Abstract

Suppliers play the vital role of ensuring the continuous supply of goods to the market for businesses. If businesses do not maintain a strong bond with their suppliers, they may not be able to secure a steady supply of goods and products for their customers. As a result of failure to deliver products, the production and business activities of the business can be delayed which leads to the loss of customers. Normally, each trading enterprise will have a variety of commodity supply chains with multiple suppliers. Suppliers play an important role and contribute to the value of the entire supply chain. Should any supplier encounters a problem, the whole supply chain of businesses will be affected and could lead to not guaranteeing the stable supply to the market. Thus, suppliers can be seen as a threat to businesses where they have the ability to increase input prices or decrease the quality of the required products and services they provide. The quantity of the business, and the supply lead time directly affect the operations and reduce the profitability of the business. The paper mainly focuses on the supplier selection problem under a variety of price level and product families when using a two-phase fuzzy multi-objective linear programming. The objectives of the proposed model are to minimize the total purchasing and ordering cost in order to reduce the quantity of defective materials and the late-delivery components from suppliers. Moreover, the piecewise linear membership function is applied in the model to determine an optimal solution which is based on the requirement of decision makers under their fuzzy environment. The results of this study can be applied in various business environment and provide a reliable decision tool for choosing potential suppliers relating to these objectives. Based on the results, the company can make a good decision on supplier selection; therefore, the company can improve the quality and quantity of their final product. This is because, the best supplier can supply raw material using just-in-time application and reduce production risk on the manufacturing process.

Highlights

  • In the current international competitive environment, most companies attempt to meet the customers’ demand, improve quality, and reduce manufacturing cost

  • The introduced model utilized the Best–Worst method (BWM), TOPSIS model, and fuzzy multi-objective linear programming (FMOLP) technique to evaluate the performance of potential suppliers and optimize order allocation among qualified suppliers

  • The Analytic Network Process (ANP) method is applied to calculate the ranking of potential suppliers based on relevant criteria and the Multiobjective Mixed Integer Linear Programming (MOMILP) model is used to determine the order allocation among these suppliers, with the objectives of minimizing budget and defect rate

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Summary

Introduction

In the current international competitive environment, most companies attempt to meet the customers’ demand, improve quality, and reduce manufacturing cost As a result, they focus heavily on production cost and supplier selection. Due to the conflict among the three objective functions: minimize the total purchasing and ordering cost, minimize the net number of late delivered goods ordered from suppliers, and minimize the net number of rejected items form the suppliers, a fuzzy goal approach is proposed in this research to solve the model under multi-price level and product families. The aim of the research is to develop a two-phase fuzzy multi-objective linear programming model to support the supplier selection and order allocation process under vary price level and multi-product condition.

Literature Review
Parameters
Mathematical Model Model constrains
Findings
Interactive Two-Phase Fuzzy Multi-Objective Linear Programming Model
Full Text
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