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.

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.

Supplier Selection Problem: A Multi-Objective Model Considering both All-Unit and Incremental Discounts with Multiple-Item

2014 ◽  
Vol 606 ◽  
pp. 271-275
Author(s):  
Ismed Iskandar ◽  
Soroush Avakh Darestani ◽  
S. Ghavami ◽  
Amir Azizi
Keyword(s):  
Supplier Selection ◽  
Mathematical Formulation ◽  
Selection Problem ◽  
Special Importance ◽  
Multi Objective ◽  
Numerical Example ◽  
Multiple Item ◽  
Objective Model ◽  
Supplier Selection Problem ◽  
Single Objective

In supply chain management, supplier selection has a special importance. In this paper, a multi-objective model is developed based on decisions on quality, service level and cost of purchased goods. The difference of this research is to consider discount parameter into the model. A numerical example for three proposed suppliers is interpreted. The model has been solved in two steps: 1-single-objective, 2-multi-objective approach. According to Lpmetric solution, results can predict optimum selection of suppliers as well as the purchased goods amount. The results show that the single objective problem has better result than multi-objective function. This paper is organized by six sections: in next section, some previous studies and researches on supplier selection problem considering discount and non-considering discount have been discussed. In section 3, mathematical formulation of the supplier selection model considering all-unit and incremental with multiple-item is presented. In section 4, aLP metrics solution is dedicated. In section 5, a numerical example is given and the results are presented. Finally in section 6, conclusions of this research are discussed.

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.

A multi-objective optimization model for sustainable supply chain network with using genetic algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian
Keyword(s):  
Supply Chain ◽  
Performance Indicators ◽  
Supplier Selection ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Sustainability Performance ◽  
Multi Objective ◽  
Sustainable Supplier Selection

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.

Cognitive biases in MCDM methods: an embedded filter proposal through sustainable supplier selection problem

2020 ◽  
Vol 33 (5) ◽  
pp. 947-963
Author(s):  
Nurcan Deniz
Keyword(s):  
Loss Aversion ◽  
Supplier Selection ◽  
Cognitive Biases ◽  
Status Quo ◽  
The Other ◽  
Selection Problem ◽  
Content Type ◽  
Sustainable Supplier Selection ◽  
Comparison Of The Results ◽  
Supplier Selection Problem

PurposeExpert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this evaluation. The mainstream research focus on the ambiguity in this process and use fuzzy logic. On the other hand, cognitive biases are the other but scarcely studied challenges to make accurate decisions. The purpose of this paper is to propose pilot filters – as a debiasing strategy – embedded in the MCDM techniques to reduce the effects of framing effect, loss aversion and status quo-type cognitive biases. The applicability of the proposed methodology is shown with analytic hierarchy process-based Technique for Order-Preference by Similarity to Ideal Solution method through a sustainable supplier selection problem.Design/methodology/approachThe first filter's aim is to reduce framing bias with restructuring the questions. To manipulate the weights of criteria according to the degree of expected status quo and loss aversion biases is the second filter's aim. The second filter is implemented to a sustainable supplier selection problem.FindingsThe comparison of the results of biased and debiased ranking indicates that the best and worst suppliers did not change, but the ranking of suppliers changed. As a result, it is shown that, to obtain more accurate results, employing debiasing strategies is beneficial.Originality/valueTo the best of the author's knowledge, this approach is a novel way to cope with the cognitive biases. Applying this methodology easily to other MCDM techniques will help the decision makers to take more accurate decisions.

scholarly journals The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Selection Problem ◽  
Programming Approach ◽  
Vendor Selection ◽  
Chain Management ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

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