Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

Abstract

Introduction/purpose: The paper presents a model for the selection of a route for the transport of hazardous materials using fuzzy logic systems, as a type of artificial intelligence systems. The system presented in the paper is a system for assistance in the decisionmaking process of the traffic service authorities when choosing one of several possible routes on a particular path when transporting hazardous materials. Methods: The route evaluation is performed on the basis of five criteria. Each input variable is represented by three membership functions, and the output variable is defined by five membership functions. All rules in a fuzzy logic system are determined by applying the method of weight premise aggregation (ATPP), which allows the formation of a database based on experience and intuition. Based on the number of input variables and the number of their membership functions, the basic base of 243 rules is defined. Three experts from the Ministry of Defense were interviewed to determine the weighting coefficients of the membership functions, and the values of the coefficients were determined using the Full Consistency Method (FUCOM). Results: A user program which enables the practical application of this model has been created for the developed fuzzy logic system. Conclusion: The user platform was developed in the Matlab 2008b software package.

Robust Aggregation Operators for Intuitionistic Fuzzy Hypersoft Set with Their Application to Solve MCDM Problem

“…The problem of selecting and evaluating a sustainable supplier is addressed in many works. Analyzing papers [49][50][51] and using review papers [52][53][54] in this example of sustainable supplier selection, it was decided to extract the following set of five basic criteria. These are: c 1 , quality of service; c 2 , pollution control; c 3 , environmental efficiency; c 4, price; and c 5 , corporate social responsibility.…”

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

“…Fuzzy logic techniques are efficient in solving complex, ill-defined problems that are characterized by uncertainty of environment and fuzziness of information [36,37]. Taking into account that disturbances and noises are common sources of uncertainties, it can be concluded that from the aspect of fuzzy implementation this system is highly resistant to noise and disturbance [38,39,40]. The fuzzy membership functions for the input linguistic variables, as well as the output linguistic variable are given in Figure 6.…”

Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD

“…The determination of the subjective weight is based on the opinion of experts or expert groups representing the views of various stakeholders. These are such methods as the direct ranking method (DR) (Goodwin & Wright, 1998;Roberts & Goodwin, 2002;Von Winterfeldt & Edwards, 1986), the point allocation (PA) method (Doyle et al, 1997;Roberts & Goodwin, 2002), the ranking method (Ahn & Park, 2008;Barron, 1992Barron, , 1996Roberts & Goodwin, 2002;Solymosi & Dombi, 1986;Milosevic et al, 2021), methods of programming (Pekelman & Sen, 1974;Shirland et al, 2003;Deng et al, 2004), Delphi method (Hwang & Yoon, 1981), pair-wise comparison (AHP) (Saaty, 1980;Takeda et al, 1987), step-wise weight assessment ratio analysis (SWARA) (Kersuliene et al, 2010), full consistency method (FUCOM) (Pamučar et al, 2018;Pamucar & Ecer, 2020), Level Based Weight Assessment (LBWA) (Žižović & Pamucar, 2019). One of the important problems of subjective methods is an assessment of the consistency of expert opinions.…”