Luu Quoc Dat

Optimizing reverse logistic costs for recycling end-of-life electrical and electronic products

With accelerating technological changes and market expansions of electrical and electronic products (EEPs) during the last few decades, much focus and effort have been placed on the waste of these products. In order to reduce their negative impacts on the environment and human, at the end of their product lifecycles, their wastes need to be properly handled, processed, disposed, and if applicable, remanufactured, recycled or reused. Based on the analysis of the waste EEPs (WEEPs) reverse logistic network, this paper presents a mathematical programming model which minimizes the total processing cost of multiple types of WEEPs. The monetary factors considered in the model include the costs of collection, treatment, and transportation as well as sales income with different fractions of returned products. Based on the proposed model, the optimal facility locations and the material flows in the reverse logistic network can be determined. A sensitivity analysis of the proposed model is also presented. Finally, a numerical example is illustrated to gain a better insight into the proposed model.

A revised method for ranking fuzzy numbers using maximizing set and minimizing set

A large number of methods have been proposed for ranking fuzzy numbers in the last few decades. Nevertheless, none of these methods can always guarantee a consistent result for every situation. Some of them are even non-intuitive and not discriminating. Chen proposed a ranking method in 1985 to overcome these limitations and simplify the computational procedure based on the criteria of total utility through maximizing set and minimizing set. However, there were some shortcomings associated with Chens ranking method. Therefore, we propose a revised ranking method that can overcome these shortcomings. Instead of considering just a single left and a single right utility in the total utility, the proposed method considers two left and two right utilities. In addition, the proposed method also takes into account the decision makers optimistic attitude of fuzzy numbers. Several comparative examples and an application demonstrating the usage, advantages, and applicability of the revised ranking method are presented. It can be concluded that the revised ranking method can effectively resolve the issues with Chens ranking method. Moreover, the revised ranking method can be used to differentiate different types of fuzzy numbers.

An improved ranking method for fuzzy numbers with integral values

Ranking fuzzy numbers is a very important decision-making procedure in decision analysis and applications. The last few decades have seen a large number of approaches investigated for ranking fuzzy numbers, yet some of these approaches are non-intuitive and inconsistent. In 1992, Liou and Wang proposed an approach to rank fuzzy number based a convex combination of the right and the left integral values through an index of optimism. Despite its merits, some shortcomings associated with Liou and Wangs approach include: (i) it cannot differentiate normal and non-normal fuzzy numbers, (ii) it cannot rank effectively the fuzzy numbers that have a compensation of areas, (iii) when the left or right integral values of the fuzzy numbers are zero, the index of optimism has no effect in either the left integral value or the right integral value of the fuzzy number, and (iv) it cannot rank consistently the fuzzy numbers and their images. This paper proposes a revised ranking approach to overcome the shortcomings of Liou and Wangs ranking approach. The proposed ranking approach presents the novel left, right, and total integral values of the fuzzy numbers. The median value ranking approach is further applied to differentiate fuzzy numbers that have the compensation of areas. Finally, several comparative examples and an application for market segment evaluation are given herein to demonstrate the usages and advantages of the proposed ranking method for fuzzy numbers.

Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making

Neutrosophic set is a powerful general formal framework which generalizes the concepts of classic set, fuzzy set, interval-valued fuzzy set, intuitionistic fuzzy set, etc. Recent studies have developed systems with complex fuzzy sets, for better designing and modeling real-life applications. The single-valued complex neutrosophic set, which is an extended form of the single-valued complex fuzzy set and of the single-valued complex intuitionistic fuzzy set, presents difficulties to defining a crisp neutrosophic membership degree as in the single-valued neutrosophic set. Therefore, in this paper we propose a new notion, called interval complex neutrosophic set (ICNS), and examine its characteristics. Firstly, we define several set theoretic operations of ICNS, such as union, intersection and complement, and afterward the operational rules. Next, a decision-making procedure in ICNS and its applications to a green supplier selection are investigated. Numerical examples based on real dataset of Thuan Yen JSC, which is a small-size trading service and transportation company, illustrate the efficiency and the applicability of our approach.

Parting curve selection and evaluation using an extension of fuzzy MCDM approach

Parting curve selection and evaluation plays an important role in mold design. Multiple criteria decision-making (MCDM) is an effective tool for evaluating and ranking problems involving multiple criteria. In order to select suitable parting curve, several criteria need to be taken into account. Therefore, this paper proposes an extension of fuzzy MCDM approach to solve parting curve selection problem. In the proposed model, the ratings of alternatives and importance weights of criteria for parting curve selection are expressed in linguistic terms. The membership functions of the final fuzzy evaluation value in the proposed model are developed based on the linguistic expressions. To make the procedure easier and more practical, the normalized weighted ratings are defuzzified into crisp values by using a new maximizing set and minimizing set ranking approach to determine the ranking order of alternatives. An example of parting curve evaluation and selection is given. The results show that the proposed approach is very effective in selecting the optimal parting curve for the molded part. Finally, this paper compares the proposed approach with another fuzzy MCDM approach to demonstrate its advantages and applicability.

Analyzing the ranking method for L-R fuzzy numbers based on deviation degree

Ranking fuzzy numbers based on their left and right deviation degree (L-R deviation degree) has attracted the attention of many scholars recently, yet most of their ranking methods have two systematic shortcomings that are usually ignored. This paper addresses these shortcomings and proves them through mathematical proofs instead of providing counter-examples. Applying our analyses will help other authors avoid some common errors when building their own ranking index functions. We use Asadys ranking index function (2010) as an example when we present our arguments and proofs and provide fully detailed analyses of two of the ranking index functions herein. Based on these analyses, an algorithm for detecting inconsistencies in ranking results is proposed, and numerical examples are given to illustrate our arguments.

Selection of Key Component Vendor from the Aspects of Capability, Productivity, and Reliability

In a technology-driven industry, the appropriate vendors/suppliers can effectively contribute to cobusiness development profits. Key component vendors help dynamically drive solution design firms to achieve strong performances, especially when an integrated circuit (IC) component that has technical know-how specifications dominates an electronic solution design. This paper presents a systematic framework to examine the decision process for the selection of wireless fidelity (Wi-Fi) IC vendor alternatives from the business ecosystem aspect in order to review the importance of buyer-supplier synergistic effects. We implement the fuzzy analytic hierarchy process technique which incorporates a vendor’s capability, productivity, and reliability characteristics into a hierarchical structure and deploys decision experts’ judgments along with vague data analysis to solve a real-world problem faced by a leading company specialized in the research and design of wireless networking solutions. The findings indicate the Taiwanese local vendor is the top priority for alternatives selection, and the results contribute significant values to the design firm’s operation management.

Intelligent Autonomous Navigation System for the Wheeled Mobile Robot

An intelligent behavior control system for an autonomous mobile robot operating in an unstructured environment with sensor uncertainties is proposed. This study focuses on implementing and improving the methodology from Motlagh et al. [7] on a two-wheeled P3DX mobile robot. Motlagh et al. verified their design with computer simulation. When applying it on a real robot platform, we noticed some problems and improved the design using sensor selection strategy, safe rule and target switching strategy. The proposed sensor fusion architecture introduces two additional sensors, a laser range finder on the robot and an omnidirectional CCD camera on the ceiling, to improve the reliability of the sensing capability of P3DX mobile robot. The target switching strategy is used to guide the robot out of a dead zone and reach the target by creating a virtual target. Results of the experiments with the U-shaped and subspace dead zones are presented. These results proved that the target switching strategy successfully dealt with the loop path problem in the dead zone.

Analyzing the Ranking Method for Fuzzy Numbers in Fuzzy Decision Making Based on the Magnitude Concepts

Ranking fuzzy numbers is an important component in the decision-making process with the last few decades having seen a large number of ranking methods. Ezzati et al. (Expert Syst Appl 39:690–695, 2012) proposed a revised approach for ranking symmetric fuzzy numbers based on the magnitude concepts to overcome the shortcoming of Abbasbandy and Hajjari’s method. Despite its merits, some shortcomings associated with Ezzati et al.’s approach include: (1) it cannot consistently rank the fuzzy numbers and their images; (2) it cannot effectively rank symmetric fuzzy numbers; and (3) it cannot rank non-normal fuzzy numbers. This paper thus proposes a revised method to rank generalized and/or symmetric fuzzy numbers in parametric forms that can surmount these issues. In the proposed ranking method, a novel magnitude of fuzzy numbers is proposed. To differentiate the symmetric fuzzy numbers, the proposed ranking method takes into account the decision maker’s optimistic attitude of fuzzy numbers. We employ several comparative examples and an application to demonstrate the usages and advantages of the proposed ranking method. The results conclude that the proposed ranking method effectively resolves the issues with Ezzati et al.’s ranking method. Moreover, the proposed ranking method can differentiate different types of fuzzy numbers.

Supplier selection and evaluation using generalized fuzzy multi-criteria decision making approach

Supplier selection and evaluation plays an importance role for companies to gain competitive advantage and achieve the objectives of the whole supply chain. To select the appropriate suppliers, many qualitative and quantitative criteria are needed consider in the decision process. Therefore, supplier selection and evaluation can be seem as a multi-criteria decision making (MCDM) problem in vague environment. However, most existing fuzzy MCDM approaches have been developed using normal fuzzy numbers or converting generalized fuzzy numbers into normal fuzzy numbers through normalization process. This leads to a restriction in the application of the fuzzy MCDM approaches. In this study, a generalized fuzzy MCDM approach is proposed to select and evaluate suppliers. In the proposed approach, the ratings of alternatives and important weights of criteria are expressed in linguistic terms using generalized fuzzy numbers. Then, the membership functions of the final fuzzy evaluation value are developed. To make procedure easier and more practical, the weighted ratings are defuzzified into crisp values by employing the maximizing and minimizing set ranking approach to determine the ranking order of alternatives. Finally, a numerical example is presented to illustrate the applicability and efficiency of the proposed method.