Decision Support System Determination of Main Work Unit In WPP-711 Using Fuzzy TOPSIS

Decision-making to determine the working units for being prioritized to be developed in order to improve fishery monitoring in WPP-711 is imperative. The Ministry of Maritime Affairs and Fisheries should make no mismatch decision-making through long-term calculation and analysis. The problem of determining the priority of working units is a complex problem, thus it is required to find an appropriate method to avoid a missmatch decision. TOPSIS is a decision-making method capable of solving multi-criteria problems. TOPSIS working principle determines the alternative by considering the shortest distance from the positive ideal alternative and furthest from the ideal negative solution. To improve the performance of TOPSIS, this research is integrated with Fuzzy logic with the aim of giving the right numeric value preference. From the test of 11 alternatives of 6 criteria, the priority of development of fishery monitoring in FMA 711 is: Pontianak Working Unit= 0.917, Batam Working Unit = 0.791 Natuna Working Unit = 0.685 and Tanjung Pinang Working Unit = 0.607. Furthermore,  the ranking result will be used as the basis for determining the strategy in increasing the monitoring of WPP-711 to minimize State losses due to the illegal fishing within Indonesia’s WPP-711 Regions

Investigating car purchasing decision-making process using Multi- Objective Optimization Ratio Analysis based Analytical Hierarchy Process Model: An empirical case from Vietnam

This study aims to define and quantify the factors affecting selecting the best car among the market's available alternatives. Many criteria are involved while deciding to purchase the best car from various car models; therefore, car purchasing behaviour is a multi-criteria decision-making problem (MCDM). Proposed criteria are based on the customers’ survey when they are willing to purchase the cars, including Price, Branding, Safety, Performance, Exterior, Fuel efficiency, Maintainance cost, After-Sale Service, and Resale. In this study, the AHP technique calculates each criterion's weight, and then Multi-Objective Optimization Ratio Analysis (MOORA) is employed to rank the car models in a numerical example from Vietnam. The results show that this proposed model can minimize the consumer effort to select a car and make accurate decisions. Furthermore, this study's findings could provide car manufacturers with valuable insight into the criteria that reflect the customer's assessment of the car selection process. JEL: C02, C61, D53, Q1

Comparative analysis of stock selection using a hybrid MCDM approach and modern portfolio theory

The problem of selecting an optimal set of investment stocks is of a huge interest for both individual and institutional investors. This paper compares the hybrid multiple criteria decision making (MCDM) approach to selecting the best stock to invest in, with the stock selection using modern portfolio theory (MPT). When selecting stocks, it is very important to thoroughly analyse stocks, according to multiple criteria, including their equity market indicators, as well as financial indicators. The objective of the research is to compare the stock selection using a hybrid MCDM approach and MPT, which includes only the equity market indicators. The analysed sample includes 18 stocks, which are CROBEX components on the Croatian capital market from January 2017 to January 2019. The rankings of stocks were calculated using five MCDM methods. These were then used to obtain the final hybrid stock ranking, which was compared to the MPT stock selection. The results show that there is a significant difference in the stock rankings. However, the stocks which have not entered any portfolio in MPT selection were ranked as lowest according to the hybrid MCDM approach, which confirms that those stocks are the worst to invest in. The research can serve as a guidance for investors to use all available stock information in their decision making process of investment

Математические модели реализации концепции жестких бюджетных ограничений в бюджетной системе

 The subject of the study is the processes of budget decentralization in the management of public finances, as wellas mathematical methods and models for implementing the concept of hard budget restrictions in order to create conditions for the self-development of administrative-territorial units. The aim of the study is to develop adaptive economic and mathematical models for implementing the strategy of hard budget constraints implemented in the process  of inter-budget regulation. The relevance of the study is due to the fact that currently the subject of acute discussion in the scientific community is the self-development of administrative-territorial entities and increasing their financial independence. In this regard, the focus of economic research is focused on the problems of budgetary decentralization as an engine of economic development, as well as the related topics of the use of mathematical tools for modeling decision support in this area. The created models are subject to the requirements of learnability, adaptability to changing conditions of environmental influences, and the ability to operate not only with quantitative, but also with qualitatively defined characteristics. The problem of mathematical modeling is solved by applying an interdisciplinary synthesis of the theories of stochastic automata operating in random environments and fuzzy logic. The proposed synthesis of theoretical and methodological devices is the novelty of the research. As a result, an economic and mathematical model of a fuzzy automaton is constructed for determining and quantifying the values of the norms for the distribution of tax revenues between budgets of different levels of the budget system. A fuzzy automaton interacts with a simulation model that reproduces budget flows and quantifies the decisions made by the automaton model. The practical significance of the research results lies in the program implementation of the developed models and their inclusion in the public finance management circuit. In the future, it is planned to create a mathematical model of the collective behavior of fuzzy automata models, the interaction of which solves the problem of coordinating the interests of budgets of different levels of the hierarchy in the distribution of tax revenues.  Предметом исследования являются процессы бюджетной децентрализации при управлении общественными финансами, а также математические методы и модели реализации концепции жестких бюджетных ограничений с целью создания условий саморазвития административно-территориальных единиц. Цель исследования — разработка адаптивных экономико-математических моделей для осуществления стратегии жестких бюджетных ограничений, реализуемых в процессе межбюджетного регулирования.Актуальность исследования обусловлена тем, что в настоящее время в научном сообществе предметом острой дискуссии является саморазвитие административно-территориальных образований и повышение их финансовой самостоятельности. В этой связи фокус внимания экономических исследований сосредоточен на проблематике бюджетной децентрализации как двигателе экономического развития, а также связанной с ней тематике применения математического аппарата для моделирования поддержки принятия решений в этой сфере. К создаваемым моделям предъявляются требования обучаемости, адаптивности к изменяющимся условиям воздействий внешней среды и умения оперирования не только количественными, но и качественно определенными характеристиками. Поставленная проблема математического моделирования решается посредством применения междисциплинарного синтеза теорий стохастических автоматов, функционирующих в случайных средах, и нечеткой логики. Предлагаемый синтез теоретико-методологических аппаратов составляет новизну проведенных исследований. В результате построена экономико-математическая модель нечеткого автомата для определения и количественного обоснования величин нормативов распределения налоговых поступлений между бюджетами различных уровней бюджетной системы России. Нечеткий автомат в процессе функционирования взаимодействует с имитационной моделью, воспроизводящей бюджетные потоки и количественно оценивающей принимаемые автоматной моделью решения. Практическая значимость результатов исследования состоит в программной реализации разработанных моделей и их включении в контур управления общественными финансами. В перспективе предполагается создание математической модели коллективного поведения нечетких автоматных моделей, взаимодействие которых решает проблему согласования интересов бюджетов различных уровней иерархии при распределении налоговых доходов.

Location Planning of Urban Distribution Center under Uncertainty: A Case Study of Yogyakarta Special Region Province, Indonesia

Purpose: The paper aims at proposing a framework of hybrid spatial-fuzzy multi-criteria decision-making and demonstrating application of the framework to evaluate and select the appropriate location for Urban Distribution Center in Yogyakarta Special Region Province, Indonesia. The study has been inspired by the need to evaluate the Urban Distribution Center initiative, i.e., Jogja Inland Port by local government that has been hampered due to lack of participating companies. Design/methodology/approach: The proposed framework consists of two steps of analysis. First, spatial analysis to generate alternative locations using weighted Geographical Information System data; second, fuzzy multi-criteria decision-making to select the best location. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution was applied to deal with multi-criteria, multiple stakeholders, and uncertainty. Accessibility, security, connectivity of multi-modal transport, costs, environmental impact, proximity to customers, proximity to suppliers, resource availability, expansion possibility, service quality, are taken as the decision criteria. Local government of Yogyakarta province, practitioners, and logistic expert, are involved as representative participants in evaluating the Urban Distribution Center location of Yogyakarta Special Region Province. Findings: The proposed framework has indicated that the Jogja Inland Port is not the best alternative. A joint warehouse managed by a group of private companies located in Berbah (Sleman district) appears to be the best alternative location for Urban Distribution Center. Consistent results are also found by using other approaches (Intuitionistic Fuzzy Technique for Order Preference by Similarity to Ideal Solution and Set Pair Analysis). Research limitations/implications: In addition to the government, expert, and practitioners that involved in this study, future research could engage local residents as decision makers to refine the results, as various stakeholders may come up with different preferences. Practical implications: From a practical point of view, the application of combined approach (integrating spatial analysis using weighted Geographical Information System data and fuzzy multi-criteria decision making) is a promising approach in dealing with Urban Distribution Center location problem which is characterized by multi-criteria, multiple stakeholders, spatial-related issues, and uncertainty. Social implications: The unsuccessful establishment of Jogja Inland Port implies that Urban Distribution Center location problem is a complex system, involving multifaceted factors that should be considered simultaneously. Originality/value: The research proposes a framework to evaluate and select the appropriate location for Urban Distribution Center through combined approach of weighted Geographical Information System data and fuzzy multi-criteria decision-making which involves relevant stakeholders.Peer Reviewe

The integration of fuzzy delphi and fuzzy topsis for pharmaceutical waste treatment selection in the context of green practice

Pharmaceutical waste should be treated in the best possible manner to avoid harm toward public health and the environment. Thus, green practices can be adopted in treating the waste as effectively as possible. However, research about the best treatment with green features has only been conducted in other countries and cannot be a primary reference for Malaysia due to geographical differences. Practically, an approach to model holistic decision-making for pharmaceutical waste in Malaysia context and evaluate the robustness of the model is essential. Hence, this research develops a decision-making model to select the best treatment for pharmaceutical waste in the context of green practices in Malaysia. By using a systematic literature review and experts’ opinions, a comprehensive list of criteria, sub-criteria, and treatments were successfully collected. The computation of weights for criteria and sub-criteria as well as the ranking of treatments were analysed through Fuzzy Delphi TOPSIS. The results revealed that waste immobilisation (encapsulation) is selected as the best treatment and environmental is the most important criterion as evaluated by a panel of experts. The sensitivity analysis indicated that different combinations of criteria could influence the ranking of the treatments. The developed model contributes to the related stakeholders in waste management to assist the decision-making process. It also expands the knowledge of waste treatment in the perspective of green practices and it is argued to be a trustworthy mechanism to be implemented in Malaysia

An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies

To stay competitive in a business environment, continuous performance evaluation based on the triple bottom line standard of sustainability is necessary. There is a gap in addressing the computational expense caused by increased decision units due to increasing the performance evaluation indices to more accuracy in the evaluation. We successfully addressed these two gaps through (1) using principal component analysis (PCA) to cut the number of evaluation indices, and (2) since PCA itself has the problem of merely using the data distribution without considering the domain-related knowledge, we utilized Analytic Hierarchy Process (AHP) to rank the indices through the expert’s domain-related knowledge. We propose an integrated approach for sustainability performance assessment in qualitative and quantitative perspectives. Fourteen insurance companies were evaluated using eight economic, three environmental, and four social indices. The indices were ranked by expert judgment though an analytical hierarchy process as subjective weighting, and then principal component analysis as objective weighting was used to reduce the number of indices. The obtained principal components were then used as variables in the data envelopment analysis model. So, subjective and objective evaluations were integrated. Finally, for validating the results, Spearman and Kendall’s Tau correlation tests were used. The results show that Dana, Razi, and Dey had the best sustainability performance.This article belongs to the Special Issue Sustainability Assessmen

An extension of fuzzy TOPSIS for a group decision making with an application to Tehran stock exchange

In financial markets, investors attempt to maximize their profits within a constructed portfolio with the aim of optimizing the tradeoffs between risk and return across the many stocks. This requires proper handling of conflicting factors, which can benefit from the domain of multiple criteria decision making (MCDM). However, the indexes and factors representing the stock performance are often imprecise or vague and this should be represented by linguistic terms characterized by fuzzy numbers. The aim of this research is to first develop three group MCDM methods, then use them for selecting undervalued stocks by dint of financial ratios and subjective judgments of experts. This study proposes three versions of fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution): conventional TOPSIS (C-TOPSIS), adjusted TOPSIS (A-TOPSIS) and modified TOPSIS (M-TOPSIS) where a new fuzzy distance measure, derived from the confidence level of the experts and fuzzy performance ratings have been included in the proposed methods. The practical aspects of the proposed methods are demonstrated through a case study in the Tehran stock exchange (TSE), which is timely given the need for investors to select undervalued stocks in untapped markets in the anticipation of easing economic sanctions from a change in recent government leadership

Environmental Impacts of Heavy-Duty Natural Gas Vehicle Incentives in California

Society has an interest in reducing pollutants emitted from the vehicles used for transporting people and goods. The main goal of heavy-duty natural gas vehicle (NGV) incentive projects is to offer upfront monetary incentives to reduce greenhouse gas emissions and the production of regulated pollutants in the state. However, these incentives are often based on vehicle weight and do not account for environmental impacts. In addition, although heavy-duty NGVs are being used in a variety of vocation types, conventional emission models only support a limited number of these vocation types. Because of this, it is challenging to assess the precise impacts of the heavy-duty NGV (HD NGV) adoption and predict the specific environmental benefits per given operational conditions and vocation type. If government agencies realize the environmental benefits of alternative fuel vehicles (AFVs), like NGVs, with respect to vocation type and operating characteristics, it would be beneficial to design cost-effective incentive structures and implementation plans. This study primarily focused on the operational characteristics and environmental impacts of the HD NGVs incentivized in California. This study conducted pattern clustering and classification analyses to obtain drive mode compositions (DMC) over duty cycles and showed the heterogeneity of operational and emission characteristics of the vocational HD NGVs. The vocational impact analysis computed the adoption impact of 40 NGVs operating in California across ten different vocation types. The proposed evaluation framework included life-cycle nitrogen oxides (NOx) and carbon dioxide (CO2) emissions of natural gas, renewable natural gas and diesel fuel pathways and compared the lifetime NOx emission reduction potential of the considered vocation type vehicles. The resulting emission benefits of the fuel pathways were used to determine the most incentive-effective vocation types among the considered NGV applications. The multi-criteria decision-making analysis prioritized the fuel pathways based on multiple criteria which are related to an incentive effectiveness index as well as life cycle emissions. Refuse truck and transit bus pathways are likely to achieve the highest return for the total incentive granted when the vehicles are renewable natural gas (RNG)-powered. For compressed natural gas (CNG) fuel pathways, school and transit buses take the highest ranks over the various analysis scenarios. Each vocation type showed different incentive effects and emission reduction potential, which means that some vocational vehicles can play a critical role in the state’s funding and emission reduction plans. The suggested decision-making tool and assessment framework can provide useful reference data to improve the performance of future alternative fuel vehicle incentive programs