilities of the proposed model.



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