A Fuzzy Multi Objective Model for Supplier Selection (original) (raw)
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Fuzzy multi-objective supplier selection problem in a supply chain
2018
The decision making of supplier selection and their allocation is one of the main concerns in supply chain management. In this paper, an attempt has been made to obtain an optimal allocation for supplier based on minimizing the net cost, minimizing the net rejections, and minimizing the net late deliveries subject to realistic constraints regarding buyer’s demand, vendors’ capacity, vendors’ quota flexibility, purchase value of items, budget allocation to individual vendor, etc. We convert the problem into single objective fuzzy goal programming problem by using weighted root power mean the method of aggregation with linear, exponential and hyperbolic membership functions. The comparison has been made by assigning different weights to the objective functions. A numerical illustration is provided for the verification of applicability of the approach.
A New Method for Solving Fully Fuzzy Multi Objective Supplier Selection Problem
International Journal of Research, 2017
Supplier selection is one of the most critical activities of purchasing management in a supply chain. Because selecting right suppliers helps reduce purchasing costs, improve quality of final products and services, etc. In a real situation, for a supplier selection problem, most of the input information is not known precisely, since decision making deal with human judgment and comprehension and its nature includes ambiguity. In fact, on the one hand, deterministic models cannot easily take this vagueness into account. In these cases, the theory of fuzzy sets is one of the best tools to handle uncertainty. On the other hand, Kumar et al. proposed a new approach to find the fuzzy optimal solution of fully fuzzy linear programming problem. So, using this approach in this paper, we present a new mixed integer multi objective linear programming model for supplier selection problem. Due to uncertainty of the data, in continuation, we present a new method to solve multi objective fully fuz...
Fuzzy Multi-Objective Supplier Selection Problem for Multiple Items in a Supply Chain
Today's market is highly competitive. The role of supply chain managers is to select best suppliers because major part of the capital is spent on purchasing raw material/semi finished items. The strategic decision of supply chain is to minimize the expenses on the purchase of items. There are several criteria involved in this problem; such as cost, quality, on-time delivery and long term relationship. Some of the criteria are quantitative in nature and some the criteria are qualitative in nature. Qualitative criteria are expressed in triangular fuzzy numbers. It requires defuzzification; the graded mean integration (GMI) representation method is used. Again all of these criteria are conflicting in nature that's why fuzzy programming is used. For formulating the crisp model, it requires defuzzification; fuzzy compensatory operator is applied. This model gives us the idea about supplier selection as well as order quantity from each selected suppliers. Also, the numerical example is given to illustrate the above methods.
Multi-Objective Vendor Selection Problem of Supply Chain Management Under Fuzzy Environment
Journal of the Operations Research Society of China, 2018
Survival of a company in today's competitive business environment depends mainly on its supply chain. An adequate supply chain gives a competitive edge to a company. Sourcing, which is the initial stage of a supply chain, can be made efficient by making an appropriate selection of vendors. Appropriate vendor selection results not only in reduced purchasing costs, decreased production lead time, increased customer satisfaction but also in improved corporate competitiveness. In general, the vendor selection problem is a multi-objective decision-making problem that involves some quantitative and qualitative factors. So, we have considered a multi-objective vendor selection problem (MOVSP) with three multiple objective goals: minimization of net ordering price, minimization of rejected units and minimization of late delivered units. In most of the cases, information about the price of a unit, percentage of rejected units, percentage of late delivered units, vendor rating value and vendor quota flexibility may not be known precisely due to some reasons. In this paper, imprecision in input information is handled by the concept of a simulation technique, where the parameter follows the uniform distribution. Deterministic, stochastic, α-cut and ranking function approaches are used to get the crisp value of the simulated data sets. The four different algorithms, namely-fuzzy programming, goal programming, lexicographic goal programming and D 1-distance algorithm, have been used for solving the MOVSP. In last, three different types of simulated data sets have been used to illustrate the work.
The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management
Mathematics, 2020
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 illustrate...
Multi-Sourcing Multi-Product Supplier Selection: An Integrated Fuzzy Multi-Objective Linear Model
Proceedings of the 2013 (4th) International Conference on Engineering, Project, and Production Management, 2013
Supplier selection is an important strategic supply chain design decision. It is always exposed to major risks and a number of uncertainties in the decision such as risks of not having sufficient raw materials to meet their fluctuating demand. These risks and uncertainty may be caused by natural disasters to man-made actions. Incorporating the uncertainty of demand and supply capacity into the optimization model results in a robust selection of suppliers. The fuzzy set theories can be employed due the presence of vagueness and imprecision of information. In addition, supplier selection is a Multi-Criteria Decision Making problem (MCDM) in which criteria has different relative importance. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. This study focuses on a fuzzy multi-objective linear model to deal with the problem. The model is capable of incorporating multiple products with multiple suppliers (sourcing). The proposed model can help the Decision Makers (DMs) to find out the appropriate order to each supplier, and allows the purchasing manager(s) to manage the supply chain performance on cost, quality and service. The model is explained by an illustrative example, showing that the proposed approach can handle realistic situation when there is information vagueness related to inputs.
Applied Mathematical Modelling, 2013
The aim of this paper is to solve a supplier selection problem under multi-price level and multi-product using interactive two-phase fuzzy multi-objective linear programming (FMOLP) model. The proposed model attempts to simultaneously minimize total purchasing and ordering costs, a number of defective units, and late delivered units ordered from suppliers. The piecewise linear membership functions are applied to represent the decision maker's fuzzy goals for the supplier selection and order allocation problem, and can be resulted in more flexibility via an interactive decision-making process. To demonstrate effectiveness of the proposed model, results of applying the proposed model are shown by a numerical example. The analytical results show that the proposed approach is effective in uncertain environments and provide a reliable decision tool for integrated multiobjective supplier selection problems.
Discrete Dynamics in Nature and Society
One of the advantages of sustainable competition for manufacturing systems is to make supply chain activities more efficient and effective. One of the major parts of these activities that can save a lot of costs is careful outsourcing. In this study, an approach based on decision-making policies in order to select suppliers and allocate order volume to them is introduced. The main contribution of this research is a comprehensive approach for optimizing both supplier evaluation and order allocation. In this regard, first, based on the evaluation, 39 key indicators were identified to evaluate the suppliers, and based on the content analysis, 25 key indicators were screened based on the Lavache method. Next, based on the fuzzy Delphi method, 11 indicators were selected from among the 25 key effective indicators. Finally, the Best-Worst Method (BWM) and a robust multi-objective formulation are proposed to find the weight of the effective criteria and the optimal order allocation to supp...
International Journal of Services and Operations Management, 2015
This paper studies a multi-objective supplier selection and order allocation problem with fuzzy objectives. The problem is formulated as a linear programming model, and three interactive and non-interactive approaches are suggested for solving the problem, namely interactive fuzzy multi-objective linear programming (i-FMOLP), interactive fuzzy goal programming (IFGP) and a standard fuzzy programming approach. The objective of the paper is to efficiently obtain solutions that are close to the aspiration levels and the decision maker's satisfaction degree. The performance of the suggested approaches and the weighted max-min approach of an earlier study are evaluated by using a set of metric distance functions. The results obtained illustrate that the solutions of the approaches applied in this paper are closer to the ideal solution as compared to the compromise solution of the weighted max-min method used in an earlier study. 436 N. Kazemi et al.
A weighted additive fuzzy programming approach for multi-criteria supplier selection
Expert Systems with Applications, 2011
In supply chain management, to build strategic and strong relationships, firms should select best suppliers by applying appropriate method and selection criteria. In this paper, to handle ambiguity and fuzziness in supplier selection problem effectively, a new weighted additive fuzzy programming approach is developed. Firstly, linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the factors. By applying the distances of each factor between Fuzzy Positive Ideal Rating and Fuzzy Negative Ideal Rating, weights are obtained. Then applying suppliers' constraints, goals and weights of the factors, a fuzzy multi-objective linear model is developed to overcome the selection problem and assign optimum order quantities to each supplier. The proposed model is explained by a numerical example.