Fuzzy Interactive Approach for a Multi-objective Supplier Selection Problem under Robust Uncertainty

In this paper, the authors proposed a multi-objective Mixed Integer Linear Programming (MILP) model for supplier selection problems. The main aim of the system under the investigation is to plan the companies to supply goods to achieve financial benefit by minimizing the total costs and satisfying the customers with on-time delivery and minimizing rejected items. In this case, some restrictions such as multi-product and multi-period conditions, shortage inventory constraints, and discount circumstances simultaneously are considered. Despite these efforts, due to the uncertainty nature of the problem, some parameters are considering as uncertainty data. For this aim, applying robust counterparts for uncertain parameters plays an essential role in real-world applications of this case. It is concluded that the feasibility and optimality properties of the usual solutions of real-world LPs can be severely affected by small changes of the data and that the robust optimization (RO) methodology can be successfully used to overcome this phenomenon

An Environmentally Conscious Multi-Objective Weber Problem for Green Location and Distribution Planning: A Fuzzy Weighted Additive Approach

In this study, a multi-objective Weber (p-median) problem is treated in order to determine the location of the warehouses to be opened and the distribution plans of products. The company carries out the distribution with three types of vehicles differing in unit transportation cost, carbon emission and velocity. Three conflicting objectives are aimed to be minimized, i.e.; the demand weighted total transportation cost, the total delivery time and the total carbon. We adopted a fuzzy weighted additive approach to deal with the multi-objective optimization function, in which the weights of each individual objective function are determined by Analytic Hierarchy Process

An Environmentally Conscious Multi-Objective Weber Problem for Green Location and Distribution Planning: A Fuzzy Weighted Additive Approach

In this study, a multi-objective Weber (p-median) problem is treated in order to determine the location of the warehouses to be opened and the distribution plans of products. The company carries out the distribution with three types of vehicles differing in unit transportation cost, carbon emission and velocity. Three conflicting objectives are aimed to be minimized, i.e.; the demand weighted total transportation cost, the total delivery time and the total carbon. We adopted a fuzzy weighted additive approach to deal with the multi-objective optimization function, in which the weights of each individual objective function are determined by Analytic Hierarchy Process

Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment

Purpose: The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM) model is presented to solve the proposed problem. Design/methodology/approach: The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO) is designed as the solution method. Findings: The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1. Practical implications: The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy. Originality/value: The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.Peer Reviewe

An Optimization Model for Ordering and Transporting Raw Materials by Manufacturers Based on Linear Programming

This study applies analytic hierarchy process (A­­­HP), 0-1 integer programming and other systematic programming models, combined with the needs of manufacturers to build a set of mathematical models to help manufacturers select suppliers, control raw material ordering costs, and transporting costs. As the production costs of products is linked to the ordering and transporting of raw materials, manufacturers need to choose suitable raw material suppliers and develop the most economical ordering and transporting schemes with the most negligible loss so as to improve profits and enhance the market competitiveness. Taking a building and decorative plate enterprise as a case, this model shows that AHP can effectively quantify the supplying characteristics of suppliers and obtain a list of high-quality suppliers. LINGO software combined with linear programming can be used to obtain the optimal weekly ordering and transporting schemes, thus reducing the raw material ordering costs and transporting losses. It is shown from the results that the production costs of enterprises from the source can be reduced so as to improve their cost control system. The present study seeks to fill the gap in ordering and transporting raw materials for manufacturers to control production costs. At the same time, this model provides references for producers who have the demand for processing raw materials and play a significant role in controlling production costs

İKİ AMAÇLI FARKLI MAKİNE SEÇENEKLİ KAPALI DÖNGÜ TEDARİK ZİNCİRİ OPTİMİZASYONU: BULANIK ÇÖZÜM TEKNİĞİ UYGULAMASI

Tedarik zinciri yönetimi, küreselleşme çağının başlangıcından beri akademisyenlerin ve uygulayıcıların artan ilgisini çekmeye devam etmiştir. Son yıllarda, tedarik zinciri yönetiminin odak noktası, enerji tüketimi, karbon emisyonları gibi ekonomik, sosyal ve çevresel yönlerin ortaklaşa ele alındığı sürdürülebilir akış yönetimi olmaya başlamıştır. Bu çalışmada, çok dönemli kapalı döngü tedarik zinciri ağ tasarım probleminin optimizasyonu için iki amaçlı karmaşık tamsayılı doğrusal programlama modelinin formüle edilmesi ve çözülmesi gerçekleştirilmiştir. Model, farklı makine tiplerinde faaliyet gösteren tesislerin toplam operasyon maliyeti ve toplam karbon emisyonları olmak üzere iki ayrı amacın minimizasyonunu hedeflerken, üretim ve dağıtım stratejilerini belirlemekte ve yeni veya eski tip makinelerin kullanımına da karar vermektedir. Daha eski ve güncel olmayan makinelerin ilk satın alma maliyeti, yeni ve güncellenmiş makinelere göre daha düşük olmasına rağmen, eski makineler, saat başına daha yüksek maliyetle çalışırken yeni makinelere göre saat başına daha fazla karbon salmaktadır. Ayrıca, bir saat içinde üretilen ürünlerin sayısı, yani üretkenlik, yeni makinelerde daha üstündür. Bu iki amaçlı kapalı döngü tedarik zinciri modelinin çözümü için bulanık ağırlıklandırma yaklaşımı kullanılmıştır. Sonuçlar, üretimde yeni nesil teknolojilere yatırım yapılmasının hem ekonomik hem de çevresel amaçlara ulaşmak için önemli olduğunu göstermektedir

Multi-Criteria Decision-Making Methods Application in Supply Chain Management: A Systematic Literature Review

Over the last decade, a large number of research papers, certified courses, professional development programs and scientific conferences have addressed supply chain management (SCM), thereby attesting to its significance and importance. SCM is a multi-criteria decision-making (MCDM) problem because throughout its process, different criteria related to each supply chain (SC) activity and their associated sub-criteria must be considered. Often, these criteria are conflicting in nature. For their part, MCDM methods have also attracted significant attention among researchers and practitioners in the field of SCM. The aim of this chapter is to conduct a systematic literature review of published articles in the application of MCDM methods in SCM decisions at the strategic, tactical and operational levels. This chapter considers major SC activities such as supplier selection, manufacturing, warehousing and logistics. A total of 140 published articles (from 2005 to 2017) were studied and categorized, and gaps in the literature were identified. This chapter is useful for academic researchers, decision makers and experts to whom it will provide a better understanding of the application of MCDM methods in SCM, at various levels of the decision-making process, and establish guidelines for selecting an appropriate MCDM method for managing SC activities

Integrated FANP-f-MIGP model for supplier selection in the renewable energy sector

The available integrated models for choosing efficient suppliers developed so far are mostly specific to companies with mass production capabilities. However, in some sectors involved in project-type manufacturing, the same decision-making criteria cannot be applied and, plus, there is no point in determining the quantity of orders. For instance, in wind power plant projects, a single turbine supplier needs to be selected for each project. This study proposes an integrated FANP-f-MIGP model that ensures the selection of the optimal supplier for each project by applying the model to an energy firm. The criteria specific to the selection of wind power plant turbine suppliers are established, and the criteria weights are obtained by fuzzy analytic network process (FANP). As a result of the analysis, the most important criterion of all is cost. These weights constitute the coefficients of the f-MIGP model’s objective function. Under the defined constraints, by minimizing cost and risk and maximizing quality and services of the firm, the selection of an optimal wind turbine supplier from three suppliers for each of three projects is ensured. This study contributes to the literature both by the specific criteria it establishes and its proposed integrated model which allows for the selection of the best supplier in wind turbine and similar project-based productions

A Novel Hybrid Fuzzy Multi-Criteria Decision-Making Model for Supplier Selection Problem (A Case Study in Advertising industry)

Abstract Choosing the proper supplier has a critical role in designing of a supply chain. This problem is complex because each supplier may fulfill some of the manufacturer criteria and choosing the best supplier is a multi criteria problem. This paper proposes a novel hybrid approach to rank suppliers in advertising industry and considers two new criteria to evaluate the suppliers. The proposed approach combines Modified Digital Logic (MDL) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using fuzzy theory. At the end, the results of the proposed approach are compared with a hybrid method using Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy TOPSIS on a real case study