Creating Alternatives for Stochastic Water Resources Management Decision-Making Using a Firefly Algorithm-Driven Simulation-Optimization Approach 

Authors

  • Ting Cao York University, Toronto, ON, M3J 1P3, Canada
  • Julian Scott Yeomans York University, Toronto, ON, M3J 1P3, Canada

DOI:

https://doi.org/10.15377/2410-3624.2016.03.02.2

Keywords:

Isotadeonal, biofilm, Polygonum punctatum, Pseudomonas aeruginosa, Staphylococcus aureus.

Abstract

Abstract: In solving complex water resources management (WRM) problems, it can prove preferable to create numerous quantifiably good alternatives that provide multiple, disparate perspectives. This is because WRM normally involves multifaceted problems that are riddled with incompatible performance objectives and contain inconsistent design requirements, which are very difficult to quantify and capture when supporting decisions must be constructed. By producing a set of options that are maximally different from each other in terms of their unmodelled variable structures, it is hoped that some of these dissimilar solutions may convey very different perspectives that may serve to address these unmodelled objectives. In environmental planning, this maximally different option production procedure is referred to as modelling-to-generate-alternatives (MGA). In addition, many components of WRM problems possess extensive stochastic uncertainty. This study provides a firefly algorithm-driven simulation-optimization approach for MGA that can be used to efficiently create multiple solution alternatives to problems containing significant stochastic uncertainties that satisfy required system performance criteria and yet are maximally different in their decision spaces. This algorithmic approach is both computationally efficient and simultaneously produces a prescribed number of maximally different solution alternatives in a single computational run of the procedure. The effectiveness of this stochastic MGA approach for creating alternatives in “real world”, environmental policy formulation is demonstrated using a WRM case study.

Author Biographies

Ting Cao, York University, Toronto, ON, M3J 1P3, Canada

OMIS Area, Schulich School of Business

Julian Scott Yeomans, York University, Toronto, ON, M3J 1P3, Canada

OMIS Area, Schulich School of Business

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Published

2017-01-30

How to Cite

1.
Ting Cao, Julian Scott Yeomans. Creating Alternatives for Stochastic Water Resources Management Decision-Making Using a Firefly Algorithm-Driven Simulation-Optimization Approach . Glob. Environ. Eng. [Internet]. 2017Jan.30 [cited 2021Sep.16];3(2):49-62. Available from: https://www.avantipublishers.com/jms/index.php/tgevnie/article/view/1012

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Articles