Multi-objective simulation optimization for selection and determination of order quantity in supplier selection problem under uncertainty and quality criteria

2015 ◽  
Vol 93 (1-4) ◽  
pp. 161-173 ◽  
Author(s):  
Elham Shadkam ◽  
Mehdi Bijari
Keyword(s):  
Supplier Selection ◽  
Simulation Optimization ◽  
Quality Criteria ◽  
Selection Problem ◽  
Order Quantity ◽  
Multi Objective ◽  
Supplier Selection Problem

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.

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.

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.

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