İrem Otay

Multi-Criteria and Multi-Stage Facility Location Selection under Interval Type-2 Fuzzy Environment: A Case Study for a Cement Factory

AbstractThe study proposes a comprehensive and systematic approach for multi-criteria and multi-stage facility location selection problem. To handle with high and more uncertainty in the evaluation and selection processes, the problem is solved by using multi-criteria decision making technique with interval Type-2 fuzzy sets. The study contributes the facility location selection literature by introducing the application of fuzzy TOPSIS method with interval Type-2 fuzzy sets. Finally, the suggested approach is applied to a real life region and site selection problem of a cement factory.

A fuzzy integrated approach for project selection

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 ...

A fuzzy multi-objective model for solving project network problem with bonus and incremental penalty cost

We develop multiobjective linear mathematical model for project network problem under fuzziness.We design a model supporting project managers to evaluate bonus and incremental penalty cost simultaneously.We compare the findings with different methods under various sets of weights.We demonstrate a real life case study to check the feasibility of the model.We observed that the trade-off between time & cost is significant and implementation of the proposed method may provide substantial savings. Project management decisions require considering several conflicting constraints and objectives as well as uncertainties in the information over the planning period. The study aims to design a multi-objective linear programming model for solving project network problem under fuzzy environment. The developed model consists of three objectives such as minimizing total project completion time, minimizing total project completion cost and minimizing the earliest time of an event requiring special attention by taking into account several factors such as crash time, normal time, normal cost, crash cost, indirect cost as well as financial bonus and incremental penalty cost. In the study, a case study based on a real life problem is conducted to illustrate the validity and feasibility of the model. The study contributes to the project network literature by developing the fuzzy goal programming model and allows the project managers simultaneously evaluate financial bonus and incremental penalty cost with respect to total project time. In addition, the results of the sensitivity analysis highlight that the developed model can be used for helping the contractors make effective decisions.

A multiobjective fuzzy mathematical model for a supply chain problem with the forward and reverse flows

Reverse logistics has been one of the complex and popular topics drawing attentions of the researchers and practitioners. Recovery of products has many advantages to companies in reducing costs and protecting the environment. In this study, one of the recovery options, namely reuse, is analysed. For this pursuit, a mathematical model is developed to plan production and distribution of the reusable products as well as the new products by considering the forward and reverse flows of the products. The model is a multi-echelon supply chain model composed of multiple customers, multiple distributors, multiple transshipment points, and a factory. Due to vagueness, ambiguity and lack of information in the reverse logistics, the problem is constructed and solved under the fuzzy environment. The model is implemented on a hypothetical supply chain network based on an industrial case, and the results of the model are compared with the results of the other methods.

Fuzzy Extensions of Confidence Intervals: Estimation for µ, σ2, and p

Even though classical point and interval estimations (PIE) are one of the most studied fields in statistics, there are a few numbers of studies covering fuzzy point and interval estimations. In this pursuit, this study focuses on analyzing the works on fuzzy PIE for the years between 1980 and 2015. In the chapter, the literature is reviewed through Scopus database and the review results are given by graphical illustrations. We also use the extensions of fuzzy sets such as interval-valued intuitionistic fuzzy sets (IVIFS) and hesitant fuzzy sets (HFS) to develop the confidence intervals based on these sets. The chapter also includes numerical examples to increase the understandability of the proposed approaches.

Fuzzy Sets in Earth and Space Sciences

Earth science refers to the field of science dealing with planet Earth while space science pertains several scientific disciplines studying the upper atmosphere, space, and celestial bodies rather than Earth. The fuzzy set theory is one of the tools that has been recently used in the earth and space sciences. In this chapter, we review and analyze the papers utilizing fuzzy logic in earth and space science problems from Scopus database. The graphical and tabular illustrations are presented for the subject areas, publication years and sources of the papers on earth and space sciences.

A Review on Intelligent Systems in Research and Development

Research and development (R&D) is one of the topics drawing great concern from researchers and practitioners. R&D is important for many of the areas such as pharmaceutical and medical industry, technology, and manufacturing. On the other hand, the sophisticated nature of the real life problems and its long computational time led researchers to develop intelligent systems. Intelligent systems have been used in many of the R&D areas since they give more reliable and consistent solutions when compared to the traditional solution techniques. In this pursuit, the chapter focuses on analyzing intelligent systems from a broader perspective considering a various research and development areas. For this aim, a comprehensive literature review from the years mainly between 2000 and 2014 is conducted. From the literature, it is observed that there are a large number of studies from 2010 to 2014. The motivation to conduct this chapter is to contribute to the literature by presenting an extensive literature review and making a synthesis with regard to intelligent systems in research and development .