A REVIEW OF APPLICATIONS OF MULTIPLE - CRITERIA DECISION-MAKING TECHNIQUES TO FISHERIES

Management of public resources, such as fisheries, is a complex task. Society, in general, has a number of goals that it hopes to achieve from the use of public resources. These include conservation, economic, and social objectives. However, these objectives often conflict, due to the varying opinions of the many stakeholders. It would appear that the techniques available in the field of multiple-criteria decision-making (MCDM) are well suited to the analysis and determination of fisheries management regimes. However, to date, relatively few publications exist using such MCDM methods compared to other applicational fields, such as forestry, agriculture, and finance. This paper reviews MCDM applied to fishery management by providing an overview of the research published to date. Conclusions are drawn regarding the success and applicability of these techniques to analyzing fisheries management problems.Resource /Energy Economics and Policy,

A holistic multi-methodology for sustainable renovation

A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in building renovation regarding cultural changes and technological/physical changes. The outcome is a proposal for a multi-methodology framework, which is developed by introducing, evaluating and mixing methods from Soft Systems Methodologies (SSM) with Multiple Criteria Decision Making (MCDM). The potential of applying the proposed methodology in renovation projects is demonstrated through a case study

AN INTERVAL TYPE 2 FUZZY EVIDENTIAL REASONING APPROACH TO PERSONNEL RECRUITMENT

Recruitment process is a procedure of selecting an ideal candidate amongst different applicants who suit the qualifications required by the given institution in the best way. Due to the multi criteria nature of the recruitment process, it involves contradictory, numerous and incommensurable criteria that are based on quantitative and qualitative measurements. Quantitative criteria evaluation are not always dependent on the judgement of the expert, they are expressed in either monetary terms or engineering measurements, meanwhile qualitative criteria evaluation depend on the subjective judgement of the decision maker, human evaluation which is often characterized with subjectivity and uncertainties in decision making. Given the uncertain, ambiguous, and vague nature of recruitment process there is need for an applicable methodology that could resolve various inherent uncertainties of human evaluation during the decision making process. This work thus proposes an interval type 2 fuzzy evidential reasoning approach to recruitment process. The approach is in three phases; in the first phase in order to capture word uncertainty an interval type 2(IT2) fuzzy set Hao and Mendel Approach (HMA) is proposed to model the qualification requirement for recruitment process. This approach will cater for both intra and inter uncertainty in decision makers’judgments and demonstrates agreements by all subjects (decision makers) for the regular overlap of subject data intervals and the manner in which data intervals are collectively classified into their respective footprint of uncertainty. In the second phase the Intervaltype 2 fuzzy Analytical hierarchical process was employed as the weighting model to determine the weight of each criterion gotten from the decision makers. In the third phase the interval type 2 fuzzy was hybridized with the ranking evidential reasoning algorithm to evaluate each applicant to determine their final score in order to choose the most ideal candidate for recruitment.The implementation tool for phase two and three is Java programming language. Application of this proposed approach in recruitment process will resolve both intra and inter uncertainty in decision maker’s judgement and give room for consistent ranking even in place of incomplete requirement

AHP Model for Selection of Sustainable Energy: A Focus on Power Generation and Supplying for End-users

AHP is one of important technology management tools for decision making that is used during technology selection process, and applied prior to acquisition of a new technology. In the last decade, AHP was discussed by numerous studies, covering wide-variety of areas, focusing on many criteria and sub-criteria, for the purposes of selecting, allocating, evaluating, or benchmarking different alternatives of technology. The use of AHP for selecting the source of renewable energy as the alternative for the non-renewable source of energy is important, especially to the environmental conscious’ end-users, or those who are living in the rural area. However, in the field of sustainable energy, AHP application for power generation focusing on the end-users is still limited. As a result, this study aims to develop an AHP model, by investigating the suitable group of criteria, sub-criteria, and alternatives that will suit the needs of the end-users. This model will helps the relevant parties to identify the most suitable sources of technology for power generation to solve the end-users’ needs. To do this, secondary data were collected from the relevant empirical studies. Based on the descriptive analysis, it was found that the previous studies have ranked and prioritized each of these criteria, sub-criteria, and alternatives differently, which implies a specific AHP model for the end-users should be developed. With the findings, this study has developed an AHP model comprising of four major criteria, each with three sub-criteria, and five alternatives. This model is being verified by an ongoing research in Malaysia

Energy Planning using "Web-HIPRE" software

This Report is focusing on understanding Multi Criteria Decision Making. Most decision making reqmres the consideration of several conflicting objects the term multiple criteria decision making (MCDM) describes various methods for aiding decisions makers in reaching better decisions. The techniques provide solutions to the problem involving conflicting and multiple objectives. The aim of MCDM method is to help decision makers to organize and synthesize the information they have collected so that they feel comfortable and confident in their decisions. This project is to select the best and most suitable Energy planning/Power Plants using the Multi-Criteria Decision Making (MCDM) methods to come out with the best alternative. For every problem all the related factors regarding the discussed issue should be considered during the selection process. The aid of specialized software is being used to facilitate the decision making and to simulate the MCDM methods

Optimizing Biomass Pre-Treatment Technologies for BBJP Plants in Indonesia: A Multi-Criteria Decision Making Approach

The challenges of energy consumption and environmental sustainability are pronounced in the dynamic landscape of contemporary industries driven by Industry 4.0 technologies. Indonesia, heavily reliant on fossil fuels, charts a course toward a clean energy future with a National Energy Transition Roadmap for Net Zero Emission by 2060. This transition involves innovative strategies such as biomass co-firing and waste utilization in Solid Recovered Fuel (SRF) plants, known as Bahan Bakar Jumputan Padat (BBJP) plants. To optimize these BBJP plants, this study employs Multi-Criteria Decision Making (MCDM) methodologies, specifically the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to evaluate and select pre-treatment technologies. Criteria include capacity, conversion process, waste type, electricity consumption, operational ease, land requirement, and investment cost. Comparing bio-drying, thermal drying, and mechanical drying, AHP ensures consistent criterion weights, with TOPSIS ranking bio-drying as the most favorable, followed by thermal and mechanical drying. The study acknowledges global waste management challenges and introduces a mobile-modular containerized BBJP/SRF plant model, addressing installation, maintenance, scalability, and adaptability issues. While recognizing challenges, especially in pre-treatment processes, the research emphasizes the need for efficient and cost-effective solutions. Practical implications include enhanced decision-making in biomass drying, identification of technology advantages and disadvantages, and a commitment to address challenges for sustainable implementation. The study contributes to Indonesia's energy transition discourse, advocating the pivotal role of BBJP plants in balancing Industry 4.0 demands and environmental protection, providing insights for stakeholders and decision-makers in advancing sustainable waste-to-energy initiatives

Decision support for information systems management : applying analytic hierarchy process

Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision making. AHP can be applied if the decision problem includes multiple objectives, conflicting criteria, incommensurable units, and aims at selecting an alternative from a known set of alternatives. An AHP analysis is described by using the project selection decision as an example. The strengths and weaknesses of AHP are investigated based on a set of eight criteria for evaluating I/S decision support methods. This evaluation shows that AHP scores well on most criteria. Given this promising performance, other possible applications of AHP within the I/S function are listed.

Combining Multi-Criteria Decision Making (MCDM) Methods with Building Information Modelling (BIM): A Review

Integrating building information to support decision-making has been a key challenge in the Architecture, Engineering, and Construction (AEC) industry. The synergy of Building Information Modelling (BIM) and Multi-Criteria Decision Making (MCDM) is expected to improve information integration and decision-making. The aim of this paper is to identify strategies to improve the synergy between MCDM and BIM. From the earliest literature (2009) to the present, this study examines 45 articles combining MCDM with BIM. We find that the five major application domains are sustainability, retrofit, supplier selection, safety, and constructability. Five established strategies for improving the synergy between MCDM and BIM were discussed and can be used as a benchmark for evaluating the application of decision techniques in practice. This study points out gaps of combining MCDM and BIM in the current literature. It also sheds new light into combining MCDM with BIM for practitioners, as to promote integrated decision-making

A Comparative Analysis of TOPSIS & VIKOR Methods in the Selection of Industrial Robots

Now-a-days robots are very essential in manufacturing industries for the optimization of their production. So selection of an industrial robot for a particular application is one of the most vital problems in real time manufacturing environment. The decision maker needs to choose the most suitable and applicable industrial robot in order to get the required output with minimum cost and having the specific abilities. This paper mainly focuses to compare the different multiple criteria decision making (MCDM) methods such as TOPSIS and VIKOR Method for selection of alternative industrial robots. Both the methods are based on an aggregating function that represents closeness to the ideal solution. VIKOR method is based on linear normalization whereas TOPSIS method used vector normalization to eliminate the units of criterion functions. A solution obtained by TOPSIS method has the shortest distance from the ideal one and farthest from the negative ideal solution. VIKOR method helps to determine a compromise solution that gives a maximum group utility for the majority and minimum for opponents