A Fuzzy-based Framework to Support Multicriteria Design of Mechatronic Systems

Designing a mechatronic system is a complex task since it deals with a high number of system components with multi-disciplinary nature in the presence of interacting design objectives. Currently, the sequential design is widely used by designers in industries that deal with different domains and their corresponding design objectives separately leading to a functional but not necessarily an optimal result. Consequently, the need for a systematic and multi-objective design methodology arises. A new conceptual design approach based on a multi-criteria profile for mechatronic systems has been previously presented by the authors which uses a series of nonlinear fuzzy-based aggregation functions to facilitate decision-making for design evaluation in the presence of interacting criteria. Choquet fuzzy integrals are one of the most expressive and reliable preference models used in decision theory for multicriteria decision making. They perform a weighted aggregation by the means of fuzzy measures assigning a weight to any coalition of criteria. This enables the designers to model importance and also interactions among criteria thus covering an important range of possible decision outcomes. However, specification of the fuzzy measures involves many parameters and is very difficult when only relying on the designer's intuition. In this paper, we discuss three different methods of fuzzy measure identification tailored for a mechatronic design process and exemplified by a case study of designing a vision-guided quadrotor drone. The results obtained from each method are discussed in the end

A Spatial Fuzzy Compromise Approach for Flood Disaster Management

Natural disasters affect regions with different intensity and produce damages that vary in space. Topographical features of the region; location of properties that may be exposed to the peril; level of exposure; impact of different mitigation measures; are all variables with considerable spatial variability. A new method for evaluation of disaster impacts has been presented in this report that takes into consideration spatial variability of variables involved and associated uncertainty. Flood management has been used to illustrate the utility of proposed approach. Floodplain management is a spatial problem. Representation of flood damage mitigation alternatives and objectives in space provides a better insight into the management problem and its characteristics. Protection of a region from floods can be achieved through various structural and non-structural measures. Comparison of different measures and evaluation of their impacts is based on the multiple criteria. If they are described spatially, decision-making problem can be conceptualized as spatial multi criteria decision-making (MCDM). Tkach and Simonovic (1997) introduced spatial Compromise Programming (SPC) technique to account for spatial variability in flood management. Some of the criteria and preferences of the stakeholders involved with flood management are subject to uncertainty that may originate in the data, knowledge of the domain or our ability to adequately describe the decision problem. The main characteristic of flood management is the existence of objective and subjective uncertainty. Fuzzy set theory has been successfully used to address both, objective and subjective uncertainty. Bender and Simonovic (2000) incorporated vagueness and imprecision as sources of uncertainty into multi criteria decision-making in water resources. In this report a new technique named Spatial Fuzzy Compromise Programming (SFCP) has been developed to enhance our ability to address the issues related to uncertainties in spatial environment. A general fuzzy compromise programming technique, when made 2 spatially distributed, proved to be a powerful and flexible addition to the list of techniques available for decision making where multiple criteria are used to judge multiple alternatives. All uncertain variables (subjective and objective) are modeled by way of fuzzy sets. In the present study, fuzzy measures have been introduced to spatial multi criteria decision-making in the GIS environment in order to account for uncertainties. Through a case study of the Red River floodplain near the City of St. Adolphe in Manitoba, Canada, it has been illustrated that the new technique provides measurable improvement in flood management. Final results in the form of maps that shown spatial distribution of the impacts of mitigation measures on the region can be of great value to insurance industry.https://ir.lib.uwo.ca/wrrr/1004/thumbnail.jp

Development of Fuzzy Multi Criteria Decision Making Method for Selection of Optimum Maintenance Alternative

An optimal maintenance strategy is a key support to production in the manufacturing industry. This paper present a fuzzy approach based on Multi-Criteria Decision-Making (MCDM) methodology for selecting the optimal maintenance alternative. In the present work the criticality of each equipment is achieved by ranking (based on production loss).It is very difficult to quantify the qualitative factors in exact numerical value. These factors can be expressed in the linguistics terms which can be translated into mathematical measures by using fuzzy sets & system theory. The study problem to develop a fuzzy decision approach to rank the suitable maintenance alternative. The objective of this paper is to propose fuzzy frame work based on fuzzy number theory to solve optimal maintenance alternative which includes decision criteria analysis, weight assessment & decision model development. The approach can aid formulating a cost-effective maintenance strategy for a manufacturing plant

A multi criteria group decision making approach based on fuzzy measure theory to assess the different gene regions used in rodent species

Many mitochondrial and nuclear gene regions are used in phylogenetic and taxonomic studies to investigate the historical background of the species and to present the hierarchy of the species. In this paper, we consider the problem of proposing a favorable gene region that determines the diversification of rodent species as a multi criteria group decision making problem. We use fuzzy measure theory and fuzzy integrals to get the results. We conclude with different fuzzy measures and fuzzy integral techniques that COI gene region which is preferred in animal barcoding studies is more favorable.Publisher's Versio

A FUZZY DECISION MAKING APPROACH IN EVALUATING FERRY SERVICE QUALITY

The service quality evaluation is undeniably important especially in highly competitive service related industry. However, service quality evaluation is not always straightforward as criteria in evaluation and customer perceptions toward services are intangible measures. This paper presents a fuzzy multi-criteria decision making approach for evaluating the service quality of ferry that transport customers between the mainland of Peninsular Malaysia and a tourist spot island. Service quality is a composite of various criteria, among them many criteria are intangible and difficult to measure. Fuzzy numbers and linguistic level based on fuzzy sets theory as a method to overcome vaguely judgment in evaluation. The crisp survey results were collected via a ten-service criteria questionnaire from eighty seven customers and computed using Best non-Fuzzy Performance and Degree of Similarity. Based on the concept of the defuzzification, the ranking of service performance is obtained. Degree of Similarity provides the level of satisfaction and its degrees for each criterion. The criterion of ‘service efficiency of ferry personnel’ was the first in the ranking. All the criteria received ‘good’ and ‘very good’ for the level of satisfaction. These evaluation results facilitate the ferry operator to upgrade its ferry services and eventually meet its customers’ needs.Service quality, fuzzy number, satisfaction level, defuzzification.

NEW DISSIMILARITY MEASURES ON PICTURE FUZZY SETS AND APPLICATIONS

The dissimilarity measures between fuzzy sets/intuitionistic fuzzy sets/picture fuzzy sets are studied and applied in various matters. In this paper, we propose some new dissimilarity measures on picture fuzzy sets. This new dissimilarity measures overcome the restrictions of all existing dissimilarity measures on picture fuzzy sets. After that, we apply these new measures to the pattern recognition problems. Finally, we introduce a multi-criteria decision making (MCDM) method that used the new dissimilarity measures and apply them in the supplier selection problems

Some New Correlation Coefficient Measures Based on Fermatean Fuzzy Sets using Decision Making Approach in Pattern Analysis and Supplier Selection

Fermatean fuzzy set (FFS) is an effective tool to depict expert reasoning information in the decision‐making process than fuzzy sets (FS), intuitionistic fuzzy sets (IFS), and Pythagorean fuzzy sets (PFS). Keeping in mind the importance of correlation coefficient and application in medical diagnosis, decision making and pattern recognition, several studies on correlation coefficient measures have been proposed in the literature. As there does not exist any study concerning correlation coefficient measures for FFS, in this communication, we propose novel entropy-correlation measures for Fermatean fuzzy sets and applied it decision making problems of pattern analysis and multi-criteria decision making for supplier selection. With the help of proposed correlation coefficient, we establish some weighted measures for FFS. Using numerical computations, we determine the efficacy of the suggested measures over other measures. The aim of this study is to propose a novel and efficient methodology for evaluation of supplier’s selection with uncertain information. Finally, we establish the comparative study of our developed measures over the existing correlation coefficient measures. The analysis showed that the suggested methodology is reliable, flexible, and consistent with the existing techniques

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure

An application of fuzzy-AHP to ship operational energy efficiency measures

Lowering fuel consumption of ships has gained a great deal of attention in maritime industry with regards to both environmental and economic concerns. The potential for fuel economy in shipping ranging between 25% to 75% is possible by using existing technology and practices and technical improvements in the design of new ship. Despite the existence of many technology and design-based approaches, limitations of emerging these measures has led to discussions about the potential energy savings through operational changes. In this study, operational measures were examined within the scope of Ship Energy Efficiency Management Plan (SEEMP) adopted by International Maritime Organization (IMO). We applied the Analytic Hierarchy Process (Fuzzy-AHP) approach, one of multi-criteria decision making (MCDM) techniques, to prioritize the weight of each measure. Fuzzy AHP effectively reflects the vagueness of human thinking with interval values, and shows the relative importance of operational measures - which can be the fundamental decision making data for decision makers (ships' masters, operating companies and ship owners) - by providing a strategic approach to identify energy efficient solutions