An Efficient Ranking Analysis In Multi-Criteria Decision Making

This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods

A review on path planning and obstacle avoidance algorithms for autonomous mobile robots

Mobile robots have been widely used in various sectors in the last decade. A mobile robot could autonomously navigate in any environment, both static and dynamic. As a result, researchers in the robotics field have offered a variety of techniques. This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). Classical approaches have limitations of trapping in local minima, failure to handle uncertainty, and many more. On the other hand, it is observed that heuristic approaches can solve most real-world problems and perform well after some modification and hybridization with classical techniques. As a result, many methods have been established worldwide for the path planning strategy for mobile robots. The most often utilized approaches, on the other hand, are offered below for further study

A review: On path planning optimization criteria and mobile robot navigation

Mobile robots are growing more significant from time to time and have been applied to many fields such as agriculture, space, and even human life. It could improve mobile robot navigation efficiency, ensure path planning safety and smoothness, minimize time execution, etc. The main focus of mobile robots is to have the most optimal functions. An intelligent mobile robot is required to travel autonomously in various environments, static and dynamic. This paper article presents the optimization criteria for mobile robot path planning to figure out the most optimal mobile robot criteria to fulfill, including modeling analysis, path planning and implementation. Path length and path smoothness are the most parameters used in optimization in mobile robot path planning. Based on path planning, the mobile robot navigation is divided into three categories: global navigation, local navigation and personal navigation. Then, we review each category and finally summarize the categories in a map and discuss the future research strategies

A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods

More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary gam

A review of game theory and multi-criteria decision-making methods with 10 application to the oil production and price

The oil production and price issues have been discovered a long time ago, and always be a continuous problem to the globe especially during the current global threats of the coronavirus pandemic. This paper provides a literature review that involves game theory and multi-criteria decision-making (MCDM) methods with its applications to oil production and price problems. This paper identifies and analyses the use of the game theory and MCDM methods on oil production and price to compare the situation studied, to determine the model that has been used, the trend of past literature and also the details of the basic elements for the game theory framework. Therefore, the oil production and price problem using the game theory and MCDM methods are reviewed and numerous applications studied from the past works of literature are highlighted. The trend of oil production and price which used the game theory and MCDM methods based on the year 2001 till 2021 is still lacking sources from the Web of Science and Scopus databases. The main contribution of the recent study is the employment of the game theory and MCDM methods to the oil production and price problem

A shapley trade-off ranking method for multi-criteria decision-making with defuzzification characteristic function

More studies tend to hybrid the game theory technique with the MCDM method to cater to real-situation problems. This paper provides a novel hybrid Shapley value solution concept in the cooperative game with the trade-off ranking method in MCDM. The fundamental methodology of the Shapley value solution concept and trade-off ranking method are explained to make the methodology clear to the readers. A Shapley trade-off ranking (S-TOR) method has been proposed to obtain the best solution to the fuzzy conflicting MCDM in the personnel selection problem. Thus, the triangular fuzzy number is used to represent the DMs evaluation. Then, the fuzzy number be transformed into crisp values using the defuzzification process. The future suggestions are the fuzzy system may be changed to real data for more practical problems, attempt to incorporate a comprehensive method to increase sharing-profit and decrease sharing-loss in the economy or financial problems, and other types of fuzzy numbers may be used to represent an evaluation of the DMs

A study of vehicle routing problem via trade-off ranking method

Vehicle routing defines selecting the minimum cost, distance, and/or time path from a depot to several alternatives for a goods or service to reach its destination. The objective of most routing problem is to minimize the total cost of providing the service. But other objectives also may come into play, particularly in the public sector. For emergency services, such as ambulance, police, and fire engine, minimizing the response time to an incident is of primary importance. A few routing algorithms do not use a deterministic algorithm to find the "best" route for a goods to get from its original source to its destination. Instead, to avoid congestion, a few algorithms use a randomized algorithm that routes a path to a randomly picked intermediate destination, and from there to its true destination. In this paper, the trade-off ranking method is used to solve for the vehicle routing treated as a conflicting multi-criteria problem. The integration of the trade-off ranking method into the vehicle routing problem gives another perspective on how to solve the problem, hence broadened the decision support system for the vehicle routing problem

Arithmetic operations of intuitionistic Z numbers using horizontal membership functions

An intuitionistic Z-number (IZN) is an integration of an intuitionistic fuzzy number with a Z-number. The IZN composes of two components; restriction and reliability components, which are represented by the membership and non-membership degrees to indicate the hesitancy. The objective of this paper is to propose new arithmetic operations of IZN using the horizontal membership functions, which are closely related the concept of the relative distance measure. For that reason, the addition, subtraction, multiplication and division on normal trapezoidal IZNs are considered. The proposed operations preserve the arithmetic operations over real numbers and the original IZN-based information, avoiding any significant loss of information. The implementation of the bandwidth method in deriving the operations has reduced the computational complexity on IZN. In the future, aggregation operators of IZN can be derived using the proposed arithmetic operations

Synergic ranking of fuzzy Z-numbers based on vectorial distance and spread for application in decision-making

Decision science has a wide range of applications in daily life. Decision information is usually incomplete and partially reliable. In the fuzzy set theory, Z-numbers are introduced to handle this situation because they contain the restriction and reliability components, which complement the impaired information. The ranking of Z-numbers is a challenging task since they are composed of pairs of fuzzy numbers. In this research, the vectorial distance and spread of Z-numbers were proposed synergically, in which the vectorial distance measures how much the fuzzy numbers are apart from the origin, which was set as a relative point, and their spreads over a horizontal axis. Furthermore, a ranking method based on the convex compound was proposed to combine the restriction and reliability components of Z-numbers. The proposed ranking method was validated using several empirical examples and a comparative analysis was conducted. The application of the proposed ranking method in decision-making was illustrated via the development of the Analytic Hierarchy Process-Weighted Aggregated Sum Product Assessment (AHP-WASPAS) model to solve the prioritization of public services for the implementation of Industry 4.0 tools. Sensitivity analysis was also conducted to evaluate the performance of the proposed model and the results showed that the proposed model has improved its consistency from 66.67% of the existing model to 83.33%. This research leads to a future direction of the application of ranking based on the vectorial distance and spread in multi-criteria decision-making methods, which use Z-numbers as linguistic values

Application of Intuitionistic Z-Numbers in Supplier Selection

Intuitionistic fuzzy numbers incorporate the membership and nonmembership degrees. In contrast, Z-numbers consist of restriction components, with the existence of a reliability component describing the degree of certainty for the restriction. The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers, namely intuitionistic Z-numbers (IZN). The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are characterized by the membership and non-membership functions, exhibiting the degree of the hesitancy of decision-makers. This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems. A decision-making model is proposed using the trapezoidal intuitionistic fuzzy power ordered weighted average as the aggregation function and the ranking function to rank the alternatives. The proposed model is then implemented in a supplier selection problem. The obtained ranking is compared to the existing models based on Znumbers. The results show that the ranking order is slightly different from the existing models. Sensitivity analysis is performed to validate the obtained ranking. The sensitivity analysis result shows that the best supplier is obtained using the proposed model with 80% to 100% consistency despite the drastic change of criteria weights. Intuitionistic Z-numbers play a very important role in describing the uncertainty in the decision makers’ opinions in solving decision-making problems