Hybrid Methods for Optimisation of Weights in Spatial Multi-Criteria Evaluation Decision for Fire Risk and Hazard

The challenge for everyone involved in preserving the ecosystem is to find creative ways to protect and restore the remaining ecosystems while accommodating and enhancing the country social and economic well-being. Frequent fires of anthropogenic origin have been affecting the ecosystems in many countries adversely. Hence adopting ways of decision making such as Multicriteria Decision Making (MCDM) is appropriate since it will enhance the evaluation and analysis of fire risk and hazard of the ecosystem. In this paper, fire risk and hazard data from the West Gonja area of Ghana were used in some of the methods (Analytical Hierarchy Process, Compromise Programming, and Grey Relational Analysis (GRA) for MCDM evaluation and analysis to determine the optimal weight method for fire risk and hazard. Ranking of the land cover types was carried out using; Fire Hazard, Fire Fighting Capacity and Response Risk Criteria. Pairwise comparison under Analytic Hierarchy Process (AHP) was used to determine the weight of the various criteria. Weights for sub-criteria were also obtained by the pairwise comparison method. The results were optimised using GRA and Compromise Programming (CP). The results from each method, hybrid GRA and CP, were compared and it was established that all methods were satisfactory in terms of optimisation of weight. The most optimal method for spatial multicriteria evaluation was the hybrid GRA method. Thus, a hybrid AHP and GRA method is more effective method for ranking alternatives in MCDM than the hybrid AHP and CP method.





References:
[1] Zimmermann, H. J. (2000), “An Application-Oriented View of Modelling Uncertainty”, European Journal of Operational Research, Vol. 122, No. 2, pp. 190-198.
[2] Hwang, C. L. and Yoon, K. (1982), Multiple Attribute Decision Making, Taylor and Francis Group, U.S., 350 pp.
[3] Turskis, Z. and Zavadskas, E. K. (2010), “A Novel Method for Multiple Criteria Analysis: Grey Additive Ratio Assessment (ARAS-G) Method”, Informatica, Vol. 21, No. 4, pp. 597-610.
[4] Jayakrishna, K., Vinodh, S., Sanghvi, V.S. and Deepika, C., 2016. Application of GRA for sustainable material selection and evaluation using LCA. Journal of The Institution of Engineers (India): Series C, 97(3), pp.309-322.
[5] Stanujkic, D. Dordevic, B. and Dordevic, M. (2013), “Comparative Analysis of Some Prominent MCDM Methods: A Case of Ranking Serbian Banks”, Serbian Journal of Management, Vol. 8, No. 2, pp. 213-241.
[6] Ginevicius, R., Podvezko, V., Raslanas, S. (2008), Evaluatiing the Alternative Solutions of Wall Insultation by Multicriteria Methods, Journal of Civil Engineering and Management, Vol. 14, No. 4, 217-226.
[7] Sivilevicius, H. Zavadskas, E. K., Turkis, Z. (2008), Quality Attributes and Complex Assessment Methodology of Asphalt Mixing Plant”, The Baltic Journal of Road and Bridge Engineering, Vol. 3, No. 3, pp. 161-166.
[8] Zavadskas, E. K., Liias, R., Turskis, Z. (2008), Contractor Selection of Construction in a Competitive Environment”, Journal of Business Economics and Management, Vol. 9, No. 3, pp. 181–187.
[9] Kaplinski, O. (2008), “Usefulness and Credibility of Scoring Methods in Construction Industry”, Journal of Civil Engineering and Management, Vol. 14, No. 1, pp. 21–28.
[10] Zeleny, M. (1982), Multiple Criteria Decision Making, McGraw-Hill, New York, 563 pp.
[11] Kao, C. (2010), “Weight Determination for Consistently Ranking Alternatives in Multiple Criteria Decision Analysis”, Applied Mathematical Modelling, Vol. 34, pp. 1779-1787.
[12] Galand, L., Perny, P. and Spanjaard, O. (2017), “Choquet-based Optimization in Multiobjective Shortest Path and Spanning Tree Problems”, European Journal of Operational Research, Vol. 2, pp. 303-315.
[13] Avigad, G. and Moshaiov, A. (2011), “Simultaneous Concept-Based Evolutionary Multi-Objective Optimization”, Applied Soft Computing, Vol. 11, No. 1, pp. 193-207.
[14] Li, R. and Leung, Y. (2011), “Multi-Objective Route Planning for Dangerous Goods Using Compromise Programming”, Journal of Geographical Systems, Vol. 13, No. 3, pp. 249-271.
[15] Adeyeye, A. D., Odu, G. O. and Charles-Owaba, O. E. (2015), “Adaptation of Compromise Programming Approach for Multi-criteria Material Selection”, American Journal of Engineering Research (AJER), Vol. 4, No. 6, pp. 112-122.
[16] Fan, Y., Xinming, Q. and Ping, H (2012), “Fire Safety Assessment of underground builing based on Grey Relational Analysis”, Procedia Engineering, Vol. 45, pp. 89-95.
[17] Gai, C., Weng, W. and Yuan, H. (2014), “GIS-Based Forest Fire Risk Assessment and Mapping”, Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference,
[18] Saaka M. and Glover K. (2017), “Assessing the Prevalence of Malaria and the Use of Insecticide Treated Bed Nets in Ghana” UDS International Journal of Development, Vol. 4 No. 1, pp. 12
[19] Dickson, K. B. and Benneh, G. (2004), A New Geography of Ghana, Longmans Group Limited, London, 5th edition, pp. 23 – 45.
[20] Yakubu, I., Mireku-Gyimah, D. and Duker, A. A., (2013), “Multi-Spatial Criteria Modelling of Fire Risk and Hazard in the West Gonja Area of Ghana”, Research Journal of Environmental and Earth Sciences, Vol. 5, No. 5, pp. 267-277.
[21] Saaty, L. T. (1990), “An Exposition of the AHP in Reply to the Paper “Remarks on the Analytical Hierarchy Process””, Management Science, Vol. 38, No. 3, pp. 259-268.
[22] Abdullah, L. and Azman, F. N. (2011), “Weights of Obesity Factors Using Analytical Hierarchy Process”, IJRRAS, Vol. 7, No. 1, pp. 57-63.
[23] Lazim A. and Filzah S (2016), “Identifying Type of Prostate Cancer using Analytic Hierarchy Process”, Journal of Emerging Trends in Computing and Information Sciences, Vol. 7, No. 2, pp. 27-32.
[24] Pantouvakis, J. and Manoliadis, O. G. (2008), “A compromise Programming Model for Site Selection of Borrow Pits”, Taylor and Francis, Vol. 26, pp. 433-446.
[25] Manoliadis, O. G. (2001), “A Two Level Multicriteria DSS for Landfill Site Selection”, Environmental Protection and Ecology, Vol. 2, No. 2, pp. 45–9.
[26] Simonovic, S. P. (1988), “Application of Water Resources Systems Concepts to the Formulation of a Water Master Plan”, Water International, Vol. 15, pp. 37–51.
[27] Silverman, J., Steuer, R. E. and Whisman, A. W. (1988), “A Multi-period, Multiple criteria Optimization System for Manpower Planning”, European Journal of Operational Research, Vol. 34, pp. 160–70.
[28] Tkach, R. J. and Simonovic, S. P. (1997), “A New Approach to Multi-criteria Decision Making in Water Resources”, Journal of Geographical Information, Vol. 1, pp. 25–43.
[29] Bardossy, A., Bogardi, I. and Duckstein, L. (1985), Composite Programming as an Extension of Compromise Programming, in Serfini, P. (ed.) Mathematics of Multiple Objective Optimization”, Springer-Verlag, Vol. 289, pp. 375–408.
[30] Diaz-Balteiro, L., Voces, R. and Romero, C. (2011), “Making Sustainability Rankings Using Compromise Programming. An Application to European Paper Industry”, Silva Fennica, Vol. 45, No. 4, pp. 761–773.
[31] Zhang, W. H. (2003), “A Compromise programming method using multibounds formulation and dual approach for multicriteria structural optimization”, International Journal for numerical Methods in Engineering, Vol. 58, No.4, pp. 661-678.
[32] Yu, P. L. (1973), “A Class of Solutions for Group Decision Problems”, Management Science, Vol. 19, No. 8, pp. 936-946.
[33] Julong, D. (1989), “Introduction to Grey System Theory”, The Journal of Grey System, Vol. 1, Nol. 1, pp. 1-24.
[34] Hsiao, S. Lin, H. and Ko. Y. (2017), “Application of Grey Relational Analysis to Decision-Making during Product Development”, EURASIA Journal of Mathematics, Science and Technology Education, Vol. 13, No. 6, pp. 2581-2600.
[35] Ertugrul, I., Oztas, T., Ozcil A. and Oztas, G. Z. (2016), “Grey Relational Analysis Approach in Academic Performance Comparison of University: A Case Study of Turkish Universities”, European Scientific Journal, pp. 128-139.