Fuzzy Information and Engineering

Agarwal, Pallavi; Sharma, Ajay; Kumar, Neeraj

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.1915457

Genetic Algorithm (GA) is an optimized method to find a perfect solution which is based on general genetic process of life cycle. In this article we discussed a crisp and a fuzzy inventory model keeping its demand rate constant for the imprecision and uncertainly deteriorating items with special reference to shortage and partially backlogging systems. The objective of this paper is to minimize the total cost of fuzzy inventory environment for which Graded mean representation, Signed distance and Centroid methods are used to defuzzify the total cost of the systems. Consequently, we are comparing the total average cost, obtained through these methods with the help of numerical example, and sensitively analysis is also given to show the effects of the values on these items. Moreover, Genetic Algorithm (GA) is also applied to the optimistic value of the total cost of the crisp model for the effective and fruitful results.

Emam, E. G.

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.1947944

In this paper, we discuss in detail several properties of two kinds of intuitionistic fuzzy matrices which they are consistent and weak transitive. The nilpotent and transitive intuitionistic fuzzy matrices play an important role in this discussion. We show that our two kinds of matrices are controllable. We give a formula for the canonical form of a weak transitive intuitionistic fuzzy matrix. Our results are completely by counter examples to clarify it.

Forouzandeh, Saman; Rostami, Mehrdad; Berahmand, Kamal

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.2019430

Recommender systems have been pervasively applied as a technique of suggesting travel recommendations to tourists. Actually, recommendation systems significantly contribute to the decision-making process of tourists. A new approach of recommendation systems in the tourism industry by a combination of the Artificial Bee Colony (ABC) algorithm and Fuzzy TOPSIS is proposed in the present paper. A multi-criteria decision-making method called the Techniques for Order of Preference by Similarity to Ideal Solution (TOPSIS) has been applied for the purpose of optimizing the system. Data were gathered through a 1015 online questionnaire on the Facebook social media site. In the first stage, the TOPSIS model defines a positive ideal solution in the form of a matrix with four columns, which indicates factors that get involved in this study. In the second stage, the ABC algorithm starts to search amongst destinations and recommends the best tourist spot to users.

Kamil, Farah; Moghrabiah, Mohammed Yasser

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.2019432

The investigation into mobile robot navigation under uncertain dynamic environments is of great significance. This paper seeks to solve the current problems which are the difficulty to plan in indeterminate ever-changing environments, the problem of optimality, failure in complex situations, and the problem of predicting the obstacle velocity vector. The objective of this study is to propose a multilayer decision-based fuzzy logic model to find the solution for robot navigation through a safe path while preventing any types of barriers and to understand the non-collision mobile robots’ movement in an unknown dynamic environment. In this study, the prediction and priority rules of a multilayer decision are used by the fuzzy logic controller to improve the quality of the next position with regard to its path length, safety, and runtime. The results of comparison studies revealed a considerable improvement in failure rate and path length. Outcomes show that the suggested method displays attractive features, for instance, great stability, great optimality, zero failure rates, and low running time. The average path length for all test environments is 13.11 with 0.47 a standard deviation that provides 89% of an average optimality rate. The average running time is about 5.31 s with a 0.25 standard deviation.

Niksirat, Malihe

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.2019434

One of the most important problems in network design applications is the hub location problem, which is an extension of the facility location problem. The purpose of the problem is to select the least hub nodes from the available nodes so by establishing faster connections between hub nodes, the cost of transferring the entire network traffic is minimised. To deal with uncertainty and hesitation, the traffic amount between origin and destination nodes, the transfer cost, and the cost of establishing hub nodes are considered to be trapezoidal intuitionistic fuzzy numbers. The problem is formulated, and a new approach and a linearisation technique are shown to transform the Intuitionistic Fuzzy Hub Location Problem into a classical one. The transformed problem is solved using integer linear programming algorithms. The feasibility and efficiency of the obtained solutions applied to some airline passenger distribution problem applications are illustrated.

Jangid, Vinod; Kumar, Ganesh

2022 Fuzzy Information and Engineering

doi: 10.1080/16168658.2021.2019969

With the help of various different representations of a hexadecagonal fuzzy number, this paper investigates the uncertainty associated with ambiguity and imprecision in the results of 16-component game scenarios. Numerous membership functions for alpha-cuts are established in terms of symmetrical and asymmetrical situations. We look at the centroid methodology, as well as the mean of the alpha-cut technique, the mean of the bounded area removal method and the bounded area included by the fuzzy number. A new centroid-based technique is used to rank two hexadecagonal fuzzy numbers. Defuzzification approaches have also been used to numerical examples based on fuzzy game theory in order to illustrate the effectiveness of the techniques.