[1] | Brugnach, M., Tagg, A., Keil, F., and De Lange, W.J., 2007, Uncertainty matters: computer models at the science-policy interface, Water Resources Management, 21, 1075-1090. |
[2] | Janssen, J.A.E.B., Krol, M.S., Schielen, R.M.J., and Hoekstra, A.Y., 2010, The effect of modelling quantified expert knowledge and uncertainty information on model-based decision making, Environmental Science and Policy, 13(3), 229-238. |
[3] | Matthies, M., Giupponi, C., and Ostendorf, B., 2007, Environmental decision support systems: Current issues, methods and tools, Environmental Modelling and Software, 22(2), 123-127. |
[4] | Mowrer, H.T., 2000, Uncertainty in natural resource decision support systems: Sources, interpretation, and importance, Computers and Electronics in Agriculture, 27(1-3), 139-154. |
[5] | Walker, W.E., Harremoes, P., Rotmans, J., Van der Sluis, J.P., Van Asselt, M.B.A.P., Janssen, J.A.E.B., and Krayer von Krauss, M.P., 2003, Defining uncertainty – a conceptual basis for uncertainty management in model-based decision support, Integrated Assessment, 4(1), 5-17. |
[6] | Loughlin, D.H., Ranjithan, S.R., Brill, E.D., and Baugh, J.W., 2001, Genetic algorithm approaches for addressing unmodelled objectives in optimization problems, Engineering Optimization, 33(5), 549-569. |
[7] | Yeomans, J.S., and Gunalay, Y., 2011, Simulation-optimization techniques for modelling to generate alternatives in waste management planning, Journal of Applied Operational Research, 3(1), 23-35. |
[8] | Brill, E.D., Chang, S.Y., and Hopkins, L.D., 1982, Modelling to generate alternatives: the HSJ approach and an illustration using a problem in land use planning, Management Science, 28(3), 221-235. |
[9] | Baugh, J.W., Caldwell, S.C., and Brill, E.D., 1997, A mathematical programming approach for generating alternatives in discrete structural optimization, Engineering Optimization, 28(1), 1-31. |
[10] | Zechman, E.M., and Ranjithan, S.R., 2007, Generating alternatives using evolutionary algorithms for water resources and environmental management problems, Journal of Water Resources Planning and Management, 133(2), 156-165. |
[11] | Gunalay, Y., Yeomans, J.S., and Huang, G.H., 2012, Modelling to generate alternative policies in highly uncertain environments: An application to municipal solid waste management planning, Journal of Environmental Informatics, 19(2), 58-69. |
[12] | Imanirad, R., and Yeomans, J.S., 2013, “Modelling to Generate Alternatives Using Biologically Inspired Algorithms”. In Yang, X.S. (Ed.), Swarm Intelligence and Bio-Inspired Computation: Theory and Applications, Amsterdam: Elsevier, 313-333. |
[13] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2012, A computationally efficient, biologically-inspired modelling-to-generate-alternatives method, Journal on Computing, 2(2), 43-47. |
[14] | Yeomans, J.S., 2018, “An Efficient Computational Procedure for Simultaneously Generating Alternatives to an Optimal Solution Using the Firefly Algorithm”. In Yang X.S. (Ed.), Nature-Inspired Algorithms and Applied Optimization. New York: Springer, 261-273. |
[15] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2012, A co-evolutionary, nature-inspired algorithm for the concurrent generation of alternatives, Journal on Computing, 2(3), 101-106. |
[16] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2013, Modelling-to-generate-alternatives via the firefly algorithm, Journal of Applied Operational Research, 5(1), 2013, 14-21. |
[17] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2013, A Concurrent Modelling to Generate Alternatives Approach Using the Firefly Algorithm, International Journal of Decision Support System Technology, 5(2), 33-45. |
[18] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2013, A biologically-inspired metaheuristic procedure for modelling-to-generate-alternatives, International Journal of Engineering Research and Applications, 3(2), 1677-1686. |
[19] | Yeomans, J.S., 2017, Simultaneous Computing of Sets of Maximally Different Alternatives to Optimal Solutions, International Journal of Engineering Research and Applications, 7(9), 21-28. |
[20] | Yeomans, J.S., 2017, An Optimization Algorithm that Simultaneously Calculates Maximally Different Alternatives, International Journal of Computational Engineering Research, 7(10), 45-50. |
[21] | Yeomans, J.S., 2018, Computationally Testing the Efficacy of a Modelling-to-Generate-Alternatives Procedure for Simultaneously Creating Solutions, Journal of Computer Engineering, 20(1), 38-45. |
[22] | Yeomans, J.S., 2017, A Computational Algorithm for Creating Alternatives to Optimal Solutions, Transactions on Machine Learning and Artificial Intelligence, 5(5), 58-68. |
[23] | Yeomans, J.S., 2019, A Simultaneous Modelling-to-Generate-Alternatives Procedure Employing the Firefly Algorithm. In Dey, N. (Ed.), Technological Innovations in Knowledge Management and Decision Support. Hershey, Pennsylvania: IGI Global, 19-33. |
[24] | Yeomans, J.S., 2018, An Algorithm for Generating Sets of Maximally Different Alternatives Using Population-Based Metaheuristic Procedures, Transactions on Machine Learning and Artificial Intelligence, 6(5), 1-9. |
[25] | Fu, M.C., 2002, Optimization for simulation: theory vs. practice, INFORMS Journal on Computing, 14(3), 192-215. |
[26] | Kelly, P., 2002, Simulation optimization is evolving, INFORMS Journal on Computing, 14(3), 223-225. |
[27] | Zou, R., Liu, Y., Riverson, J., Parker, A., and Carter, S., 2010, A nonlinearity interval mapping scheme for efficient waste allocation simulation-optimization analysis, Water Resources Research, 46(8), 1-14. |
[28] | Imanirad, R., Yang, X.S., and Yeomans, J.S., 2016, “Stochastic Decision-Making in Waste Management Using a Firefly Algorithm-Driven Simulation-Optimization Approach for Generating Alternatives”. In. Koziel, S., Leifsson, L., and Yang, X.S. (Eds.), Recent Advances in Simulation-Driven Modeling and Optimization, Heidelberg, Germany: Springer, 299-323. |
[29] | Yeomans, J.S., 2012, Waste management facility expansion planning using simulation-optimization with grey programming and penalty functions, International Journal of Environmental and Waste Management, 10(2/3), 269-283. |
[30] | Yeomans, J.S., 2008, Applications of simulation-optimization methods in environmental policy planning under uncertainty, Journal of Environmental Informatics, 12(2), 174-186. |
[31] | Yeomans, J.S., and Yang, X.S., 2014, Municipal waste management optimization using a firefly algorithm-driven simulation-optimization approach, International Journal of Process Management and Benchmarking, 4(4), 363-375. |
[32] | Linton, J.D., Yeomans, J.S., and Yoogalingam, R., 2002, Policy planning using genetic algorithms combined with simulation: The case of municipal solid waste, Environment and Planning B: Planning and Design, 29(5), 757-778. |
[33] | Yeomans, J.S., 2019, A Bicriterion Approach for Generating Alternatives Using Population-Based Algorithms, WSEAS Transactions on Systems, 18(4), 29-34. |
[34] | Yeomans, J.S., 2019, A Simulation-Optimization Algorithm for Generating Sets of Alternatives Using Population-Based Metaheuristic Procedures, Journal of Software Engineering and Simulation, Forthcoming. |
[35] | Yeomans, J.S., 2019, A Stochastic, Dual-Criterion, Simulation-Optimization Algorithm for Generating Alternatives, Journal of Computer Science Engineering, 5(6), 1-10. |
[36] | Yeomans, J.S., 2019, A Stochastic Multicriteria Algorithm for Generating Waste Management Facility Expansion Alternatives, Journal of Civil Engineering Research, 9(2), 43-50. |
[37] | Maqsood, I.M., Huang, G.H., and Yeomans, J.S., 2005, Water resources management under uncertainty: An interval-parameter fuzzy two-stage stochastic programming approach, European Journal of Operational Research, 167(1), 208-225. |