Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration

electromagnetism-like mechanism (em) algorithm, a meta-heuristic algorithm for global optimisation, utilises an attraction-repulsion mechanism to move the sample points towards the optimality. the original em has a strong ability for diversification. and a simple random line search algorithm for local search has been added to improve its intensification. however, it plays a quite limited role and the performance of the original em is not satisfactory. therefore, in this paper, a modified solis and wets local search is proposed to improve the performance of em. two self-adapt parameters are introduced into solis and wets local search. in addition, an accelerated force formula is adopted for high-dimensional function optimisation. some benchmark test problems have been used to evaluate the proposed-algorithm. results obtained are compared with those from other algorithms including original em algorithm and all kinds of particle swarm optimisation methods. the comparisons show that the novel em has achieved significant improvement.

A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem: A case study

This paper discusses selection of construction projects based on multiple criteria using a quantitative fuzzy-set method, which considers multiple attributes in a decision-making process involving a group of decision makers. This approach implements a modified fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to help decision makers rank projects based on various attributes. A triangular fuzzy set models linguistic terms used to provide subjective judgment related to decision makers' experience level, attribute weight assessment, and attribute rating. The fuzzy TOPSIS method is extended in this research to capture various levels of experience for decision makers involved in a decision to select a construction project. An illustrative example of project selection using the proposed method is provided to demonstrate its effectiveness. The computational results of this research provide project stakeholders with a computer model that could be implemented to assist in the construction project bid or not bid decision and provide a ranking of different projects to bid on. Furthermore, the results of this study show that the proposed method is suitable for modeling the uncertainty associated with project selection. The bid/no bid project selection model presented in this study is based on a set of common attributes; the selection of attributes that contribute toward the project bid or not bid decision can be different based on construction project conditions. The proposed method is suitable for construction type projects, but the methodology used in the study can be implemented for any type of project and is not limited to a specific geographic area. The proposed computer model is limited to handling input from up to 10 decision makers with varying degrees of experience. Another limitation of the computer model introduced in this study is that contractors can consider up to five different projects for bid purposes.

Recycling is the process of collecting and reusing that helps the countries to achieve their sustainable development goals. This study, for the first time in the literature, considers the recycling of many daily consumption products as a decision-making problem with the q-rung orthopair fuzzy (q-ROF) approach. In Turkey, recycling initiatives are primarily led by the government and municipalities, involving either reprocessing in public facilities or collaboration with private enterprises. The research evaluates the effectiveness of recycling strategies, considering paper, plastic, textiles, batteries, frying oils, electronics, glass, and wood as alternative products. Criteria such as convertibility rate, resource usage for recycling, converted product lifespan, recycling process complexity, economic gain, product consumption rate, and trading opportunities are employed in the decision-making process. The q-rung orthopair fuzzy Technique for Order Preference by Similarity to Ideal Solution (q-ROFTOPSIS) method is applied to assess these criteria. Decision makers, comprising a recycling expert, a recycling business engineer, and an academician specializing in recycling studies, contribute to the evaluation. The study reveals electronic products as the most successful in recycling, while frying oils exhibit the least success.

Universities carry a central responsibility in student well-being, as there has been a troubling increase in the number of university students experiencing mental health challenges, ranging from anxiety and depression to emotional distress. This growing concern highlights the urgent need for universities to identify and implement effective mental health intervention programs. In this study, selecting a mental health program is viewed as a multi-criteria decision-making (MCDM) problem and analyzed using the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). The study involved six experts from the Psychology and Counseling Unit at UiTM Cawangan Kelantan, who evaluated four intervention alternatives: counseling and therapy services, physical activities, peer support groups, and online mental health resources. In addition, five key criteria were considered: accessibility, effectiveness, cost-efficiency, flexibility, and privacy. The findings demonstrate that counseling and therapy services are ranked as the most effective mental health intervention programs based on expert evaluation. Therefore, universities must focus on interventions that enhance students’ psychological well-being and emotional resilience.

Bioenergy production from biomass is a multicriteria decision-making (MCDM) problem involving multidimensional criteria due to the vast range of resources available for consideration. In this paper, we propose a hybrid fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) and analytical hierarchy process (AHP) that is able to tackle vagueness and ambiguity in data and produce weights for all criteria in the MCDM problem. By utilizing this methodology, different aspects of experts’ data evaluation including fuzzy values can be converted into crisp values. Accuracy in each decision matrix is ensured by determining the weights of the subcriteria. We then apply the model to sustainable biomass resource selection in Ghana. Specifically, we comprehensively review the sustainable criteria within the bioenergy domain namely social, environmental, and economic aspects together with thirteen subcriteria. The proposed model was applied to biomass resource alternatives including crop residue, animal manure, forest residue, energy crops, and municipal solid waste. Results show the weights of thirteen subcriteria to be within the range of 0.10340 and 0.05263. The FTOPSIS shows that animal manure may be the most desirable resource for bioenergy production in Ghana, followed by energy crop, municipal solid waste, forest residue, and crop residue, respectively. Engineering and energy planning problems with conflicting multicriteria data can be easily solved by using this proposed hybrid AHP/FTOPSIS framework.

Facility location selection is a multi-criteria decision problem and has a strategic importance for many companies. The aim of this study is to propose a fuzzy approach for facility location selection. This paper is based on a fuzzy extension of the technique for order preference by similarity to ideal solution (TOPSIS) method. In this method, the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic variables represented by fuzzy numbers. Fuzzy numbers try to resolve the ambiguity of concepts that are associated with human being’s judgments. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). By using fuzzy TOPSIS, uncertainty and vagueness from subjective perception and the experiences of decision maker can be effectively represented and reached to a more effective decision. Key words: Fuzzy logic, multi-criteria decision making, fuzzy technique for order preference by similarity to ideal solution (TOPSIS), facility location selection.

SummaryNext generation wireless networks consist of many heterogeneous access technologies that should support various service types with different quality of service (QoS) constraints, as well as user, requirements and provider policies. Therefore, the need for network selection mechanisms that consider multiple factors must be addressed. In this paper, a network selection method is proposed by applying the analytic network process to estimate the weights of the selection criteria, as well as a fuzzy version of technique for order preference by similarity to ideal solution to perform the ranking of network alternatives. The method is applied to a heterogeneous network environment providing different QoS classes and policy characteristics. Each user applies the method to select the most appropriate network, which satisfies his or her requirements in respect of his or her service‐level agreement (SLA). Performance evaluation shows that when the user requests only one service, the proposed method performs better compared to the original technique for order preference by similarity to ideal solution, as well as the Fuzzy AHP‐ELECTRE method. Moreover, the proposed method can be applied in cases where a user requires multiple services simultaneously on a device. The sensitivity analysis of the proposed method shows that it can be properly adjusted to conform to network environment changes. Copyright © 2014 John Wiley & Sons, Ltd.

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

The Purpose research is to develop a new interval value fuzzy by integrating Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for multiple criteria group decision-making model (FMCGDM). The Interval Value Analytic Hierarchy Process (IVFAHP) approach is capable of elaborating complex multi-criteria problems into a hierarchical structure and determining the optimal weight in multi-criteria decision-making. In determining the best alternative, the Interval Value Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IVFTOPSIS) approach is well-suited for being able to make multi-decisions based on the alternative that has the shortest distance from the ideal solution positive and furthest from the ideal negative solution. The results study is a new framework Interval Value Fuzzy (AIVF) decision-making model with flexible linguistic preferences and a high degree of accuracy. The method is implemented in mapping strategy selection problem for measurement e-learning.

A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment

Facility location selection is a multi-criteria decision problem and has a strategic importance for many companies. The conventional methods for facility location selection are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use fuzzy analytic hierarchy process (AHP) and the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods for the selection of facility location. The proposed methods have been applied to a facility location selection problem of a textile company in Turkey. After determining the criteria that affect the facility location decisions, fuzzy AHP and fuzzy TOPSIS methods are applied to the problem and results are presented. The similarities and differences of two methods are also discussed.

The rapid and uncontrolled growth of the world's population technological developments, increase in the social welfare and the transformation of societies into consumer societies have changed the dimensions of environmental problems. Nowadays waste management has become an important issue for the solution of environmental problems. Hence, we discussed the municipal solid waste management. Municipal solid waste management problem is a complex and it has many different aspects as political, social, technological and economical criteria have to consider. The evaluation of these criteria numerically is complicated and vague. This paper deals with this complexity by proposed methodology. Also the contribution of the article to the literature is that the proposed methodology is applied for the first time in municipal solid waste management problems. In this paper, two fuzzy decision making approaches are combined for sitting a waste to energy plant in the Kırıkkale in Turkey. Four alternative locations and nine criteria are defined from the expert opinions and the literature survey. A new hybrid methodology that has not been applied before for this decision problem is proposed. In proposed methodology, there are two main stages. Criteria weights determination is the first stage, and ranking of the alternative locations is the second stage of the methodology. In first stage, Interval type 2 Fuzzy Analytic Hierarchy process method is performed and in the second stage hesitant fuzzy technique for order preference by similarity to an ideal solution method is used for ranking the alternative locations. Also decision makers have different experience level and knowledge about the problem and different decision makers’ weights are considered for group decision making. Two fuzzy methods are combined for the solid waste energy production plant location selection problem. As a result of the study, the second alternative (Bahsılı-Bedesten) is determined as the most suitable area for waste to energy production plant. Besides, with scenario analysis the effect of criteria on ranking of the alternatives is analyzed.

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.

The importance of dynamic multi-objective optimization problems (DMOPs) is on the rise, in complex systems. DMOPs have several objective functions and constraints that vary over time to be considered simultaneously. As a result, the Pareto optimal solutions (POS) and Pareto front (PF) will also vary with time. The desired algorithm should not only locate the optima but also track the moving optima efficiently. In this paper, we propose a new Cultural Algorithm (CA) based on decomposition (CA/D). The primary objective of the CA/D algorithm is to decompose DMOP into several scalar optimization subproblems and solve simultaneously. The subproblems are optimized utilizing the information shared only by its neighboring problems. The proposed CA/D is evaluated using CEC 2015 optimization benchmark functions. The results show that CA/D outperforms CA, Multi-population CA (MPCA), and MPCA incorporating game strategies (MPCA-GS), particularly in hybrid and composite benchmark problems.