Ant Colony Optimization for Design of Water Distribution Systems

Maier, Holger R.; Simpson, Angus R.; Zecchin, Aaron C.; Foong, Wai Kuan; Phang, Kuang Yeow; Seah, Hsin Yeow; Tan, Chan Lim

doi:10.1061/(asce)0733-9496(2003)129:3(200)

Cited by 408 publications

(139 citation statements)

References 17 publications

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“…Only two players have not managed to find a feasible solution to the problem (#1 and #13), i.e., a solution that satisfies all minimum pressure requirements. have learned will be assessed qualitatively using the knowledge of the decisions (pipe diameters) implemented in the optimized solution [51].…”

Section: Resultsmentioning

confidence: 99%

“…Savic and Walters [50] used the problem to illustrate the sensitivity of such optimization problems to small changes in the coefficients used in calculating the frictional losses observed in the system, demonstrating solutions ranging from $37.14M to $40.45M. The best-known feasible solution (using the latest EPANET software version) of $38.64M was obtained using the Ant Colony Simulation approach of Maier et al [51].…”

Section: Problem Description and Formulationmentioning

confidence: 99%

“…Although this is a clearly measurable indicator and it can indicate that well-engaged players get closer to the best solutions found, it has its own disadvantages, as some players could achieve a good solution in a small number of attempts. In addition to achieving a good solution, which provides an indication of knowledge gained in the game, the measure of how much the players have learned will be assessed qualitatively using the knowledge of the decisions (pipe diameters) implemented in the optimized solution [51].…”

Section: Criteria For Game Evaluationmentioning

confidence: 99%

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Serious Gaming for Water Systems Planning and Management

Savić

Morley

Khoury

2016

Water

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Water systems planning and management share the same roots with gaming, as they rely on concepts in systems analysis, operations research and decision sciences. This paper focuses on Serious Games (those used for purposes other than mere entertainment), with applications in the area of water systems planning and management. A survey of published work on gaming is carried out with particular attention given to applications of Serious Gaming to water systems planning and management. The survey is also used to identify the principal criteria for the classification of Serious Gaming for water related applications, including application areas, goals, number and type of players, user interface, type of simulation model used, realism of the game, performance feedback, progress monitoring and game portability. The review shows that game applications in the water sector can be a valuable tool for making various stakeholders aware of the socio-techno-economic issues related to managing complex water systems. However, the critical review also indicates a gap that exists in the Serious Game application area with the lack of water distribution system games. A conceptually simple, but computationally elaborate new game for water distribution system analysis, design and evaluation (SeGWADE) is presented in this paper. It has a main goal of finding a least-cost design for a well-known benchmark problem, for which the game environment takes the computational and visualisation burden away from the simulation tool and the player. The game has been evaluated in a classroom environment in which a high degree of player engagement with the game was observed, due to its basic game ingredients and activities, i.e., challenge, play and fun. In addition, a clear improvement in learning has been observed in how players attempted to identify solutions that satisfy the pressure criterion with players readily identifying the proximity of the better solutions to the starting, infeasible configuration. Through applications of Serious Gaming such as this, decision makers can learn about the complexity of the water distribution system design problem, experiment safely using a computer model of a real system, understand conflicting objectives (i.e., minimization of cost and satisfaction of minimum pressure) and develop strategies for coping with complexity without being burdened by the limitations of the ICT technology at their disposal.

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Section: Resultsmentioning

confidence: 99%

Section: Problem Description and Formulationmentioning

confidence: 99%

Section: Criteria For Game Evaluationmentioning

confidence: 99%

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Serious Gaming for Water Systems Planning and Management

Savić

Morley

Khoury

2016

Water

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“…These four typical runs used the same starting random number seeds. The current best known solution for the NYTP case study with a cost of $38.64 million was first reported by Maier et al (2003). This best known solution was found by the runs of the four algorithms presented in Figure 3.…”

Section: New York Tunnels Problemmentioning

confidence: 99%

A Performance Comparison of Differential Evolution and Genetic Algorithm Variants Applied to Water Distribution System Optimization

Zheng

Simpson

Zecchin

2012

World Environmental and Water Resources Congress 2012

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Abstract:The differential evolution (DE) algorithm has been received some attention recently in terms of water distribution system (WDS) optimization. The DE is potentially becoming an alternative optimization tool for WDS design due to its satisfactory search performance. This paper presents a systematic performance comparison between the DE algorithm and the frequently used genetic algorithms (GAs). Two DE variants and two GA variants are compared in this paper in terms of optimizing the design of WDSs. These include the traditional DE, the dither DE algorithm, the traditional GA and the creeping mutation GA. Two well-known benchmark water distribution case studies are used in this study, which are the New York Tunnels Problem and the Hanoi Problem. The results show that the DE variants significantly outperform the GA variants in terms of both the solution quality and efficiency.

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“…where p ij (k, t) is the probability that option l ij is chosen by ant k for variable i at iteration t; τ ij (t) is the pheromone concentration associated with option l ij at iteration t; ij is a heuristic factor for preferring among available options and is an indicator of how good it is for ant k to select option l ij (this heuristic factor is generated as per the problem characteristics and its value is fixed for each option l ij ); and α and β are exponent parameters that control the relative importance of pheromone concentration versus the heuristic factor [10]. Both α and β can take values greater than zero and can be determined by trial and error.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Employing Ant Colony for the Optimal Reduction of Project Risk Severity

Zabel¹,

Georgy

Ibrahim

2014

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-Efforts undertaken in identifying, analyzing and assessing project risks are only made good use of when proper risk treatment strategies are decided upon and pursued. Based on the criteria established by senior management, the risk management plan goes about defining how each risk is to be handled. There are options to that end, including acceptance, avoidance, transfer and mitigation. Whilst these strategies are known to all in the industry, the decision-making process is far from easy. A research was undertaken to optimize risk treatment in construction projects, where both costs and benefits are balanced out at the project level. The paper particularly introduces Ant Colony Optimization (ACO) as a capable algorithm for the balanced selection of risk treatment strategies; that is to reduce the overall risk severity in a project at the minimum cost possible. ACO resembles the real life behavior of ants in their intelligent and guided search for food. The research is being applied in the pipeline construction sector and made use of professional knowledge and project records from a big construction company in the Middle East. The paper further presents an example project to demonstrate how ACO explores the risk treatment alternatives in a project and chooses the optimal set of strategies in such context.

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Ant Colony Optimization for Design of Water Distribution Systems

Cited by 408 publications

References 17 publications

Serious Gaming for Water Systems Planning and Management

Serious Gaming for Water Systems Planning and Management

A Performance Comparison of Differential Evolution and Genetic Algorithm Variants Applied to Water Distribution System Optimization

Employing Ant Colony for the Optimal Reduction of Project Risk Severity

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