Multi-criteria Techniques Research Articles

Combining geophysical techniques and multi-criteria GIS-based application modeling approach for groundwater potential assessment in southwestern Nigeria

A new approach of modeling very low frequency–electromagnetic (VLF–EM) and vertical electrical sounding (VES) data with a view of evaluating groundwater resources potential via application of GIS-based multi-criteria technique is investigated in this study. On eight VLF–EM traverses established in the site, 40 VES locations were combed. The acquired geophysical data (VLF–EM and VES) were processed applying Fraser/Karous–Hjelt filter and Win-Resist program geophysical software to determine the area subsurface geophysical parameters. Five hydrogeologic maps were produced based on the results of the interpreted geophysical parameters. The produced hydrogeologic maps were assigned suitable weights and different rankings to the individual classes boundary within the maps using the standard Saaty’s scale principle in the context of analytical hierarchy process (AHP) data mining technique. A raster-based empirical GIS model was developed for integrating the hydrogeologic maps to compute the groundwater potential index (GWPI) values in the range of 1.02–2.82 for the study area. Based on the estimated GWPI results, a final map zoning the area into low (0.0930–1.3922), medium (1.3922–1.9109) and high (1.9109–2.8173) groundwater potential classes was produced in GIS environment. The prediction accuracy of the produced potential map was established via cross-validation and in situ well correlation analysis. The results of the study established a new approach of modeling geophysical data for exploring groundwater productivity potential in the study area.

Effectiveness of conservation areas for protecting biodiversity and ecosystem services: a multi-criteria approach

ABSTRACTIn land planning strategies, methods to quantify ecosystem services (ESs) are now used to complement biodiversity assessments. Tension arises when areas important for biodiversity do not spatially co-occur with important areas for ESs. We investigate the effectiveness of protected areas in simultaneously protecting biodiversity and ESs in central Colombia and identify complementary areas. We map, integrate using a multi-criteria technique and correlate five indicators (sensitive species, ecological systems, habitat quality, scenic beauty and water provision). Reflecting the uncertainty in criteria weights, multiple maps were created and overlain with current protected areas to investigate their effectiveness. A consensus and an uncertainty map were calculated to identify multifunctional areas (high value for biodiversity and high provision of ESs and low uncertainty). Protected areas show low to intermediate levels of effectiveness (3–56% percentage overlap with simulated areas), with water provision being the service least effectively protected. Indicators do not show high levels of correlation (all p < 0.57). Sensitive species are negatively correlated with all other indicators. High representativeness levels were found around the city of Bogotá; still, extensive multifunctional areas are not contemplated under any protection status. We advocate the use of our approach to identify multi-purpose areas that are robust to divergent stakeholder opinions.EDITED BY Berta Martin-Lopez

A SThM probe optimization and its time-space multi-scale modeling

We present two aspects of modeling and design of a Scanning Thermal Microscopy (SThM) probe built by microfabrication techniques. An optimized design based on a full parametrization of its geometry is calculated using a multi-criteria optimization technique after a drastic selection of the most sensitive geometrical parameters. The optimization is carried out in the static regime. We also report a new time-space multi-scale model of the probe operating in active mode and heated with a combination of DC and modulated harmonic current sources, a case where the simulation takes too long to be used in a regular design process. The model derivation is based on an asymptotic methods related to high frequency periodic source. Precisely, the model distinguishes between two time scales and two space scales related to the low and high frequency phenomena. Simulation results show the potential of the model in terms of accuracy and computation speed and are compared to experimental results.

A Disaster Risk Management Performance Index to Assess Safety and Security in Industrial Plants

The goal of the research is to present an integrated approach that combines multi criteria analysis and disaster and emergency management. The study is based on a well know multi criteria technique, the Analytic Hierarchy Process (AHP). An AHP model is proposed in order to define a Disaster Risk Management Performance Index (DRMPI) that quantifies the performance and effectiveness of risk management to evaluate emergency alternative problems. This model is implemented in a real case study.

Multicriteria Decision Making With Ordinal/Linguistic Intuitionistic Fuzzy Sets For Mobile Apps

We discuss the need for obtaining aggregation operations on ordinal-based intuitionistic fuzzy subsets (OBIFS) in order to enable the use of user-friendly fuzzy multicriteria techniques in the mobile “Apps” based environment. We next formally define these OBIFS and look at some of their properties. We describe the formal definition of aggregation of these sets, which is central to multicriteria decision making. We look at some fundamental types of aggregation in this ordinal intuitionistic environment. Particularly notable is our discussion of a new class of ordinal t-norms and t-conorms called stick-type operators.

Ranking of industrial forest plantations in terms of sustainability: A multicriteria approach

As forest managers and owners must have precise assessments of sustainability, in this study we have proposed a methodology based on multi-criteria techniques for assessing sustainability in industrial forest plantations and establishing a ranking of these plantations in terms of sustainability. First, we identified and have briefly described a set of sustainability indicators (economic, environmental and social). Next, we developed a statistical procedure to determine if a linear relationship existed between the indicators. With this analysis, the final set of indicators was defined and normalized. Then, we formulated four goal programming models, by which to aggregate the different indicators. In these models, we introduced the preferences of the decision makers for each indicator, using a survey with questions formulated in a pairwise comparison format.The procedure was applied to 30 Eucalyptus globulus Labill. plantations in northwestern Spain and 11 indicators were selected in order to define the sustainability. The results showed several rankings under each goal programming model. Although the results may not be the same in the different models, some plantations are always the most sustainable, while others are always the worst in terms of sustainability. The combination of initial values of indicators, goal programming models and preferences of stakeholders (preferential weights and targets) influence the results, and it cannot be predicted a priori which plantation is the best/worst in terms of sustainability. In our case study, we show how changes in preferential weights and targets substantially modify the results obtained.

DO INDUSTRY AND ACADEMIC EXPERTS DIFFER IN WEIGHTING CRITERIA FOR AGRICULTURAL PLANNING AND IN THEIR LOSS AVERSION?

&lt;p&gt;Agricultural planning models account for changing weather conditions and for high food price volatility. Applying the criteria of maximum farmer’s profit in various years enables the use of multi-criteria techniques. This paper presents the application of the Analytical Hierarchy Process (AHP) to estimate the importance of these criteria. The study contributes to the literature by a) addressing expert opinions on the importance of the criteria of profit in normal, dry years, and in years when agricultural prices rise; b) examining differences in weighting criteria between industry and academic experts; c) taking into account the loss averse behavior for these two groups of experts. Industry and academic experts were interviewed in the agricultural region of North-Eastern Israel. Changes in profit are approximated by a linear utility function with a positive slope (for both losses and gains) which is steeper for losses (profit in dry years) than for gains (profit in years when prices rise). The AHP method allows for the identification of the importance of the criteria for all respondents as a whole and for academic experts as compared to industrial experts. The share of loss averse respondents and coefficients of loss aversion are identified for both groups of experts. These coefficients are used for explaining differences between industry and academic expert opinions in estimating the criteria importance.&lt;/p&gt;

The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots

This paper suggests spatial multi-criteria model in order to assist decision makers in the selection of sites which are suitable for ammunition depots (AD). They represent military facilities which have more criteria that need to be matched than civil structures. The proposed model is based on combined use of Geographic information systems (GIS) and multi-criteria techniques. The model application is presented in the case study of Carpathian region, the Eastern part of Serbia. The model deals with nine restrictions and six evaluation criteria. Decision Making Trial and Evaluation Laboratory—Analytic Network Process (DEMATEL-ANP) multi-criteria techniques are used to determine weight coefficients of evaluation criteria. Along with the above mentioned methods, this paper introduces a new technique for the multi-criteria decision making—MAIRCA (MultiAttributive Ideal-Real Comparative Analysis) method. The MAIRCA method is used for the ranking and selection of suitable locations. The results have shown that 45 km2 of the Carpathian region is very suitable for ammunition depot construction. The MAIRCA method chose location L1 as the most appropriate. Sensitivity analysis shows that the model is capable of identifying a suitable ammunition depot location. This approach can be helpful in determining suitable ammunition depot locations in other regions with similar geographic conditions and can also be successfully used for the suitability assessment of existing ammunition depots.

Multi-criteria technique for mapping of debris-covered and clean-ice glaciers in the Shaksgam valley using Landsat TM and ASTER GDEM

Glaciers in the Shaksgam valley provide important fresh water resources to neighbourhood livelihood. Repeated creation of the glacier inventories is important to assess glacier–climate interactions and to predict future runoff from glacierized catchments. For this study, we applied a multi-criteria technique to map the glaciers of the Shaksgam valley of China, using Landsat Thematic Mapper (Landsat TM) (2009) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model version two (ASTER GDEM V2) data. The geomorphometric parameters slope, plan, and profile curvature were generated from ASTER GDEM. Then they were organized in similar surface groups using cluster analysis. For accurate mapping of supraglacial debris area, clustering results were combined with a thermal mask generated from the Landsat TM thermal band. The debris-free glaciers were identified using the band ratio (TM band 4/TM band 5) technique. Final vector maps of the glaciers were created using overlay tools in a geographic information system (GIS). Accuracy of the generated glacier outlines was assessed through comparison with glacier outlines based on the Second Chinese Glacier Inventory (SCGI) data and glacier outlines created from high-resolution Google Earth™ images of 2009. Glacier areas derived using the proposed approach were 3% less than in the reference datasets. Furthermore, final glacier maps show satisfactory mapping results, but identification of the debris-cover glacier terminus (covered by thick debris layer) is still problematic. Therefore, manual editing was necessary to improve the final glacier maps.

Identification and prioritization of effective factors in assessment and ranking of contractors using fuzzy multi-criteria techniques

Article history: Received June 25, 2015 Received in revised format: June 28, 2015 Accepted July 31, 2015 Available online August 6 2015 In the recent years, issues like high competitive pressure, globalization, business difficulties, resources limits, technological complications and activities specialization, fast changes in environment, etc. have caused organizations to reconsider their management methods. As a result, they are looking forward to branding new strategies in order to achieve competitive advantages. Focusing on main competences and outsourcing most of the activities are some of these strategies. Assessment management and selecting the appropriate contractor who holds adequate efficiency is of critical importance for having a project accomplished in time and with foreseen resources. Various qualitative and quantitative factors of different importance are involved in contractors’ assessment and should be taken into account before decision making. In this paper, once the factors are identified using fuzzy screening method, they are prioritized according to their importance by means of fuzzy hierarchical analysis. Growing Science Ltd. All rights reserved. 6 © 201

Multi-Criteria Decision Analysis Approaches for Selecting and Evaluating Digital Learning Objects

The wide spread of internet resources has emerged new paradigms of learning and knowledge delivery to facilitate and enhance learning particularly in e-learning systems. The important milestones of these new paradigms are known as digital learning objects (DLO) which are smallest packed bits for learning. The abundance of these DLOs raises an important question on how to select effectively high quality reusable learning objects. There exist many soft computing approaches such as; fuzzy computing, neural networks, evolutionary computing, support vector machines, machine learning and probabilistic reasoning. In this paper, fuzzy multi-criteria decision-making methods in choosing suitable DLOs were reviewed. This paper discusses recent variety of soft computing methods used in selecting and evaluating digital learning objects through multi criteria decision analysis approaches used; for selecting metrics like basic topical, course similarity, internal topical, basic and user similarity personal, and context similarity situational relevance and for evaluation; scalarization method, employing triangular, trapezoidal and distance based similarity (adapted from TOPSIS techniques). As DLOs continue to evolve it is inevitable to utilize multi-criteria techniques for selecting and or improving quality. The abundance of DLOs has increased the need for applying practical soft computing techniques to retrieve high quality, reusable DLOs.

Weak and Strong Compensation for the Prioritization of Public Investments: Multidimensional Analysis for Pools

Despite the economic crisis still heavily affecting most of Europe, a possible resumption can be found in the revitalization of public and private investments. These investments should be directed not only towards the strategic areas of infrastructures and production, but also to those which allow for a higher level of the quality of life (sports facilities, parks, etc.). In such cases, the need to balance the reasons of financial sustainability with environmental and social profiles is even more evident. Thus, multicriteria techniques, supporting complex assessments, should be implemented together with a monetary feasibility study (cost-benefit analysis). Multidimensional methods allow for the aggregation of different profiles into overall indicators. This study gives an account of how the application and comparison of multi-criteria approaches based on tools characterized by a higher or lower level of compensation between criteria can broaden the spectrum of analysis of the problems and lead to a more subtle logic of funding for public works and works of public utility, with a more current and mature sharing of profitability between private investors and users of community infrastructures.

Test Case Prioritization Using Metaheuristic Search Techniques

In this paper, Artificial Particle Swarm Optimization (PSO) inspired by real Swarm social–psychological tendency is used to solve time constraint prioritization problem-the techniques to prioritize the test cases that finds faults as early as possible, or maximize the rate of fault detection in the suite. The proposed technique is compared with three searches based metaheuristic approaches–(1) an ant-colony optimization approach, (2) Cuscuta search algorithm and (3) Hybrid Particle Swarm Optimization algorithm and two evolutionary metaheuristic- (1) Multi-Criteria Genetic algorithm technique which the fitness is APFD and (2) Multi-Criteria Genetic algorithm technique which the fitness is the proposed fitness multiplied by APFD and with five other non-search based prioritization techniques- (1) optimal, (2) random, (3) reverse, (4) untreated and (5) average faults found per minute algorithm based ordering. We investigate whether the proposed PSO metaheuristic outperforms existing prioritizing techniques in terms of APFD Score.

Selecting a small run-of-river hydropower plant by the analytic hierarchy process (AHP): A case study of Miño-Sil river basin, Spain

Hydroelectric power is obtained by harnessing the potential energy of a mass of water flowing along a river bed to convert it first into mechanical and then into electrical energy. The system is therefore both clean and autonomous and has a high potential for development.A small hydropower plant has an installed power capacity of below 10MW and is considered run-of-river when it diverts part of a river flow to generate its electricity.The use of multicriteria techniques in environmental decision making, including selecting between various alternatives, is important when it involves complex decisions in a number of disciplinary fields. The most widely used of these techniques is the analytic hierarchy process (AHP).This work proposes an application of the AHP method to select the best alternative for the installation of a small run-of-river hydropower plant. The systemization of the process, together with its mathematical rigor, means the best project will be selected from the available technical, economic and environmental alternatives.The main criteria identified in this study for the selection of RoR plant are: protected fauna, fish population, water quality, landscape quality, flow regime and vegetation. Finally, the best alternative was the project of the company Energia of Galicia.

A conceptual framework for economic optimization of an animal health surveillance portfolio.

Decision making on hazard surveillance in livestock product chains is a multi-hazard, multi-stakeholder, and multi-criteria process that includes a variety of decision alternatives. The multi-hazard aspect means that the allocation of the scarce resource for surveillance should be optimized from the point of view of a surveillance portfolio (SP) rather than a single hazard. In this paper, we present a novel conceptual approach for economic optimization of a SP to address the resource allocation problem for a surveillance organization from a theoretical perspective. This approach uses multi-criteria techniques to evaluate the performances of different settings of a SP, taking cost-benefit aspects of surveillance and stakeholders' preferences into account. The credibility of the approach has also been checked for conceptual validity, data needs and operational validity; the application potentials of the approach are also discussed.

Integrating climate change criteria in reforestation projects using a hybrid decision-support system

The selection of appropriate species in a reforestation project has always been a complex decision-making problem in which, due mostly to government policies and other stakeholders, not only economic criteria but also other environmental issues interact. Climate change has not usually been taken into account in traditional reforestation decision-making strategies and management procedures. Moreover, there is a lack of agreement on the percentage of each one of the species in reforestation planning, which is usually calculated in a discretionary way. In this context, an effective multicriteria technique has been developed in order to improve the process of selecting species for reforestation in the Mediterranean region of Spain. A hybrid Delphi-AHP methodology is proposed, which includes a consistency analysis in order to reduce random choices. As a result, this technique provides an optimal percentage distribution of the appropriate species to be used in reforestation planning. The highest values of the weight given for each subcriteria corresponded to FR (fire forest response) and PR (pests and diseases risk), because of the increasing importance of the impact of climate change in the forest. However, CB (conservation of biodiversitiy) was in the third position in line with the aim of reforestation. Therefore, the most suitable species were Quercus faginea (19.75%) and Quercus ilex (19.35%), which offer a good balance between all the factors affecting the success and viability of reforestation.

Industrial and Academic Experts: Do They Differ in Their Weighting of Criteria for Agricultural Planning?

Agricultural planning models account for changing weather conditions and for high food price volatility. The maximum profit of farmers is one of the common criteria in these models. In this study I compare expert opinions on the importance of the criteria of maximum profit in a normal year, a dry year, and a year when agricultural prices rise substantially relative to a previous year. Total 32 experts in the North-Eastern Israel were interviewed: 15 of them working in agriculture (industry experts) and 17 – academic experts. Knowing weights of criteria is necessary for applying various multi-criteria techniques for handling weather and price uncertainties. The importance of the criteria was estimated from the collected expert opinions using the method of the Analytic Hierarchy Process. The experts answered questions about pairs of the criteria. All answers were reported on the 5-point scale that included “much more important”, “more important”, “the same importance”, “less important”, “much less important”. Then the balanced scale was used to give numeric values to the answers. Consistency ratios for every expert were calculated based on the given answers. The criterion “profit in a normal year” was the most important one. For academic experts this criterion was significantly less important, and the criterion of profit in a dry year was more important as compared to industrial experts. Almost the same percent in both categories of experts, 82-87%, were identified as loss averse persons. The coefficient of loss aversion was significantly higher for academic experts.

Aggregation systems for sales forecasting

Sales forecasting consists of calculating the expected sales of a specific product or company. An important issue when dealing with sales forecasting is the calculation of the average sales, usually using the arithmetic mean or the weighted average. This study introduces new methods for calculating the average sales. These methods are two modern aggregation operators: the ordered weighted average, and the unified aggregation operator. The main advantage of this approach is the possibility to deal with uncertain and complex environments in a more complete way. The study develops some key examples through multi-person and multi-criteria techniques. The study also presents a numerical example regarding the calculation of the average sales of a product in a set of countries.

GESTIÓN DE RESIDUOS SÓLIDOS EN CADENAS DE SUMINISTRO DE CICLO CERRADO DESDE LA PERSPECTIVA DE LA INVESTIGACIÓN DE OPERACIONES

The integration of reverse and direct flows within the supply chain is highly benefitial to reduce costs and avoid the enviromental damage because value from the solid waste is recovered; this integration is known as closed-loop supply chain. Most of the reported experiences regarding closed-loop supply chains and solid waste management decisions come from developed countries with strict environmental regulations and use of operations research techniques.This paper aims to identify the feasibility of applying operations research techniques to solid waste magement decisions within closed-loop supply chains in developing countries such as Colombia. Important variables such as the different kinds of solid waste, the regions and the use of optimization, simulation and multi-criteria techniques were identified by reviewing research articles. Technologic watch methodology was used to correlate these variables. The results showed that the multi-criteria technique is most frequently used because it allows including different aspects related to a single decision; therefore, the use of this technique would be appropiate to effectively approach the main decisions at the emerging closed-loop supply chains in developing countries.

Siting Carbon Conversion Energy Facilities With Spatial Multicriteria Decision Analysis

Wyoming is known for its abundance of fossil fuels, and has a significant infrastructure to support the production of these traditional energy resources. With increased demand for more diverse energy sources, a need has emerged to pursue new, innovative energy development approaches. This article describes the application of spatial multicriteria analysis to explore potential for carbon conversion energy facilities in Wyoming. Spatial multicriteria analysis is an important capability of geographic information systems, applying multiple criteria evaluation to place-based problems such as facilities siting. Two cases are presented concerning synthetic gas production—the siting of a small-scale coal gasification facility to support a public–private research partnership, and development of a statewide suitability model for commercialization of high-temperature gas-cooled nuclear reactor technology. Results demonstrate that success and challenges with multicriteria techniques are influenced by the availability of quality geospatial data, accessibility of computational processing resources, and committed engagement and utilization of domain experts.