The Weights Detection of Multi-criteria by using Solver

Multi criteria, which are generally used for decision analysis, have certain characteristics that relate to the purpose of the decision. Multi criteria have complex structures and have different weights depending upon the consideration of assessors and the purpose of the decision also. Expert’s judgment will be used to detect the criteria weights that applied by assessors. The aim of this study is a model to detect the criteria weights and biases on the subcontractor selection and detecting the significant weights, as decisive criteria. A method, which is used to modeling the weights detection, is the Solver Application. Data, totaling 40 sets, has been collected that consist of the assessor’s assessment and the expert’s judgment. The result is a pattern of weights and biases detection. The proposed model have been able to detect of 20 criteria weights and biases, that consist of 4 criteria in  the total weights of 60% (as decisive criteria) and 16 criteria in the total weights of 40%. A model has been built by training process performed by the Solver, which the result for MSE training is 9.73711e-08 and for MSE validation is 0.00900528. Novelty in the study is a model to detect pattern of weights criteria and biases on subcontractor selection by transferring the expert's judgment using Solver Application

A robustness study of state-of-the-art surrogate weights for MCDM

A vast number of methods for solving multi-criteria decision problems have been suggested for assessing criteria weights requiring more exact input data than users normally are able to provide. In particular, the selection of adequate criteria weights is difficult and in order to be realistic, other methods must be introduced. One class of such methods is to introduce so called surrogate weights, where numerical weights are assigned to each criterion based on a cardinal or ordinal rank ordering, assumed to represent the information extracted from the user. One essential problem is the robustness of such methods. In this article, we compare state-of-the-art methods based on surrogate weights from the literature and, utilizing a simulation approach, discuss underlying assumptions and robustness properties. This results in a quantitative measurement of these weighting methods and a methodology applicable also to forthcoming methods

Pairwise comparison matrices and the error-free property of the decision maker

Pairwise comparison is a popular assessment method either for deriving criteria-weights or for evaluating alternatives according to a given criterion. In real-world applications consistency of the comparisons rarely happens: intransitivity can occur. The aim of the paper is to discuss the relationship between the consistency of the decision maker—described with the error-free property—and the consistency of the pairwise comparison matrix (PCM). The concept of error-free matrix is used to demonstrate that consistency of the PCM is not a sufficient condition of the error-free property of the decision maker. Informed and uninformed decision makers are defined. In the first stage of an assessment method a consistent or near-consistent matrix should be achieved: detecting, measuring and improving consistency are part of any procedure with both types of decision makers. In the second stage additional information are needed to reveal the decision maker’s real preferences. Interactive questioning procedures are recommended to reach that goal

An integrated fuzzy approach to solving multi-criteria decision making problems / Nor Hanimah Kamis

Multi-criteria decision making (MCDM). Method is a technique where alternatives or options are assessed based on a set of criteria. Criteria weights determination and ranking of alternatives are two important aspects in solving MCDM problems. The evaluation of criteria importance by decision makers and performance rating towards alternatives often involve subjective preferences, which are normally vague and imprecise. This study proposed an improvised algorithm in criteria weights determination based on consistent fuzzy preference relations (CFPR). CFPR requires only (n-l) pair-wise comparisons from a given n criteria as compared to other some existing pairwise-based comparison approaches. We improvised Herrera-Viedma's et. al (2004) algorithm by introducing fuzzy numbers to represent input values for the entries of decision matrix. However, application of fuzzy numbers in representing importance of criteria requires tedious calculation. Therefore, centroid-index formula (Chen & Chen, 2000, 2003) was utilized in order to transform fuzzy numbers into crisp values, which indirectly gives lesser computation. The generalized Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method by Wang and Lee (2007) with some modification on criteria weights determination procedure using our proposed algorithm was employed in ranking the alternatives. An example problem on new staff selection in the Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) Malaysia is given to demonstrate the computational parts of this proposed model. This model can be used as an alternative tool in solving MCDM problems

Construction of Vehicle Theft Index by Using TOPSIS Method with Entropy Based Criteria Weights

Property theft especially vehicle theft is a major contribution of entire crime. Estimating the level of crime by depending solely on the total of vehicle theft cases recorded is insufficient in order to observe the direction of the problem itself. The aim of this paper is to construct a vehicle theft index based on multi-criteria decision method to analyse vehicle theft pattern in particular and property theft in general for 82 areas in peninsular Malaysia. As vehicle theft is the major part of property crime, it is influenced by other criteria such as unemployment, level of education, immigrant and drug which should be considered in the vehicle theft index construction. Hence, this study takes into account the diversity of intrinsic of information in the criteria by measuring the entropy or the degree of diverseness of the data as proxies of the relative importance of the criteria. Then a Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) was used to construct the vehicle theft index of 82 areas in peninsular Malaysia. The finding shows the top three areas in descending order are Kuala Lumpur, Petaling and Johor Bahru. The vehicle theft index constructed in this study can illustrate the actual direction of theft problem in Malaysia and the index construction process can be applied in other countries as well

Sustainability assessment of concrete bridge deck designs in coastal environments using neutrosophic criteria weights

"This is an Accepted Manuscript of an article published by Taylor & Francis in Structure and Infrastructure Engineering on 02/07/2020, available online: https://doi.org/10.1080/15732479.2019.1676791."[EN] Essential infrastructures such as bridges are designed to provide a long-lasting and intergenerational functionality. In those cases, sustainability becomes of paramount importance when the infrastructure is exposed to aggressive environments, which can jeopardise their durability and lead to significant maintenance demands. The assessment of sustainability is however often complex and uncertain. The present study assesses the sustainability performance of 16 alternative designs of a concrete bridge deck in a coastal environment on the basis of a neutrosophic group analytic hierarchy process (AHP). The use of neutrosophic logic in the field of multi-criteria decision-making, as a generalisation of the widely used fuzzy logic, allows for a proper capture of the vagueness and uncertainties of the judgements emitted by the decision-makers. TOPSIS technique is then used to aggregate the different sustainability criteria. From the results, it is derived that only the simultaneous consideration of the economic, environmental and social life cycle impacts of a design shall lead to adequate sustainable designs. Choices made based on the optimality of a design in only some of the sustainability pillars will lead to erroneous conclusions. The use of concrete with silica fume has resulted in a sustainability performance of 46.3% better than conventional concrete designs.The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R).Navarro, I.; Yepes, V.; Martí, J. (2020). Sustainability assessment of concrete bridge deck designs in coastal environments using neutrosophic criteria weights. Structure and Infrastructure Engineering. 16(7):949-967. https://doi.org/10.1080/15732479.2019.1676791S949967167Abdel-Basset, M., Manogaran, G., Mohamed, M., & Chilamkurti, N. (2018). Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem. Future Generation Computer Systems, 89, 19-30. doi:10.1016/j.future.2018.06.024Abdullah, L., & Najib, L. (2014). Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia. International Journal of Sustainable Energy, 35(4), 360-377. doi:10.1080/14786451.2014.907292Ali, M. S., Aslam, M. S., & Mirza, M. S. (2015). A sustainability assessment framework for bridges – a case study: Victoria and Champlain Bridges, Montreal. Structure and Infrastructure Engineering, 1-14. doi:10.1080/15732479.2015.1120754Allacker, K. (2012). Environmental and economic optimisation of the floor on grade in residential buildings. The International Journal of Life Cycle Assessment, 17(6), 813-827. doi:10.1007/s11367-012-0402-2Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96. doi:10.1016/s0165-0114(86)80034-3Barone, G., & Frangopol, D. M. (2014). Life-cycle maintenance of deteriorating structures by multi-objective optimization involving reliability, risk, availability, hazard and cost. Structural Safety, 48, 40-50. doi:10.1016/j.strusafe.2014.02.002Biswas, P., Pramanik, S., & Giri, B. C. (2015). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Computing and Applications, 27(3), 727-737. doi:10.1007/s00521-015-1891-2Bolturk, E., & Kahraman, C. (2018). A novel interval-valued neutrosophic AHP with cosine similarity measure. Soft Computing, 22(15), 4941-4958. doi:10.1007/s00500-018-3140-yBuckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233-247. doi:10.1016/0165-0114(85)90090-9Büyüközkan, G., & Göçer, F. (2017). Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Applied Soft Computing, 52, 1222-1238. doi:10.1016/j.asoc.2016.08.051Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36(5), 8900-8909. doi:10.1016/j.eswa.2008.11.046Chen, C., Habert, G., Bouzidi, Y., Jullien, A., & Ventura, A. (2010). LCA allocation procedure used as an incitative method for waste recycling: An application to mineral additions in concrete. Resources, Conservation and Recycling, 54(12), 1231-1240. doi:10.1016/j.resconrec.2010.04.001Chu, T.-C., & Tsao, C.-T. (2002). Ranking fuzzy numbers with an area between the centroid point and original point. Computers & Mathematics with Applications, 43(1-2), 111-117. doi:10.1016/s0898-1221(01)00277-2Cope, A., Bai, Q., Samdariya, A., & Labi, S. (2013). Assessing the efficacy of stainless steel for bridge deck reinforcement under uncertainty using Monte Carlo simulation. Structure and Infrastructure Engineering, 9(7), 634-647. doi:10.1080/15732479.2011.602418De la Fuente, A., Pons, O., Josa, A., & Aguado, A. (2016). Multi-Criteria Decision Making in the sustainability assessment of sewerage pipe systems. Journal of Cleaner Production, 112, 4762-4770. doi:10.1016/j.jclepro.2015.07.002Deli, I., & Şubaş, Y. (2016). A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems. International Journal of Machine Learning and Cybernetics, 8(4), 1309-1322. doi:10.1007/s13042-016-0505-3Dong, Y., Zhang, G., Hong, W.-C., & Xu, Y. (2010). Consensus models for AHP group decision making under row geometric mean prioritization method. Decision Support Systems, 49(3), 281-289. doi:10.1016/j.dss.2010.03.003Dubois, D. (2011). The role of fuzzy sets in decision sciences: Old techniques and new directions. Fuzzy Sets and Systems, 184(1), 3-28. doi:10.1016/j.fss.2011.06.003Eamon, C. D., Jensen, E. A., Grace, N. F., & Shi, X. (2012). Life-Cycle Cost Analysis of Alternative Reinforcement Materials for Bridge Superstructures Considering Cost and Maintenance Uncertainties. Journal of Materials in Civil Engineering, 24(4), 373-380. doi:10.1061/(asce)mt.1943-5533.0000398Enea, M., & Piazza, T. (2004). Project Selection by Constrained Fuzzy AHP. Fuzzy Optimization and Decision Making, 3(1), 39-62. doi:10.1023/b:fodm.0000013071.63614.3dGarcía-Segura, T., Penadés-Plà, V., & Yepes, V. (2018). Sustainable bridge design by metamodel-assisted multi-objective optimization and decision-making under uncertainty. Journal of Cleaner Production, 202, 904-915. doi:10.1016/j.jclepro.2018.08.177García-Segura, T., & Yepes, V. (2016). Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety. Engineering Structures, 125, 325-336. doi:10.1016/j.engstruct.2016.07.012García-Segura, T., Yepes, V., Frangopol, D. M., & Yang, D. Y. (2017). Lifetime reliability-based optimization of post-tensioned box-girder bridges. Engineering Structures, 145, 381-391. doi:10.1016/j.engstruct.2017.05.013Gervásio, H., & Simões da Silva, L. (2012). A probabilistic decision-making approach for the sustainable assessment of infrastructures. Expert Systems with Applications, 39(8), 7121-7131. doi:10.1016/j.eswa.2012.01.032Guzmán-Sánchez, S., Jato-Espino, D., Lombillo, I., & Diaz-Sarachaga, J. M. (2018). Assessment of the contributions of different flat roof types to achieving sustainable development. Building and Environment, 141, 182-192. doi:10.1016/j.buildenv.2018.05.063Heravi, G., Fathi, M., & Faeghi, S. (2017). Multi-criteria group decision-making method for optimal selection of sustainable industrial building options focused on petrochemical projects. Journal of Cleaner Production, 142, 2999-3013. doi:10.1016/j.jclepro.2016.10.168Invidiata, A., Lavagna, M., & Ghisi, E. (2018). Selecting design strategies using multi-criteria decision making to improve the sustainability of buildings. Building and Environment, 139, 58-68. doi:10.1016/j.buildenv.2018.04.041Jakiel, P., & Fabianowski, D. (2015). FAHP model used for assessment of highway RC bridge structural and technological arrangements. Expert Systems with Applications, 42(8), 4054-4061. doi:10.1016/j.eswa.2014.12.039Kahraman, C., Cebi, S., Onar, S. C., & Oztaysi, B. (2018). A novel trapezoidal intuitionistic fuzzy information axiom approach: An application to multicriteria landfill site selection. Engineering Applications of Artificial Intelligence, 67, 157-172. doi:10.1016/j.engappai.2017.09.009Kere, K. J., & Huang, Q. (2019). Life-Cycle Cost Comparison of Corrosion Management Strategies for Steel Bridges. Journal of Bridge Engineering, 24(4), 04019007. doi:10.1061/(asce)be.1943-5592.0001361Liang, R., Wang, J., & Zhang, H. (2017). A multi-criteria decision-making method based on single-valued trapezoidal neutrosophic preference relations with complete weight information. Neural Computing and Applications, 30(11), 3383-3398. doi:10.1007/s00521-017-2925-8Liu, P., & Liu, X. (2016). The neutrosophic number generalized weighted power averaging operator and its application in multiple attribute group decision making. International Journal of Machine Learning and Cybernetics, 9(2), 347-358. doi:10.1007/s13042-016-0508-0Martí, J. V., García-Segura, T., & Yepes, V. (2016). Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy. Journal of Cleaner Production, 120, 231-240. doi:10.1016/j.jclepro.2016.02.024Martínez-Blanco, J., Lehmann, A., Muñoz, P., Antón, A., Traverso, M., Rieradevall, J., & Finkbeiner, M. (2014). Application challenges for the social Life Cycle Assessment of fertilizers within life cycle sustainability assessment. Journal of Cleaner Production, 69, 34-48. doi:10.1016/j.jclepro.2014.01.044Mistry, M., Koffler, C., & Wong, S. (2016). LCA and LCC of the world’s longest pier: a case study on nickel-containing stainless steel rebar. The International Journal of Life Cycle Assessment, 21(11), 1637-1644. doi:10.1007/s11367-016-1080-2Moazami, D., Behbahani, H., & Muniandy, R. (2011). Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic. Expert Systems with Applications, 38(10), 12869-12879. doi:10.1016/j.eswa.2011.04.079Mosalam, K. M., Alibrandi, U., Lee, H., & Armengou, J. (2018). Performance-based engineering and multi-criteria decision analysis for sustainable and resilient building design. Structural Safety, 74, 1-13. doi:10.1016/j.strusafe.2018.03.005Navarro, I., Yepes, V., & Martí, J. (2018). Life Cycle Cost Assessment of Preventive Strategies Applied to Prestressed Concrete Bridges Exposed to Chlorides. Sustainability, 10(3), 845. doi:10.3390/su10030845Navarro, I. J., Martí, J. V., & Yepes, V. (2019). Reliability-based maintenance optimization of corrosion preventive designs under a life cycle perspective. Environmental Impact Assessment Review, 74, 23-34. doi:10.1016/j.eiar.2018.10.001Navarro, I. J., Yepes, V., & Martí, J. V. (2018). Social life cycle assessment of concrete bridge decks exposed to aggressive environments. Environmental Impact Assessment Review, 72, 50-63. doi:10.1016/j.eiar.2018.05.003Navarro, I. J., Yepes, V., Martí, J. V., & González-Vidosa, F. (2018). Life cycle impact assessment of corrosion preventive designs applied to prestressed concrete bridge decks. Journal of Cleaner Production, 196, 698-713. doi:10.1016/j.jclepro.2018.06.110Nogueira, C. G., Leonel, E. D., & Coda, H. B. (2012). Reliability algorithms applied to reinforced concrete structures durability assessment. Revista IBRACON de Estruturas e Materiais, 5(4), 440-450. doi:10.1590/s1983-41952012000400003Pamučar, D., Badi, I., Sanja, K., & Obradović, R. (2018). A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya. Energies, 11(9), 2489. doi:10.3390/en11092489Penadés-Plà, V., García-Segura, T., Martí, J., & Yepes, V. (2016). A Review of Multi-Criteria Decision-Making Methods Applied to the Sustainable Bridge Design. Sustainability, 8(12), 1295. doi:10.3390/su8121295Peng, J., Wang, J., & Yang, W.-E. (2016). A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems. International Journal of Systems Science, 48(2), 425-435. doi:10.1080/00207721.2016.1218975Petcherdchoo, A. (2015). Environmental Impacts of Combined Repairs on Marine Concrete Structures. Journal of Advanced Concrete Technology, 13(3), 205-213. doi:10.3151/jact.13.205PRASCEVIC, N., & PRASCEVIC, Z. (2017). APPLICATION OF FUZZY AHP FOR RANKING AND SELECTION OF ALTERNATIVES IN CONSTRUCTION PROJECT MANAGEMENT. Journal of Civil Engineering and Management, 23(8), 1123-1135. doi:10.3846/13923730.2017.1388278Pryn, M. R., Cornet, Y., & Salling, K. B. (2015). APPLYING SUSTAINABILITY THEORY TO TRANSPORT INFRASTRUCTURE ASSESSMENT USING A MULTIPLICATIVE AHP DECISION SUPPORT MODEL. TRANSPORT, 30(3), 330-341. doi:10.3846/16484142.2015.1081281Rashidi, M., Samali, B., & Sharafi, P. (2015). A new model for bridge management: Part B: decision support system for remediation planning. Australian Journal of Civil Engineering, 14(1), 46-53. doi:10.1080/14488353.2015.1092642Sabatino, S., Frangopol, D. M., & Dong, Y. (2015). Life cycle utility-informed maintenance planning based on lifetime functions: optimum balancing of cost, failure consequences and performance benefit. Structure and Infrastructure Engineering, 12(7), 830-847. doi:10.1080/15732479.2015.1064968Safi, M., Sundquist, H., & Karoumi, R. (2015). Cost-Efficient Procurement of Bridge Infrastructures by Incorporating Life-Cycle Cost Analysis with Bridge Management Systems. Journal of Bridge Engineering, 20(6), 04014083. doi:10.1061/(asce)be.1943-5592.0000673Sajedi, S., & Huang, Q. (2019). Reliability-based life-cycle-cost comparison of different corrosion management strategies. Engineering Structures, 186, 52-63. doi:10.1016/j.engstruct.2019.02.018Sierra, L. A., Pellicer, E., & Yepes, V. (2016). Social Sustainability in the Lifecycle of Chilean Public Infrastructure. Journal of Construction Engineering and Management, 142(5), 05015020. doi:10.1061/(asce)co.1943-7862.0001099Sierra, L. A., Yepes, V., García-Segura, T., & Pellicer, E. (2018). Bayesian network method for decision-making about the social sustainability of infrastructure projects. Journal of Cleaner Production, 176, 521-534. doi:10.1016/j.jclepro.2017.12.140Sodenkamp, M. A., Tavana, M., & Di Caprio, D. (2018). An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets. Applied Soft Computing, 71, 715-727. doi:10.1016/j.asoc.2018.07.020Stewart, M. G., Estes, A. C., & Frangopol, D. M. (2004). Bridge Deck Replacement for Minimum Expected Cost Under Multiple Reliability Constraints. Journal of Structural Engineering, 130(9), 1414-1419. doi:10.1061/(asce)0733-9445(2004)130:9(1414)Swarr, T. E., Hunkeler, D., Klöpffer, W., Pesonen, H.-L., Ciroth, A., Brent, A. C., & Pagan, R. (2011). Environmental life-cycle costing: a code of practice. The International Journal of Life Cycle Assessment, 16(5), 389-391. doi:10.1007/s11367-011-0287-5Tahmasebi Birgani, Y., & Yazdandoost, F. (2018). An Integrated Framework to Evaluate Resilient-Sustainable Urban Drainage Management Plans Using a Combined-adaptive MCDM Technique. Water Resources Management, 32(8), 2817-2835. doi:10.1007/s11269-018-1960-2Tesfamariam, S., & Sadiq, R. (2006). Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP). Stochastic Environmental Research and Risk Assessment, 21(1), 35-50. doi:10.1007/s00477-006-0042-9Wang, Y.-M., & Elhag, T. M. S. (2006). On the normalization of interval and fuzzy weights. Fuzzy Sets and Systems, 157(18), 2456-2471. doi:10.1016/j.fss.2006.06.008Yang, Z., Shi, X., Creighton, A. T., & Peterson, M. M. (2009). Effect of styrene–butadiene rubber latex on the chloride permeability and microstructure of Portland cement mortar. Construction and Building Materials, 23(6), 2283-2290. doi:10.1016/j.conbuildmat.2008.11.011Ye, J. (2013). Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. International Journal of General Systems, 42(4), 386-394. doi:10.1080/03081079.2012.761609Ye, J. (2017). Subtraction and Division Operations of Simplified Neutrosophic Sets. Information, 8(2), 51. doi:10.3390/info8020051Yepes, V., García-Segura, T., & Moreno-Jiménez, J. M. (2015). A cognitive approach for the multi-objective optimization of RC structural problems. Archives of Civil and Mechanical Engineering, 15(4), 1024-1036. doi:10.1016/j.acme.2015.05.001Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. doi:10.1016/s0019-9958(65)90241-xZadeh, L. A. (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3(1), 28-44. doi:10.1109/tsmc.1973.5408575Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016). Development of TOPSIS Method to Solve Complicated Decision-Making Problems — An Overview on Developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(03), 645-682. doi:10.1142/s021962201630001

Identification of weights in multi-cteria decision problems based on stochastic optimization

Many scientific papers are devoted to solving multi-criteria problems using methods that find discrete solutions. However, the main challenge addressed by our work is the case when new decision-making variants have emerged which have not been assessed. Unfortunately, discrete identification makes it impossible to determine the preferences for new alternatives if we do not know the whole set of parameters, such as criteria weights. This paper proposes a new approach to identifying a multi-criteria decision model to address this challenge. The novelty of this work is using a discretization in the space of the problem to identify a continuous decisional model. We present a hybrid approach where the new alternative can be assessed based on stochastic optimization and the TOPSIS technique. The stochastic methods are used to find criteria weights used in the TOPSIS method. In that way, we get assessed easily each new alternative based only on the initial set of evaluated alternatives

Classification and Mapping of Recreation and Ecotourism Areas in West Virginia

Travel and tourism are recognized as the largest and fastest growing economic sector in the world. Different recreational and tourism sites can provide different types of activities based on their unique characteristics. Like any other form of tourism, the growth of ecotourism is dependent on the flow of visitors and therefore, marketing for a destination requires identifying various characteristics of the destination and preferences of stakeholders. The main aim of this dissertation is to classify and map recreation and ecotourism areas in West Virginia. The dissertation is presented in the form of three essays. The first essay classifies and maps classes of Recreation Opportunity Spectrum (ROS) in the state and examines its relationship with the travel and tourism generated revenues. Results showed that most of the areas in the state are Rural (R) followed by Semiprimitive Nonmotorized (SPNM) and Roaded Natural (RN). Visitors\u27 travel spending was significantly associated with the urban class. The second essay identifies and maps forest-based ecotourism areas in the state using six different criteria and visitors\u27 preferences. Pairwise comparison of Analytic Hierarchy Process (AHP) was used to compute the criteria weights from questionnaire survey of visitors. Significant variations were found in visitors\u27 preferences. Areas under Class IV and Class V of naturalness continuum of both weighted and unweighted ecotourism maps covered more than half of the state\u27s area, suggesting higher prospects for promoting forest-based ecotourism in the state. The results also indicated that each class changed in size when visitors\u27 preferences were applied. The third essay performs sensitivity analysis of the criteria weights derived from visitors and experts\u27 survey and maps the robust suitable areas for forest-based ecotourism areas in the state. Similar to essay two, pairwise comparison of AHP was used to compute criteria weights from experts. Results indicated that about one third of the state\u27s area was highly suitable and not sensitive to the variations of criteria weights. The finding of this dissertation demonstrated ROS classes and forest-based ecotourism areas in the state which could provide helpful information to the resource managers and policy makers in terms of recreation and tourism development, marketing, and promotion. Results of the study were mapped using Geographic Information System (GIS) and Geographic Data Analysis (GeoDa) software