Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

Fuzzy Bi-level Decision-Making Techniques: A Survey

© 2016 the authors. Bi-level decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a bi-level hierarchy. A challenge in handling bi-level decision problems is that various uncertainties naturally appear in decision-making process. Significant efforts have been devoted that fuzzy set techniques can be used to effectively deal with uncertain issues in bi-level decision-making, known as fuzzy bi-level decision-making techniques, and researchers have successfully gained experience in this area. It is thus vital that an instructive review of current trends in this area should be conducted, not only of the theoretical research but also the practical developments. This paper systematically reviews up-to-date fuzzy bi-level decisionmaking techniques, including models, approaches, algorithms and systems. It also clusters related technique developments into four main categories: basic fuzzy bi-level decision-making, fuzzy bi-level decision-making with multiple optima, fuzzy random bi-level decision-making, and the applications of bi-level decision-making techniques in different domains. By providing state-of-the-art knowledge, this survey paper will directly support researchers and practitioners in their understanding of developments in theoretical research results and applications in relation to fuzzy bi-level decision-making techniques

Fuzzy multi-objective bilevel decision making by an approximation Kth-best approach

Many industrial decisions problems are decentralized in which decision makers are arranged at two levels, called bilevel decision problems. Bilevel decision making may involve uncertain parameters which appear either in the objective functions or constraints of the leader or the follower or both. Furthermore, the leader and the follower may have multiple conflict decision objectives that should be optimized simultaneously. This study proposes an approximation K th-best approach to solve the fuzzy multi-objective bilevel problem. Two case based examples further illustrate how to use the approach to solve industrial decision problems

A two-phase procedure for a multi-objective programming problem with fuzzy coefficients based on group decision making for project selection

Regional Development Agencies (RDAs) play a major role in ensuring sustainability and reducing inter-regional and intra-regional development disparities in line with the principles and policies set in the National Development Plan and Programs. This is done by enhancing cooperation among the public and private sectors, as well as non-governmental organizations. To achieve these targets, RDAs use certain tools such as financial support programs, technical support programs, and the like. Accordingly, an effective evaluation mechanism is crucial in selecting projects that have more added value and higher multiplier effects. In this regard, determining the right parameters that assist in choosing the best projects should be clearly demonstrated. In this study, the selection of projects according to the evaluating criteria of support mechanisms considered by RDAs are discussed through the procedure provided by a practical solution methodology, which is an integration of fuzzy parametric programming (FPP) and fuzzy linear programming (FLP). Later, a two-phase procedure is introduced to solve multi-objective fuzzy linear programming problems

Fuzzy multilevel programming with a hybrid intelligent algorithm

AbstractIn order to model fuzzy decentralized decision-making problem, fuzzy expected value multilevel programming and chance-constrained multilevel programming are introduced. Furthermore, fuzzy simulation, neural network, and genetic algorithm are integrated to produce a hybrid intelligent algorithm for finding the Stackelberg-Nash equilibrium. Finally, two numerical examples are provided to illustrate the effectiveness of the hybrid intelligent algorithm

Fuzzy Linear Programming in DSS for Energy System Planning

Energy system planning requires the use of planning tools. The mathematical models of real-world energy systems are usually multiperiod linear optimization programs. In these models, the objective function describes the total discounted costs of covering the demand for final energy or energy services. The demand for various forms of energy or energy services is the driving force of the models. By using such linear programming (LP) formulations, decision makers can elaborate suitable strategies for solving their planning problems, such as the development of emission reduction strategies. Uncertainties that affect the process of energy system planning can be divided into parameter and decision uncertainties. Data or parameter uncertainties can be addressed either by stochastic optimization or by the methodology of fuzzy linear programming (FLP). In addition, FLP allows explicit incorporation of decision uncertainties into a mathematical model. This paper therefore aims at evaluating the methodology of FLP with respect to the support that it offers the decision-making process in energy system planning under uncertainty. Employing the parallels between multi-objective linear programming (MOLP) and FLP, problems of FLP in decision support system applications are pointed out and solutions are offered. The proposed modifications are based on the methodology of aspiration-reservation based decision support and still enable modeling of uncertainties in a fuzzy sense. A case study is documented to show the application of the modified FLP approach

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Short Software Descriptions

This paper briefly presents the software for interactive decision support that was developed in 1990-1991 within the Contracted Study Agreement between the System and Decision Sciences Program at IIASA and several Polish scientific institutions, namely: Institute of Automatic Control (Warsaw University of Technology); Institute of Computing Science (Technical University of Poznaii); Institute of Informatics (Warsaw University); and Systems Research Institute of the Polish Academy of Sciences. This Contracted Study Agreement has been a continuation of the same type of activity conducted since 1985. Therefore many of the software packages are actually improved versions of the programs developed in 1985-1989. The theoretical part of the results developed within this scientific activity is presented in the IIASA Collaborative Paper CP-90-008 by A. Ruszczynski, T. Rogowski and A.P. Wierzbicki entitled "Contributions to Methodology and Techniques of Decision Analysis (First Stage)." Detailed descriptions of the methodology and the user guide for each particular software package are published in separate Collaborative Papers. Each software package described here is available in executable form for non-profit educational and scientific purposes, however, any profit-oriented or commercial application requires a written agreement with IIASA. Inquires about the software should be directed to the System and Decision Sciences Program at IIASA, Methodology of Decisions Analysis Project

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler's demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method. (C) 2014 Elsevier Inc. All rights reserved.This work has been funded partly by the Spanish Ministry of Science and Technology project: Production technology based on the feedback from production, transport and unload planning and the redesign of warehouses decisions in the supply chain (Ref. DPI2010-19977) and by the Universitat Politecnica de Valencia project 'Material Requirement Planning Fourth Generation (MRPIV) (Ref. PAID-05-12)'.Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2014). A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Applied Mathematical Modelling. 38(23):5705-5725. https://doi.org/10.1016/j.apm.2014.04.053S57055725382