Confronting tipping points: Can multi-objective evolutionary algorithms discover pollution control tradeoffs given environmental thresholds?

Ward, V L and Singh, Riddhi and Reed, P M and Keller, K (2015) Confronting tipping points: Can multi-objective evolutionary algorithms discover pollution control tradeoffs given environmental thresholds? Environmental Modelling and Software, 73. pp. 27-43. ISSN 1364-8152

[img] Text (Author version pre-print)
Ward_et_al_EMS_accepted_2015.pdf - Accepted Version
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (3MB) | Request a copy

Abstract

This study contributes a stochastic, multi-objective adaptation of the classic environmental economics Lake Problem as a computationally simple but mathematically challenging benchmarking problem. The Lake Problem considers a hypothetical town by a lake, which hopes to maximize its economic benefit without crossing a nonlinear, and potentially irreversible, pollution threshold. Optimization objectives are maximize economic benefit, minimize phosphorus in the lake, maximize the probability of avoiding the pollution threshold, and minimize the probability of drastic phosphorus loading reductions in a given year. Uncertainty is introduced through a stochastic natural phosphorus inflow. We performed comprehensive diagnostics using six algorithms: the Borg multi-objective evolutionary algorithm (MOEA), MOEA/D, epsilon-MOEA, the Non-dominated Sorting Genetic Algorithm II (NSGAII), epsilon-NSGAII, and Generalized Differential Evolution 3 (GDE3) to evaluate their controllability, reliability, efficiency, and effectiveness. Our results show only the self-adaptive search of the Borg MOEA was capable of performing well on this nontrivial benchmarking problem.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Singh, Riddhihttp://orcid.org/0000-0002-1670-1229
Item Type: Article
Uncontrolled Keywords: Risk management; Environmental thresholds; Tipping points; Multi-objective decision making; Algorithm benchmarking; Lake problem benchmark
Subjects: Civil Engineering > Soil Structure Interaction
Divisions: Department of Civil Engineering
Depositing User: Team Library
Date Deposited: 01 Sep 2015 05:06
Last Modified: 21 Jul 2017 06:45
URI: http://raiith.iith.ac.in/id/eprint/1902
Publisher URL: https://doi.org/10.1016/j.envsoft.2015.07.020
OA policy: http://www.sherpa.ac.uk/romeo/issn/1364-8152/
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 1902 Statistics for this ePrint Item