Robust Water Resource Planning at River Basins

Freshwater is a fundamental, but scarce resource vital for life. Uncertainty is one of the significant factors in water resource systems planning and management problems. We consider the problem of water resource systems planning at river basins when there are competing demands and different operating policies. Firstly, we provide a mathematical model using the minimum cost network flow problem, in which the system is represented as a directed multi-graph. Arc coefficients are introduced for modeling gain/loss in the system. Multiple arcs are used to create of the system priorities. Secondly, we reformulate the aforementioned problem using cardinality-constrained robust optimization to address uncertainty when there is an agreement amongst decision makers about uncertainty sets. A set of experiments is conducted to demonstrate the trade-off between the level of robustness and the cost of robustness. We also use Monte-Carlo simulation to analyze the performance of the model in terms of its feasibility in the presence of uncertainty. Thirdly, we employ robust decision making (RDM) to address uncertainty when there is not an agreement amongst decision makers. RDM is applied to analyze the system performance under evaporation/ precipitation uncertainty. Monte-Carlo simulation is used to take samples from the uncertain future ranges. To evaluate the policies multiple attribute decision making (MADM) methodology is used. We have shown that the combination of RDM and MADM is a suitable approach for dealing with deep uncertainty and selecting the most suitable robust strategy. This thesis provides insight into modeling uncertainty in river basins systems

Market segment evaluation and selection based on application of fuzzy AHP and COPRAS-G methods

Market segment evaluation and selection is one of the critical marketing problems of all companies. This paper presents a novel approach which integrates fuzzy analytic hierarchy process (FAHP) and COPRAS-G method for market segment evaluation and selection. Fuzzy AHP is used to calculate the weight of each criterion, and COPRAS-G method is proposed to prioritize market segments from the best to the worst ones. The application of fuzzy set theory allows incorporating the vague and imprecise linguistic terms into the decision process. This study can be used as a pattern for market segment selection and future researches. A case study on a chair manufacturing company is put forward to illustrate the performance of the proposed methodology. First published online: 14 Sep 201

ODABIR MANAGERA KONTROLE KVALITETE NA OSNOVI AHP-COPRAS-G METODA: SLUČAJ U IRANU

Due to the increasing competition of globalization and fast technological improvements and world markets, demands of companies to have professional human resources are increasing too. It is an important problem of an organization to select the most appropriate personnel among the candidates. Quality control manager is important personnel in organizations and it’s so important to select the best candidate for this work. In this paper we proposed a personnel selection system based on Analytic Hierarchy Process (AHP) and Complex proportional assessment of alternatives with grey relations (COPRAS-G) method. At first seven criteria is identified including: knowledge of product and raw material properties, Experience and educational background, Administrative orientation, Behavioral flexibility, Risk evaluation ability, Payment and Team work and after that AHP applied for calculating weight of each criteria and finally using COPRAS- G method for selecting the best candidate for this job. This study can be used as a pattern for personnel selection and future researches.S obzirom na rastuću konkurentnost u globalizaciji te brzim tehnološkim napredovanjem na svjetskom tržištu, zahtjevi kompanija za profesionalnim kadrom se također povećavaju. Vrlo je važno za organizaciju biti u mogućnosti odabrati najbolji i najprimjereniji kadar među ponuđenim kandidatima. Manager kontrole kvalitete je važan kadar u bilo kojoj organizaciji tako da je iznimno važno za taj posao odabrati najbolje kandidate. U ovom radu predlažemo sustav odabira kadra zasnovan na analitičkom hijerarhijskom procesu (AHP) i kompleksnoj proporcionalnoj evaluaciji alternativa sa sivim odnosima (COPRAS-G). Isprva je identificirano sedam kriterija uključujući: znanje o proizvodu i svojstvima sirovine, iskustvo i obrazovanje, snalaženje s administracijom, fleksibilnost u ponašanju, sposobnost procjene rizika, plaćanja i timski rad te je zatim primijenjen AHP za izračunavanje težine svakog kriterija te je naposljetku korištena COPRAS-G metoda za odabir najboljih kandidata. Ova studija se može koristiti kao predložak za odabir kandidata i buduća istraživanja

A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment

The concept of the agile supply chain has been taken into account as means of achieving a high competitive edge in rapidly changing business environments. Supply partner selection is one of the most appealing issues for agile supply chain management, which have recently been studied by academicians and practitioners. Due to a large number of factors to be considered, supplier selection process is a difficult task for every company. Therefore, supplier selection process can be viewed as a multiple attribute decision-making (MADM) problem. In this paper, a novel hybrid MADM method is proposed for agile supplier selection based on four criteria including performance, cost, flexibility and technology. Two MADM methods, including step-wise weight assessment ratio analysis (SWARA) and Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are applied in decision-making process. More precisely, SWARA is used for determining the importance of each criterion and calculating their weights and VIKOR is applied for evaluating alternatives as well as ranking supplier alternatives from the best to the worst. More precisely, the first phase of the proposed methodology, step-wise weight assessment ratio analysis (SWARA), is useful for determining the importance of each criterion and calculating the weight of each criterion, and the second phase with Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is useful for evaluating alternatives as well as ranking supplier alternatives from the best to the worst. Finally, a real case-study is presented to demonstrate the applicability of the proposed methodology. As a result, the model can help managers to evaluate and select the best supplier regarding own company strategies, resources, policies and etc. for their organization

Prioritizing Constructing Projects of Municipalities Based on AHP and COPRAS-G: a Case Study About Footbridges in Iran

Each municipality has a certain budget for constructing, maintaining and repairing every year. Prioritizing projects is one of the difficult issues of decision making and takes time for evaluating and programming. The main aim of this study is to make a framework for municipalities to prioritize their projects based on this framework and for this a footbridge project of Sari City in Iran was selected as a case study for this research to show prioritizing of boulevards that have no footbridge for constructing footbridge. The cost of constructing footbridge is sometimes high and the footbridge site place is important for pedestrians. Besides, selecting of an area for constructing new footbridges includes quantitative and qualitative factors, such as the Total cost, Environmental factors, and Socio-economic factors. For these reasons, selecting area for constructing footbridges can be viewed as a kind of Multi-Attribute Decision Making (MADM) problem. The aim of this study is the use of Analytic Hierarchy Process (AHP) and COPRAS-G methods for evaluating and selecting an area for constructing new footbridges alternatives. More precisely, AHP was used for calculation of the relative importance of criteria and COPRAS-G method was used for ranking location alternatives

Decision making in machine tool selection: an integrated approach with SWARA and COPRAS-G methods

Machine tools are one of the important parts of manufacturing process that could help company to achieving high competitiveness in the marketplace. In addition, the quality of their outputs depends on their machines and therefore every company should select the best machine by itself. Also, a choice of appropriate machine tool is very significant for a manufacturing company as it helps to reach high productivity and efficiency. Furthermore, market offers variety kind of machines with different brands. Besides, there are many criteria with respect to numerous alternatives that should be considered as part of proper machine tool selection, such as cost, operative flexibility, safety, etc. Consequently selection of machine tool can be regarded as a multiple-attribute decision making (MADM) problem. Generally, MADM methods deal with the process of selection of an alternative among number of different alternatives in the presence of usually conflict objectives and criteria. In this study two MADM methods, step-wise weight assessment ratio analysis (SWARA) and complex proportional assessment of alternatives with grey relations (COPRAS-G), were applied for machine tool evaluation and selection.This model is a hybrid model which integrates two MADM methods for improving the quality and accuracy of the selection. Literature survey was used to identify the most attractive criteria which influence the selection of a machine tool. Eight criteria for evaluation process include cost, operative flexibility, maintainability and service ability, size and physical, compatibility, safety, precision and productivity. More precisely, the first part of the proposed methodology, i.e. SWARA is useful for determining the importance of each criterion and calculating weight of each criterion, while the second part with COPRAS-G is useful for evaluating alternatives more precisely than usual crisp COPRAS and for ranking machine tool alternatives from the best to the worst ones. In evaluation process decision maker has to assess criteria which are not accurate. Grey relation analysis allows incorporating the vague and imprecise information in to the decision model. For illustration of the proposed methodology, a case study was explained in a manufacturing company in Karaj, Iran. This model can help managers to evaluate and select the best machine tool alternative based on own company strategies, resources, policies, etc. for their organization

Synergies of Data Mining and Multiple Attribute Decision Making

AbstractData Mining (DM) and Multiple Attribute Decision Making (MADM) are two fast growing trends in Operations Research (OR)/Management Science (MS). In this article, we identify the synergies of data mining and MADM. Synergies can be attained by integration of MADM techniques into data mining and vice versa. The primary goal of the paper is to show a wide range of interactions between these two fields from a new perspective with an example of the integrated approach in supplier clustering and ranking. The integrated approach includes cluster analysis as a data mining tool and Step-wise Weight Assessment Ratio Analysis (SWARA) and VIseKriterijumskao ptimizacija i KOmpromisno Resenje (VIKOR) as the two MADM tools. More precisely, the features for clustering were selected and weighted by SWARA method and suppliers are clustered using two-stage cluster analysis. In addition, VIKOR technique is used to rank the clusters from the best to the worst one. The proposed integrated approach is presented to demonstrate the applicability of the proposed methodology