Multi-objective supplier selection and order allocation under quantity discounts with fuzzy goals and fuzzy constraints (original) (raw)
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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.
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.
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.
The International Journal of Advanced Manufacturing Technology, 2014
In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria. In this paper, a fuzzy multi-objective programming model is outlined to propose supplier selection taking quantitative, qualitative, and risk factors into consideration. Also quantity discount has been considered to determine the best suppliers and to place the optimal order quantities among them. The mixed integer derivative nonlinear programming is obtained from fuzzy multi-objective programming model by chance-constrained method. To solve this problem, an innovative method is proposed. In addition, several "what if" scenarios are facilitated. Finally, a real-life sample is used to validate the proposed model.
2019
For new strategies of purchase and production process, suppliers play a key role in achieving competitive capabilities for large-sized companies. The selection of suitable suppliers is a critical component of this strategy. The problem of allocating order to suppliers is a multi-objective one that includes fuzzy parameters; in addition, suppliers usually consider discount in the case of different levels of purchase amount. Since there is no multi-objective fuzzy model for order allocation in the literature to consider discount and shortfall simultaneously in the planning horizon of multiple products, this research proposes a new model that includes minimization of costs, delays, and the percentage of defective parts as objective functions. Price, demand, delay, and percentage of defective parts are considered fuzzy parameters. Since the model is NP-hard, the two metaheuristic algorithms, NSGAII and MOPSO, have been used for solving the problem with tuned parameters using Taguchi met...
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.
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.
The International Journal of Advanced Manufacturing Technology, 2009
Supplier selection and related issues are among the most important decisions in the supply chain management area. Even though there have been so many articles and studies that focused on the mentioned problem in the literature, a few of them considered the major decisions related to supplier selection. In an attempt to fulfill that void, we present an integrated framework that involves two stages: suppliers' evaluation and order allocation. For supplier evaluation, a fuzzy TOPSIS model with a combination of two validated coefficients is conducted. Then, an integer programming with fuzzy objectives and constraints is formulated to assign optimal quantity of order to allocated supplier. Finally, the framework is implemented in a case study organization, and the results are presented.
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...
A Fuzzy Multi Objective Model for Supplier Selection
2010
Supplier selection and determination of order quantities with selected suppliers is one of the most important activities in supply chain management. Hence, supplier selection problem should be performed by scientific methods and systematic approachs. In this study, a fuzzy multi objective model with an approach for supplier selection is presented. The fuzzy multi objective model with minimum and maximum order quantity constraint, delivery delay time constraint, defect number constraint and shortage number constraint is developed, then supplier selection problem solved by the extended model with fuzzy criteria weights that calculates by logarithmic least squares. In order to better description of the proposed approach and presented model, an example presented. Key-Words: Supplier selection, Fuzzy multi objective model, Logarithmic least squares approach.