scholarly journals A Fuzzy Multiobjective Model for Supplier Selection under Considering Stochastic Demand in a Supply Chain

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Pan ◽  
Fengxia Wang ◽  
Ying Guo ◽  
Shan Liu
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Market Competition ◽  
Stochastic Demand ◽  
Multiple Objective ◽  
Competitive Advantages ◽  
Real Situation ◽  
Purchase Management ◽  
Proposed Model ◽  
Vital Effect

With the development of market competition, company faces more and more pressures. Meanwhile, procurement has a vital effect on achieving competitive advantages in a supply chain. Selecting the appropriate suppliers is one of the most important sections in purchase management. However, in real situation, supplier selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about supplier selection is relatively scarce under considering multiple items, discount price, and fuzzy and stochastic information. In our paper, we develop a fuzzy multiobjective supplier selection model for overcoming uncertainty and multiple items. Stochastic demand, fuzzy objectives, and weights are simultaneously applied to help the managers to select the suitable suppliers about different items. For illustration purpose, a numerical example is presented to verify the effectiveness of the proposed model.

A multi-objective supplier selection model for green supply chain network under uncertainty

2018 ◽  
Vol 13 (3) ◽  
pp. 605-625 ◽  
Author(s):  
Mohammad Khalilzadeh ◽  
Hadis Derikvand
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Objective Function Value ◽  
Selection Problem ◽  
Green Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Objective Model ◽  
Supplier Selection Problem

Purpose Globalization of markets and pace of technological change have caused the growing importance of paying attention to supplier selection problem. Therefore, this study aims to choose the best suppliers by providing a mathematical model for the supplier selection problem considering the green factors and stochastic parameters. This paper aims to propose a multi-objective model to identify optimal suppliers for a green supply chain network under uncertainty. Design/methodology/approach The objective of this model is to select suppliers considering total cost, total quality parts and total greenhouse gas emissions. Also, uncertainty is tackled by stochastic programming, and the multi-objective model is solved as a single-objective model by the LP-metric method. Findings Twelve numerical examples are provided, and a sensitivity analysis is conducted to demonstrate the effectiveness of the developed mathematical model. Results indicate that with increasing market numbers and final product numbers, the total objective function value and run time increase. In case that decision-makers are willing to deal with uncertainty with higher reliability, they should consider whole environmental conditions as input parameters. Therefore, when the number of scenarios increases, the total objective function value increases. Besides, the trade-off between cost function and other objective functions is studied. Also, the benefit of the stochastic programming approach is proved. To show the applicability of the proposed model, different modes are defined and compared with the proposed model, and the results demonstrate that the increasing use of recyclable parts and application of the recycling strategy yield more economic savings and less costs. Originality/value This paper aims to present a more comprehensive model based on real-world conditions for the supplier selection problem in green supply chain under uncertainty. In addition to economic issue, environmental issue is considered from different aspects such as selecting the environment-friendly suppliers, purchasing from them and taking the probability of defective finished products and goods from suppliers into account.

AHP Approach for Supplier Selection in a Polyamide Fiber Plant in Supply Chain Management

2011 ◽  
Vol 299-300 ◽  
pp. 1252-1255
Author(s):  
Hui Jin ◽  
Chun Ling Liu ◽  
Xing Yu Wang
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Supplier Evaluation ◽  
Proposed Model ◽  
Polyamide Fiber ◽  
Fiber Plant ◽  
And Performance ◽  
Supplier Selection Problem

Supplier evaluation and selection is one of the most important components of supply chain, which influence the long term commitments and performance of the plant. Supplier selection is a complex multi-criteria problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is essential to make a trade off between these tangible and intangible factors some of which may conflict. In this paper, an AHP-based supplier selection model is formulated and then applied to a real case study for a polyamide fiber plant in China. The use of the proposed model indicates that it can be applied to improve and assist decision making to resolve the supplier selection problem in choosing the optimal supplier combination.

Efficiency Evaluation of Supply Chain Network Using a Framework Based on DEA and Seller-Buyer Structure

2020 ◽  
Vol 37 (06) ◽  
pp. 2050029 ◽  
Author(s):  
Hassan Arabshahi ◽  
Hamed Fazlollahtabar ◽  
Leila Maboudi
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Selection Procedure ◽  
Point Of View ◽  
Decision Makers ◽  
Efficiency Evaluation ◽  
Supply Chain Network ◽  
Stage Model ◽  
Proposed Model ◽  
Efficient Portfolios

This paper aims to develop a DEA-based framework to evaluate the efficiency of the supply chain based on the seller–buyer structure and with respect to win–win strategy. This is a bi-stage model employing the CCR model in the forms of input-oriented and output-oriented considering the intermediate measures for two different conditions under a centralized point of view. The obtained results from the extension of this model to supply chain network lead to introduce “efficient path” concept being a path including different components of the supply chain that are efficient in terms of DEA. Other kinds of proper information provided by the proposed model can help the managers and decision-makers of the supply chain field in supplier selection procedure and making efficient portfolios and collaborations across the supply chain network.

scholarly journals The effects of different kinds of returns on an integrated chance-constrained stochastic mobile phone closed-loop supply chain configuration and supplier selection

2021 ◽  
Author(s):  
Shahrzad Ahmadi Kermanshah
Keyword(s):  
Supply Chain ◽  
Mobile Phone ◽  
Supplier Selection ◽  
Closed Loop ◽  
Stochastic Demand ◽  
Mixed Integer ◽  
Chance Constraint ◽  
Distance Method ◽  
Closed Loop Supply Chain ◽  
Multi Objective

One of the important concerns in the world is E-waste. Ending up e-waste in the landfill and inappropriate disposing of it are hazardous to the environment. The goal of this research is to design and optimize a multi-period, multi-product, multi-echelon, and multi-customer Closed-Loop Supply Chain (CLSC) network for a mobile phone network considering different types of product returns. Commercial, end of life, and end-of-use returns are well-known in practice. In this research, a multi-objective mixed-integer linear programming formulation with stochastic demand and return is proposed to maximize the total profit in the mobile phone CLSC network, alongside maximizing the weights of eligible suppliers which are estimated based on a fuzzy method for efficient supplier selection and order allocation. Chance-constraint programming is applied in order to deal with the stochastic demand and return. Moreover, distance method and εε-constraint technique are employed to solve the proposed multi-objective problem. The application of the proposed mathematical model is illustrated in Toronto, Canada using real maps.

scholarly journals Fuzzy Model for Assessing the Scope of Work of Railway Passanger Transport Undertaking

2018 ◽  
Vol 3 (1-2) ◽  
Author(s):  
Aleksandar Blagojević ◽  
Iskra Stojanova ◽  
Marko Subotić ◽  
Veljko Radičević
Keyword(s):  
Competitive Ability ◽  
Market Competition ◽  
Fuzzy Model ◽  
Competitive Advantages ◽  
Quality And Safety ◽  
Optimal Solutions ◽  
Passenger Transport ◽  
Proposed Model ◽  
Financial Quality ◽  
Better Than

The main objective of the European policy of rail transport is the development of a single railway area. The opening of the railway sector to market competition impose that railway undertakings behave like any other modern enterprises in other markets and in other industries. It means, they must constantly develop and maintain competitive advantages, and be better than others. In today’s very intense competition conditions, this is the most difficult to achieve. The railway undertakings are challenged to find optimal solutions to operate efficiently and effectively, in order not only to survive on the transport market, but also to develop and maintain a competitive advantage. The paper developed innovative model for the evaluation of efficiency of railway operators for passenger transport assessing the scope of work of railway undertakings that can greatly help to increase the competitive ability of railway undertakings in the single railway market. The developed models allow the integration of indicator groups (resources, operational, financial, quality and safety indicators) into a single assessment of the scope of work of railway undertakings and also allow the provision of information about the corrective actions that can improve the scope of work of the railway undertaking. The proposed model has been tested on actual examples, e.g. railway undertaking Railways of Republic of Srpska. The analysis of the results shows exceptional suitability for use of developed approach for assessing the scope of work of railway undertakings.

Supplier selection considering sustainability measures: an application of weight restriction fuzzy-DEA approach

2018 ◽  
Vol 52 (3) ◽  
pp. 981-1001 ◽  
Author(s):  
Atefeh Amindoust
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Social Issues ◽  
Selection Process ◽  
Essential Element ◽  
Dea Model ◽  
Weight Restriction ◽  
Proposed Model ◽  
Automotive Parts ◽  
Fuzzy Dea

With the growing of consumer awareness in environmental and social issues sustainable development has become an essential element in supply chain management. Supplier evaluation and selection is one of the main strategic decisions for purchasing management in supply chain. This paper use Data Envelopment Analysis (DEA) to propose a new model for evaluation and ranking of a given set of suppliers from sustainable point of view. The proposed model integrates the fuzzy set theory and DEA to consider the decision makers’ preferences and handle the ambiguity and uncertainty in supplier selection process. For this purpose, linguistic values in the form of triangular fuzzy numbers are used to assess the weights of criteria, sub-criteria, and the ratings of suppliers’ performance with respect to sub-criteria. Then, a fuzzy-DEA model, using α-cut approach, is developed considering weight constraints. An application from Supplying Automotive Parts Company (SAPCO) Company, which is one of the largest suppliers of automotive parts in the Middle-East, is presented to show the applicability of the proposed model. Finally, the proposed weight restriction fuzzy-DEA model is validated through comparing with one of the recent supplier selection methods.

scholarly journals Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

2017 ◽  
Vol 10 (2) ◽  
pp. 188 ◽  
Author(s):  
Muhammad Hashim ◽  
Muhammad Nazam ◽  
Liming Yao ◽  
Sajjad Ahmad Baig ◽  
Muhammad Abrar ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Supplier Selection ◽  
Decision Makers ◽  
Quality Level ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Textile Sector

Purpose:  The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem.Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value mesurement (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis.Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability.Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world problems. A detailed comparative analysis by using other algorithms is necessary for solving similar problems of agriculture, pharmaceutical, chemicals and services sectors in future.Practical implications: It can help the decision makers for ordering to different supplier for managing supply chain performance in efficient and effective manner. From the procurement and engineering perspectives, minimizing cost, sustaining the quality level and meeting production time line is the main consideration for selecting the supplier. Empirically, this can facilitate engineers to reduce production costs and at the same time improve the product quality.Originality/value: In this paper, we developed a novel multi-objective programming model based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy environment. The algorithm was tested and applied to solve a real case of textile sector in Pakistan. The experimental results and comparative sensitivity analysis illustrate the effectiveness of our proposed model.

The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage

2020 ◽  
Vol 15 (3) ◽  
pp. 705-725
Author(s):  
Mohammad Khalilzadeh ◽  
Arya Karami ◽  
Alborz Hajikhani
Keyword(s):  
Supply Chain ◽  
Combinatorial Optimization ◽  
Supplier Selection ◽  
Multiple Objectives ◽  
Selection Problem ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Supplier Selection Problem ◽  
Fuzzy Parameters

Purpose This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based partial and general coverage of suppliers makes the number of orders of products more realistic. In this model, the weights of suppliers are determined by fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, as a multi-criteria decision analysis method, in the objective function. Also, the authors consider the parameters related to delays as triangular fuzzy numbers. Findings A small-sized numerical example is provided to clearly show the proposed model. The exact epsilon constraint method is used to solve this given multi-objective combinatorial optimization problem. Subsequently, the sensitivity analysis is conducted to testify the proposed model. The obtained results demonstrate the validity of the proposed multiple objectives mixed integer mathematical programming model and the efficiency of the solution approach. Originality/value In real-life situations, supplier selection parameters are uncertain and incomplete. Hence, the fuzzy set theory is used to tackle uncertainty. In this paper, a multi-objective supplier selection problem is formulated taking into consideration the coverage of suppliers and suppliers’ weights. Integrating coverage of suppliers to select and allocate the order to them can be mentioned as the main contribution of this study. The proposed model considers the delay from suppliers as fuzzy parameters.

scholarly journals The effects of different kinds of returns on an integrated chance-constrained stochastic mobile phone closed-loop supply chain configuration and supplier selection

2021 ◽  
Author(s):  
Shahrzad Ahmadi Kermanshah
Keyword(s):  
Supply Chain ◽  
Mobile Phone ◽  
Supplier Selection ◽  
Closed Loop ◽  
Stochastic Demand ◽  
Mixed Integer ◽  
Chance Constraint ◽  
Distance Method ◽  
Closed Loop Supply Chain ◽  
Multi Objective

One of the important concerns in the world is E-waste. Ending up e-waste in the landfill and inappropriate disposing of it are hazardous to the environment. The goal of this research is to design and optimize a multi-period, multi-product, multi-echelon, and multi-customer Closed-Loop Supply Chain (CLSC) network for a mobile phone network considering different types of product returns. Commercial, end of life, and end-of-use returns are well-known in practice. In this research, a multi-objective mixed-integer linear programming formulation with stochastic demand and return is proposed to maximize the total profit in the mobile phone CLSC network, alongside maximizing the weights of eligible suppliers which are estimated based on a fuzzy method for efficient supplier selection and order allocation. Chance-constraint programming is applied in order to deal with the stochastic demand and return. Moreover, distance method and εε-constraint technique are employed to solve the proposed multi-objective problem. The application of the proposed mathematical model is illustrated in Toronto, Canada using real maps.

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