Alev Taskin Gumus

Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology

Hazardous wastes are likely to cause danger to human health and/or environment. Safe transportation of them is so important. Consequently, selection of the right and most appropriate transportation firm is an important problem for hazardous waste generators. In this paper, a two step methodology is structured to evaluate hazardous waste transportation firms containing the methods of fuzzy-AHP and TOPSIS. And a numerical example is presented to clarify the methodology.

Supply chain network design using an integrated neuro-fuzzy and MILP approach: A comparative design study

In this study, an integrated supply chain (SC) design model is developed and a SC network design case is examined for a reputable multinational company in alcohol free beverage sector. Here, a three echelon SC network is considered under demand uncertainty and the proposed integrated neuro-fuzzy and mixed integer linear programming (MILP) approach is applied to this network to realize the design effectively. Matlab 7.0 is used for neuro-fuzzy demand forecasting and, the MILP model is solved using Lingo 10.0. Then Matlab 7.0 is used for artificial neural network (ANN) simulation to supply a comparative study and to show the applicability and efficiency of ANN simulation for this type of problem. By evaluating the output data, the SC network for this case is designed, and the optimal product flow between the factories, warehouses and distributors are calculated. Also it is proved that the ANN simulation can be used instead of analytical computations because of ensuring a simplified representation for this method and time saving.

A multi-echelon inventory management framework for stochastic and fuzzy supply chains

In this paper, for effective multi-echelon supply chains under stochastic and fuzzy environments, an inventory management framework and deterministic/stochastic-neuro-fuzzy cost models within the context of this framework are structured. Then, a numerical application in a three-echelon tree-structure chain is presented to show the applicability and performance of proposed framework. It can be said that, by our framework, efficient forecast data is ensured, realistic cost titles are considered in proposed models, and also the minimum total supply chain cost values under demand, lead time and expediting cost pattern changes are presented and examined in detail.

A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets

A literature review of IT2FSs based MCDM approaches is presented.The systematic classification covers 35 MCDM approaches as single and hybrid.It provides an insight for researchers on IT2FSs based MCDM approaches. Multi criteria decision making (MCDM) is a discipline of operations research which has widely studied by researchers and practitioners. It deals with evaluating and ranking alternatives from the best to the worst under conflicting criteria with respect to decision maker(s) preferences. Since, many real-world systems include uncertainty and vagueness in information, MCDM uses fuzzy sets. In recent years, as an extension of the traditional fuzzy sets concept, type-2 fuzzy sets are preferred to have the capability of handling more uncertainty, and hence, to produce more accurate and robust results, MCDM approaches based on interval type-2 fuzzy sets (IT2FSs) have been published in various subjects. This paper reviews 82 different papers using various MCDM approaches based on IT2FSs which are classified into 35 categories. All papers with respect to single and hybrid approaches are discussed, pointing out their real applications or empirical results and limitations. Furthermore, the papers are statistically analyzed to show new trends within the context of IT2FSs. This systematic and comprehensive review study provides an insight for researchers on interval type-2 fuzzy MCDM in terms of showing current state and potential areas to be focused in the future.

An evaluation of quality goals by using fuzzy AHP and fuzzy TOPSIS methodology

There is no defined methodological approach that would rank the quality goals of a process in uncertain environments, which is one of the basic problems in process management. In this paper, the considered problem is stated as a multi-criteria decision problem. The criteria present performances which are defined by the knowledge and experience of the decision makers. The fuzzy rating weights of each pair of the considered criteria and uncertain criteria values for the defined quality goals are described by linguistic expressions which are modeled by triangular fuzzy numbers. The weights vector of criteria is calculated by the fuzzy Analytic Hierarchical Process AHP. The extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution TOPSIS is applied to rank quality goals. The proposed model is illustrated by an example.

A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management

Disaster and humanitarian logistics are one of the most important subjects for a country to take care about. It is possible to increase the performance of humanitarian relief logistics management processes by several planning and prevention activities. This papers main contribution is identifying and then evaluating the success factors which are critical for effective management of humanitarian relief logistics operations. Therefore, an effective method that combines type-2 fuzzy sets, which provide additional degrees of freedom to present the uncertainty and the fuzziness of the real world, and analytic hierarchy process, is proposed to sustain a realistic evaluation. It is aimed that, the proposed method will be used by governmental and non-governmental organizations to improve their HRLM activities and strategies.

A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making

Third-party logistics (3PL) service provider selection for a strategic alliance is not an easy decision, and is constantly associated with uncertainty and complexity. For this reason, in this study, a hybrid fuzzy multi-criteria decision-making methodology is proposed to provide a systematic decision support tool for 3PL provider evaluation, especially for 3PL transportation provider. The proposed evaluation methodology consists of several steps. First, the strategic goal and sub-attributes are identified for 3PL service provider evaluation. After constructing the hierarchy, Buckley’s fuzzy-analytical hierarchy process (AHP) extension algorithm is used to determine the evaluation criteria weights. Then, by using fuzzy-AHP results as input weights, the fuzzy-Technique for Order Preference by Similarity to Ideal Solution technique is conducted in order to identify the most suitable third-party providers. Finally, a real-life case study in a confectionary company is presented to demonstrate the potential use of the methodology and a sensitivity analysis is performed to analyse the hybrid methodology proposed here. In the conclusion of the study, future recommendations are presented.

An assessment approach for non-governmental organizations in humanitarian relief logistics and an application in Turkey

Abstract.The ever-increasing natural disasters have been causing the loss of lives, properties and resources. By the preparedness and response ability of non-governmental organizations, it is aimed to minimize these losses. In this paper, first, the critical success factors of humanitarian relief logistics management operations are determined and categorized. Then, by considering these factors, a hybrid method that consists of trapezoidal interval type-2 fuzzy sets, AHP and TOPSIS, is proposed to evaluate emergency preparedness and response ability performance of non-governmental relief organizations. The proposed hybrid method is applied for non-governmental relief organizations in Turkey to evaluate their performance, and to the factors need to be improved for each determined organization.

An outranking approach based on interval type-2 fuzzy sets to evaluate preparedness and response ability of non-governmental humanitarian relief organizations

A hybrid AHP and PROMETHEE approach based on IT2FSs is proposed.The preparedness and response ability of NGOs is evaluated.The proposed hybrid approach is applied for NGOs in Turkey. After a disaster occurs, national and international non-governmental humanitarian relief organizations (NGOs), as well as the governmental humanitarian relief organizations (GOs), are involved in carrying out the humanitarian relief operations because of insufficiency in recourses such as lack of equipment and human resources. GOs and NGOs play a crucial role in preparedness and response to natural disasters, especially when available resources of them are not enough. The preparedness and response ability of GOs and NGOs aim to minimize the losses and number of affected people. Therefore, the preparedness and response ability of NGOs are becoming more important to support governmental relief activities. In this paper, a hybrid approach, that consists of interval type-2 fuzzy sets, AHP and PROMETHEE, is proposed to evaluate emergency preparedness and response ability performances of NGOs. The proposed hybrid approach is applied to NGOs in Turkey to evaluate their performances, and is conducted in three phases: (1) determination of critical success factors (CSFs) of humanitarian relief logistics management operations, (2) application of interval type-2 fuzzy AHP for obtaining importance weights of CSFs and (3) application of PROMETHEE based on interval type-2 fuzzy sets to evaluate preparedness and response abilities of NGOs.

A New Extension of the ELECTRE Method Based Upon Interval Type-2 Fuzzy Sets for Green Logistic Service Providers Evaluation

Increase in environmental pollution makes companies give more importance to this issue, and as such, there is a need to take into account the necessary precautions. In particular, logistics service providers who are interwoven with the environment should apply some policies to increase environmental awareness. In this paper, we extended the ELECTRE method and proposed a new methodology for handling fuzzy multi criteria decision making problems based upon interval type-2 fuzzy sets. Interval type-2 fuzzy sets provided more df to reflect the uncertainty and the fuzziness of the real applications. An empirical study was presented in order to evaluate the green logistics service providers. A sensitivity analysis was applied to discuss and evaluate the greenness of the logistic service providers.