The Chemical Reaction Optimization Approach to Solving the Environmentally Sustainable Network Design Problem. (8th July 2013)

• Record Type: Journal Article
• Authors: Szeto, W. Y.; Wang, Yi; Wong, S. C.; Waller, S. Travis; Bhat, Chandra
• Is Part Of: Computer-aided civil and infrastructure engineering. Volume 29:Number 2(2014:Feb.)
• Page Start: 140
• Page End: 158
• Publication Date: 2013-07-08
• Subjects: Civil engineering -- Data processing -- Periodicals; Computer-aided engineering -- Periodicals; 624.0285
• DOI: 10.1111/mice.12033
• Languages: English
• ISSNs: 1093-9687

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Nowadays, the decision makers in the transportation industry are being urged to incorporate environmental costs into road network design decision making because road traffic affects the environment and health. The design of a road network should not only be cost‐effective but also environmentally sustainable. This article proposes a new network design problem (NDP) that takes both vehicle emissions and noise into account. This proposed environmentally sustainable NDP is formulated as a discrete bilevel program. The lower‐level problem is formulated as user‐equilibrium assignment. The upper‐level problem determines the optimal road capacity expansion to minimize the total costs of emissions, noise, and travel time with the considerations of budgetary and capacity improvement constraints. The proposed problem is solved by an enhanced version of a new meta‐heuristic named Chemical Reaction Optimization (CRO), and its parameters are tuned by our proposed tuning procedure. Two benchmark road networks with different demand levels are used to evaluate the performance of the enhanced CRO and illustrate the properties of the problem. The results show that there were tradeoffs between emissions, noise, and travel time costs, and that the enhanced CRO outperformed Genetic Algorithm (GA) on more than half of the testing scenarios and had a comparable performance on certain test scenarios compared with GA.</p> </abstract>