Non-dominated archiving multi-colony ant algorithm for multi-objective optimization: Application to multi-purpose reservoir operation

Afshar, Abbas; Sharifi, Farid; Jalali, Mohammad Reza

doi:10.1080/03052150802460414

Cited by 54 publications

(23 citation statements)

References 13 publications

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“…As mentioned before, the optimization algorithm that we use to solve the multi objective WLA problem in this paper is the Non-dominated Archiving ACO (NA-ACO) which is proposed by Afshar et al, [1]. By considering the general framework of ACO algorithms, the present multi objective optimization algorithm was developed based on archiving the non-dominated solutions.…”

Section: Non-dominated Archiving Ant Colony Optimization Algorithmmentioning

confidence: 98%

“…Multi-objective Ant Colony Optimization algorithms have recently been applied to solve multi-objective problems [2,8,9,10,12,13]. Present work focuses on the application of powerful and recently developed multi objective ACO technique known as "Non-dominated Archiving ACO" (NA-ACO) proposed by Afshar et al [1] to solve the waste load allocation problem. The goals are defined to minimize the total treatment costs and also the violation index.…”

Section: Introductionmentioning

confidence: 98%

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Waste load allocation using non-dominated archiving multi-colony ant algorithm

Mostafavi

Afshar

2011

Procedia Computer Science

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The optimal Waste Load Allocation (WLA) problem, in general, is a mathematical model incorporating a water quality simulator within the framework of multi objective optimization. The goals are defined to improve the water quality and minimize the total treatment cost of dischargers. The fraction removal levels of dischargers are the decision variables. This paper explores the capabilities of Ant Colony algorithms to solve the optimal Waste Load Allocation as a multi-objective optimization problem. We use QUAL2K as a water quality simulator and a powerful ant colony algorithm known as Non-dominated Archiving Multi-colony Ant Algorithm (NA-ACO). The applicability of the model is demonstrated through a hypothetical case example. Results' location near global optima demonstrates the suitable performance of applied algorithm.

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Section: Non-dominated Archiving Ant Colony Optimization Algorithmmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Waste load allocation using non-dominated archiving multi-colony ant algorithm

Mostafavi

Afshar

2011

Procedia Computer Science

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“…Qin et al (2010) proposed a multiobjective cultured differential evolution (MOCDE) to deal with the reservoir flood control operation problem. Afshara et al (2009) presented a non-dominated archiving ant colony optimization (NA-ACO) algorithm and used to optimize reservoir operating policy with multiple objectives. Li et al (2010) presented a novel multi-objective shuffled frog leaping algorithm (MOSFLA) and applied to solve the reservoir flood control operation problem for the Three Gorges reservoir.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Immune Algorithm with Preference-Based Selection for Reservoir Flood Control Operation

Luo

Chen

Xie

2014

Water Resour Manage

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In reservoir flood control operation, the safety of upstream and downstream of the dam are the main two optimization goals with conflicts. In addition, the irrigation water demands is also an important issue considered by decision makers. Therefore, the dispatching schemes that meet the final water level constraint are preferred. Considering such preference in decision making, a novel preference-based selection operator is developed and combined with immune inspired optimization technique to form the proposed multi-objective immune algorithm with preference-based selection (MOIA-PS) for reservoir flood control operation. The unique of MOIA-PS is that it intends to obtain a set of preferred Pareto optimal solutions that located within a part of preferred area on the Pareto front rather than to find a good approximation of the entire Pareto front as most existing methods did. Experimental results on four typical floods at the Ankang reservoir have indicated that the preferred non-dominated solutions are distributed within a local area of preferred PF region. And the newly designed preference-based selection operator can guide the search of MOIA-PS towards the preferred PF region. Comparing with the outstanding multi-objective evolutionary algorithm NSGAII and the immune inspired multi-objective optimization algorithm NNIA, the proposed MOIA-PS obtains more non-dominated solutions that densely and evenly scattered within the preferred area of the Pareto front. MOIA-PS can find finding dispatching schemes that not only reduce the flood peak significantly and guarantee the dam safety well but also satisfy the irrigation water demands. It is a more efficient use of the computing efforts.

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“…Accordingly, the issue merits further investigation. The bi-divisible ant algorithm developed in this study draws on the procedure proposed by Afshar et al (2009). Establishing a connection between the optimisation model and hydraulic-quality model in order to reach the optimal solution is an integral part of solving the optimisation problem.…”

Section: Solving the Optimisation Problemmentioning

confidence: 99%

Optimum reliable operation of water distribution networks by minimising energy cost and chlorine dosage

Babaei

Tabesh

Nazif

2015

WSA

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In recent decades much attention has been paid to optimal operation of water distribution networks (WDNs). In this regard, the system operation costs, including energy and disinfection chemicals, as well as system reliability should be simultaneously considered in system performance optimisation, to provide the minimum required level of performance in failure condition and to manage economic limitations. In this study, multi-objective optimisation of water distribution network performance in 3 different scenarios was considered. In these scenarios the effects of time-dependent chlorine injection and pump speed, as well as different combinations of objective functions for minimising energy and disinfection costs and for maximising hydraulic reliability and quality-based reliability are incorporated. As the optimisation method, a multi-objective ant colony optimisation (ACO) algorithm was used because of its high efficiency. For better managing the hydraulic behaviour and water quality in the WDN, considering temporal variations of demand, it is suggested to use variable speed pumps (VSP) as well as to inject chlorine at a variable rate. Application of VSP and time-dependent chlorine injection results in improvements such as reduction in energy and disinfection costs, and decrease in disinfection costs in application of HDSM (head-driven simulation method). In HDSM simulation of WDN, a decrease in hydraulic reliability because of shortages in water supply can be mitigated through extra chlorine injection and increase in qualitybased reliability. To deal with this challenge, it is recommended to satisfy the hydraulic reliability first and then to evaluate the quality reliability. Furthermore it is necessary to modify the hydraulic reliability relationship to incorporate different components of the WDN other than pumps. This will provide more reliable results for evaluation of the system performance.

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Non-dominated archiving multi-colony ant algorithm for multi-objective optimization: Application to multi-purpose reservoir operation

Cited by 54 publications

References 13 publications

Waste load allocation using non-dominated archiving multi-colony ant algorithm

Waste load allocation using non-dominated archiving multi-colony ant algorithm

Multi-objective Immune Algorithm with Preference-Based Selection for Reservoir Flood Control Operation

Optimum reliable operation of water distribution networks by minimising energy cost and chlorine dosage

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