A fuzzy integrated approach for project selection

Abstract

Purpose – The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers. Design/methodology/approach – First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model. Findings – The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers. Research limitations/implications – Future studies are suggested to design models having fuzzy constraints such as budget and resources. Moreover, for future studies, non-linear membership functions can be used. Practical implications – Actual projects are provided from the Turkish IS company for prioritizing process and a hypothetical mathematical model is demonstrated using illustrative data. Originality/value – This study contributes to the relevant literature by proposing a comprehensive model considering many conflicting ideas of decision makers on quantitative and qualitative criteria, and evaluating projects in an integrated way including FAHP and FMOLP.

Selection of Communication Routes in Agriculture Equipment Company

“…The problem is balanced if the overall supply equals overall demand. Each route from any supplier to any target location is evaluated with the cost coefficient c ijk , i = 1,…m, j = 1,.., n, k = 1,…, p. The threedimensional transportation model can be formulated in two forms, the planar formulation corresponds to the formulation of simple transportation model, see (2): subject to (2) where the decision variables x ijk represent the amounts to be transported from source locations i to target destinations j using k type of transport.…”

“…However, multi-criteria decision-making methods do not provide any optimal solution but only a kind of compromise between a set of criteria (Bolat et al, 2014). The model of system dynamics used by Saleh et al (2010) and Hämäläinen et al (2013) examined behavioural effects associated with group interaction and communication, changes in the target behaviour, and changes of interest.…”

A Consistent Fuzzy Preference Relations Based ANP Model for R&D Project Selection

“…Tavana et al [13] proposed a model consisting of three sections that is DEA, TOPSIS, and linear integer programming for the selection of an optimal project portfolio. In a fuzzy environment, Bolat et al [14] developed a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming that could deal with imprecise data and the uncertain judgments of decision-makers. These studies have yielded mathematical tools such as mixed-integer or nonlinear programs that are not easy to solve and, being too complex to use, have not been applied in practice.…”

“…Many mathematical programming methods have been adapted to create decision models for R&D project selection, including integer programming [13], linear programming [14], nonlinear programming [15], goal programming [16] and dynamic programming [17] techniques. Tavana et al [13] proposed a model consisting of three sections that is DEA, TOPSIS, and linear integer programming for the selection of an optimal project portfolio.…”

“…In addition, the original ANP needs to check the consistent index, and the CFPR-ANP resolves the shortcoming. The inconsistency is resolved based on the additive transitivity property of the consistent fuzzy preference relation using Equations (8) to (14) to construct the pairwise comparison matrices. In this hybrid CFPR-ANP method, consistency checks are not required and all pairwise comparisons are consistent [38].…”