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Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

Mariano, Adriano Pinto; Borba Costa, Caliane Bastos; de Angelis, Dejanira de Franceshi; Pires Atala, Daniel I.; Maugeri Filho, Francisco; Wolf Maciel, Maria Regina; Maciel Filho, Rubens
Fonte: Berkeley Electronic Press Publicador: Berkeley Electronic Press
Tipo: Artigo de Revista Científica Formato: 28
ENG
Relevância na Pesquisa
37.08%
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Processo FAPESP: 07/00341-1; Processo FAPESP: 06/551779; In this work, the capability of genetic algorithms (GAs) to optimise an alternative fermentation process for the production of biobutanol was assessed. The process consists of three interconnected units, as follows: fermentor, cell retention system (tangential microfiltration) and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The dynamic behaviour of the process is described by a non-linear mathematical model with kinetic parameters determined experimentally, whose non-linearity makes the solution of the optimisation problem difficult through conventional algorithms, thus justifying the use of an evolutionary method based on the GAs. The objective of the optimisation was the search of the process inputs that maximises the productivity of butanol for a desired substrate conversion. The potential of binary and real coded genetic algorithms to solve the optimisation problem was assessed. The GA parameters were evaluated making use of the statistical technique of the factorial design in order to identify the most significant ones to the GAs response and to determine the values of the parameters that improve the GAs performance. With both GA codes similar solutions to the optimisation problem were obtained. However...

Optimisation of a fermentation process for butanol production by particle swarm optimisation (PSO)

Mariano, Adriano Pinto; Borba Costa, Caliane Bastos; de Angelis, Dejanira de Franceschi; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens
Fonte: Wiley-Blackwell Publicador: Wiley-Blackwell
Tipo: Artigo de Revista Científica Formato: 934-949
ENG
Relevância na Pesquisa
37.13%
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Processo FAPESP: 07/00341-1; Processo FAPESP: 06/55177-9; BACKGROUND: The performance of three particle swarm optimisation (PSO) algorithms was assessed in relation to their capability to optimise an alternative fermentation process for the production of biobutanol. The process consists of three interconnected units: fermentor, cell retention system and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The dynamic behaviour of the process was described by a non-linear mathematical model. Four constrained optimisation problems were formulated concerning the operation and design of flash fermentation: (1) maximisation of butanol productivity; (2) maximisation of substrate conversion; (3) and (4) adjustment of operating conditions in the face of problems of fluctuations in the quality of the agricultural raw material and changes in the kinetics of the microorganisms.RESULTS: The design and operation of the flash fermentation process based on the optimisation of productivity, instead of substrate conversion, resulted in a smaller fermentor and provided satisfactory values of operating conditions able to overcome problems of variations in the glucose concentration in the raw material and changes in kinetics.CONCLUSIONS: The differences among the PSO algorithms...

Mathematical optimisation techniques applied to power system operation and planning

Romero, Rubén; Zobaa, Ahmed Faheem; Asada, Eduardo N.; Freitas, Walmir
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Revisão Formato: 393-403
ENG
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Nowadays, power system operation becomes more complex because of the critical operating conditions resulting from the requirements of a market-driven operation. In this context, efficient methods for optimisation of power system operation and planning become critical to satisfy the operational (technical), financial and economic demands. Therefore, the detailed analysis of modern optimisation techniques as well as their application to the power system problems represent a relevant issue from the scientific and technological points of view. This paper presents a brief overview of the developments on modern mathematical optimisation methods applied to power system operation and planning. Copyright © 2007 Inderscience Enterprises Ltd.

Optimisation of viscoelastic treatments using genetic algorithms; Optimização de tratamentos viscoelásticos com algoritmos genéticos

Sher, Branca Rosa Ribeiro Leite de Sousa
Fonte: Universidade de Aveiro Publicador: Universidade de Aveiro
Tipo: Tese de Doutorado
ENG
Relevância na Pesquisa
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Viscoelastic treatments are one of the most efficient treatments, as far as passive damping is concerned, particularly in the case of thin and light structures. In this type of treatment, part of the strain energy generated in the viscoelastic material is dissipated to the surroundings, in the form of heat. A layer of viscoelastic material is applied to a structure in an unconstrained or constrained configuration, the latter proving to be the most efficient arrangement. This is due to the fact that the relative movement of both the host and constraining layers cause the viscoelastic material to be subjected to a relatively high strain energy. There are studies, however, that claim that the partial application of the viscoelastic material is just as efficient, in terms of economic costs or any other form of treatment application costs. The application of patches of material in specific and selected areas of the structure, thus minimising the extension of damping material, results in an equally efficient treatment. Since the damping mechanism of a viscoelastic material is based on the dissipation of part of the strain energy, the efficiency of the partial treatment can be correlated to the modal strain energy of the structure. Even though the results obtained with this approach in various studies are considered very satisfactory...

Stacking sequence optimisation of composite panels subjected to slamming impact loads using a genetic algorithm

Khedmati,Mohammad Reza; Sangtabi,Mohammad Rezai; Fakoori,Mehdi
Fonte: Associação Brasileira de Ciências Mecânicas Publicador: Associação Brasileira de Ciências Mecânicas
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2013 EN
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Optimisation of stacking sequence for composite panels under slamming impact loads using a genetic algorithm method is studied in this paper. For this purpose, slamming load is assumed to have a uniform distribution with a triangular-pulse type of intensity function. In order to perform optimisation based on a genetic algorithm, a special code is written in MATLAB software environment. The optimiser is coupled with the commercial software ANSYS in order to analyse the composite panel under study and calculate the central deflection. After validation, different cases of stacking sequence optimisation are investigated for a variety of composite panels. The investigations include symmetric as well as asymmetric conditions of stacking sequence. Results obtained from these analyses reveal the fact that the adopted approach based on a genetic algorithm is highly capable of performing such optimisations.

Max-min ant system applied to water distribution system optimisation

Zecchin, A.; Maier, H.; Simpson, A.; Roberts, A.; Berrisford, M.; Leonard, M.
Fonte: The Modelling and Simulation Soc of Aust and NZ Inc; IAS, ANU, Canberra Publicador: The Modelling and Simulation Soc of Aust and NZ Inc; IAS, ANU, Canberra
Tipo: Conference paper
Publicado em //2003 EN
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Water distribution systems (WDSs) are costly infrastructure in terms of materials, construction, maintenance and energy requirements. Much attention has been given to the application of optimisation methods to minimise the costs associated with such infrastructure. Historically, traditional optimisation techniques have been used, such as linear and non-linear programming, but within the past decade the focus has shifted to the use of Evolutionary Algorithms, for example Genetic Algorithms, Simulated Annealing and more recently Ant Colony Optimisation (ACO). Advancements on the basic formulation of ACO have been developed, these advancements differ from one another in their utilisation of information learned about the search-space to manage the trade-off between exploitation and exploration in the algorithms searching behaviour. Exploration is the algorithms ability to search broadly through the problems search space and exploitation is the algorithms ability to search locally around good solutions that have been previously found. One such advanced ACO algorithm, which is presented within this paper, is the Max-Min Ant System (MMAS). This algorithm encourages local searching around the best solution found in each iteration while implementing methods to slow convergence and facilitate exploration. The performance of MMAS is compared to that of the most basic ACO formulation Ant System (AS) for two commonly used WDS case studies. The sophistication of MMAS is shown to be effective as it outperforms AS for both case studies and performs competitively in comparison to other algorithms in the literature.; http://www.mssanz.org.au/MODSIM03/MODSIM03.htm; Aaron C. Zecchin...

Trajectory design, optimisation and guidance for reusable launch vehicles during the terminal area flight phase.

Chartres, James T. A.
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado Formato: 228283 bytes; 2650435 bytes; 735674 bytes; application/pdf; application/pdf; application/pdf
Publicado em //2007 EN
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The next generation of reusable launch vehicles (RLVs) require significant improvements in guidance methods in order to reduce cost, increase safety and flexibility, whilst allowing for possible autonomous operation. Research has focused on the ascent and hypersonic re-entry flight phases. This thesis presents a new method for trajectory design, optimisation and guidance of RLVs during the terminal area flight phases. The terminal area flight phase is the transitional phase from hypersonic re-entry to the approach and landing phase. The trajectory design, optimisation and guidance methods within this thesis are an evolution of previous work conducted on the ascent and re-entry flight phases of RLVs. The methods are modified to incorporate the terminal area flight phase through the adaption of the problem definition and the inclusion of the speed brake setting as a steering parameter. The methods discussed and developed in this thesis are different to previous methods for the terminal area flight phase as they encompass optimisation, trajectory design and guidance based on the definition of the steering parameters. The NLPQL nonlinear optimiser contained within the International Mathematics Standards Library (IMSL) is utilised for trajectory design and optimisation. Real-time vehicle guidance is achieved using the restoration steps of an accelerated Gradient Projection Algorithm (GPA). The methods used are evaluated in a three degrees of freedom (3DOF) simulation environment. To properly evaluate the programs and gain a better understanding of the terminal area flight phase...

Multi-objective portfolio optimisation of upstream petroleum projects.

Aristeguieta Alfonzo, Otto D.
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2008
Relevância na Pesquisa
37.13%
The shareholders of E&P companies evaluate the future performance of these companies in terms of multiple performance attributes. Hence, E&P decision makers have the task of allocating limited resources to available project proposals to deliver the best performance on these various attributes. Additionally, the performance of these proposals on these attributes is uncertain and the attributes of the various proposals are usually correlated. As a result of the above, the E&P portfolio optimisation decision setting is characterised by multiple attributes with uncertain future performance. Most recent contributions in the E&P portfolio optimisation arena seek to adapt modern financial portfolio theory concepts to the E&P project portfolio selection problem. These contributions generally focus on understanding the tradeoffs between risk and return for the attribute NPV while acknowledging the presence of correlation among the assets of the portfolio. The result is usually an efficient frontier where one objective is set over the expected value of the NPV and the other is set over a risk metric calculated from the same attribute where, typically, the risk metric has a closed form solution (e.g., variance, standard deviation, semi-standard deviation). However...

Real-coded genetic algorithm parameter setting for water distribution system optimisation.

Gibbs, Matthew S.
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2008
Relevância na Pesquisa
37.22%
The management of Water Distribution Systems (WDSs) involves making decisions about various operations in the network, including the scheduling of pump operations and setting of disinfectant dosing rates. There are often conflicting objectives in making these operational decisions, such as minimising costs while maximising the quality of the water supplied. Hence, the operation of WDSs can be very difficult, and there is generally considerable scope to improve the operational efficiency of these systems by improving the associated decision making process. In order to achieve this goal, optimisation methods known as Genetic Algorithms (GAs) have been successfully adopted to assist in determining the best possible solutions to WDS optimisation problems for a number of years. Even though there has been extensive research demonstrating the potential of GAs for improving the design and operation of WDSs, the method has not been widely adopted in practice. There are a number of reasons that may contribute to this lack of uptake, including the following difficulties: (a) developing an appropriate fitness function that is a suitable description of the objective of the optimisation including all constraints, (b) making decisions that are required to select the most appropriate variant of the algorithm...

Reservoir characterisation using artificial bee colony optimisation

Sayyafzadeh, M.; Haghighi, M.; Bolouri, K.; Arjomand, E.
Fonte: Australian Petroleum Production and Exploration Association Publicador: Australian Petroleum Production and Exploration Association
Tipo: Artigo de Revista Científica
Publicado em //2012 EN
Relevância na Pesquisa
37.13%
To obtain an accurate estimation of reservoir performance, the reservoir should be properly characterised. One of the main stages of reservoir characterisation is the calibration of rock property distributions with flow performance observation, which is known as history matching. The history matching procedure consists of three distinct steps: parameterisation, regularisation and optimisation. In this study, a Bayesian framework and a pilot-point approach for regularisation and parameterisation are used. The major focus of this paper is optimisation, which plays a crucial role in the reliability and quality of history matching. Several optimisation methods have been studied for his¬tory matching, including genetic algorithm (GA), ant colony, particle swarm (PS), Gauss-Newton, Levenberg-Marquardt and Limited-memory, Broyden-Fletcher-Goldfarb-Shanno. One of the most recent optimisation algorithms used in different fields is artificial bee colony (ABC). In this study, the application of ABC in history matching is investigated for the first time. ABC is derived from the intelligent foraging behaviour of honey bees. A colony of honey bees is comprised of employed bees, onlookers and scouts. Employed bees look for food sources based on their knowledge...

Signal processing and optimisation of MIMO radar.

Balzan, Luke Anthony
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2012
Relevância na Pesquisa
37.26%
This thesis presents a background to and a series of interesting and novel results for a particular proposed model for narrowband MIMO radar systems. The proposed model is both novel and unique, comprising closely-spaced antenna arrays that transmit orthogonally-coded waveforms, and can be seen as a logical extension to existing models for conventional single-input, single-output radar systems. Signal processing and optimisation is performed on the proposed system with a view to yield enhanced estimation and tracking performance. The proposed signal and likelihood estimation models have been thoroughly defined, with a number of important approximations and simplifications to the models gained through the use and exploitation of orthogonally-coded waveforms. All approximations and assumptions have been justified through the use of simulated examples. The Cramer-Rao bound for the models is derived and verified as correct through the use of simulated data. Through comparison of the Cramer-Rao bound to statistical estimation variances obtained through extensive simulations, the proposed models are shown to be efficient, thereby demonstrating the validity of the bound to be used as performance metric for optimisation. With the knowledge that the proposed MIMO radar system is efficient...

Evolutionary algorithms for supply chain optimisation.

Ibrahimov, Maksud
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2012
Relevância na Pesquisa
37.01%
Many real-world problems can be modelled as a combination of several interacting components. Methods based on Evolutionary Algorithms seem to be appropriate for handling such problems, but they have not been extensively researched in such domains. In this thesis we study the applicability of Evolutionary Algorithms for today’s high complexity real-world problems which consist of several interacting components. A natural source of such problems emerged from supply chain management problems which consist of several interacting components, and are also generally non-linear, heavily constrained, and involve many variables. We aim to study possible approaches for supply chain optimisation problems that seamlessly integrate algorithms addressing the local components, under the framework of global optimisation.; Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2012

Optimisation and economical evaluation of infill drilling in CSG reservoirs using a multi-objective genetic algorithm

Salmachi, A.; Sayyafzadeh, M.; Haghighi, M.
Fonte: Australian Petroleum Production and Exploration Association; Australia Publicador: Australian Petroleum Production and Exploration Association; Australia
Tipo: Conference paper
Publicado em //2013 EN
Relevância na Pesquisa
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Water production in the early life of Coal Seam Gas (CSG) recovery makes these reservoirs different from conventional gas reservoirs. Normally, a large amount of water is produced during the early production period, while the gas-rate is negligible. It is essential to drill infill wells in optimum locations to reduce the water production and increase the gas recovery. To optimise infill locations in a CSG reservoir, an integrated framework is developed to couple the reservoir flow simulator (ECLIPSE) and the genetic algorithm (GA) optimisation toolbox of (MATLAB). In this study, the desired objective function is the NPV of the infill drilling. To obtain the economics of the infill drilling project, the objective function is split into two objectives. The first objective is the gas income; the second objective is the cost associated with water production. The optimisation problem is then solved using the multi-objective solver. The economics of the infill drilling program is investigated for a case study constructed based on the available data from the Tiffany unit in San Juan basin when gas price and water treatment cost are variable. Best obtained optimal locations of 20 new wells in the reservoir are attained using this optimisation framework to maximise the profit of this project. The results indicate that when the gas price is less than $2/Mscf...

Induction motor parameters estimation and faults diagnosis using optimisation algorithms.

Duan, Fang
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2015
Relevância na Pesquisa
37.01%
Induction motors are the most widespread rotating electric machines in industry due to their efficient and cost-effective performance. Induction motors are used to mainly operate at the constant speed since the rotor speed depends on the supply frequency. The development of power electronic devices and converter technologies has revolutionized the adjustable-speed induction motor drives. For most high-performance control methods, the effective motor control requires precise knowledge of the motor’s parameters, which are usually obtained from manufacturers. However, the manufacturers describe these parameters under starting or full-loading condition only, instead of the normal operating conditions. It is well known that motor parameters are influenced by not only the load level but also environmental factors, such as temperature, humidity and lubricant viscosity. The first part of the thesis describes the application of the sparse grid optimisation method in solving the induction motor parameter estimation problem. Kernel of the method is the efficient search in minimising the cost function on the grid created by using the Hyperbolic Cross Points (HCPs). The cost function quantifies the difference between simulation results and measurement results. Within model reference adaptive system (MRAS) framework...

Securing route optimisation in NEMO

Calderón, María; Bernardos, Carlos J.; Bagnulo, Marcelo; Soto, Ignacio
Fonte: IEEE Publicador: IEEE
Tipo: Conferência ou Objeto de Conferência Formato: text/plain; application/pdf
Publicado em /04/2005 ENG
Relevância na Pesquisa
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The network mobility (NEMO) basic support protocol enables mobile networks to change their point of attachment to the Internet, while preserving established sessions of the nodes within the mobile network. When only a nonnested mobile network is considered, the so-called triangle routing is the main problem that should be faced. In mobile IPv6, the route optimisation mechanism solves this problem, and the return routability mechanism aims to limit the security concerns originated because of the route optimisation. Nowadays return routability is considered a weak solution (i.e., based on strong assumptions). In this article we explore different approaches to route optimisation in NEMO and we devise how to adapt some of the terminal mobility solutions to a NEMO environment, where, as we propose, a delegation of signalling rights from the mobile network node to the mobile router is necessary.; Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc,and Wireless Networks. 4-6 April 2005. Riva del Garda, Trentino, Italy

Ship scheduling with time-varying draft restrictions: a case study in optimisation with time-varying costs

Kelareva, Elena
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Thesis (PhD); Doctor of Philosophy (PhD)
EN_AU
Relevância na Pesquisa
37.26%
In the last few decades, optimisation problems in maritime transportation have received increased interest from researchers, since the huge size of the maritime transportation industry means that even small improvements in efficiency carry a high potential benefit. One area of maritime transportation that has remained under-researched is the impact of draft restrictions at ports. Many ports have restrictions on ship draft (distance between the waterline and the keel) which vary over time due to variation in environmental conditions. However, existing optimisation problems in maritime transportation ignore time variation in draft restrictions, thus potentially missing out on opportunities to load more cargo at high tide when there is more water available for the ship to sail in, and more cargo can be loaded safely. This thesis introduces time-varying restrictions on ship draft into several optimisation problems in the maritime industry. First, the Bulk Port Cargo Throughput Optimisation Problem is introduced. This is a novel problem that maximises the amount of cargo carried on a set of ships sailing from a draft-restricted bulk export port. A number of approaches to solving this problem are investigated, and a commercial system - DUKC Optimiser - based on this research is discussed. The DUKC Optimiser system won the Australia-wide NASSCOM Innovation Student Award for IT-Enabled Business Innovation in 2013. The system is now in use at Port Hedland...

The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation

Corus, D.; Lehre, P.; Neumann, F.
Fonte: ACM; online Publicador: ACM; online
Tipo: Conference paper
Publicado em //2013 EN
Relevância na Pesquisa
37.08%
Bi-level optimisation problems have gained increasing inter- est in the field of combinatorial optimisation in recent years. With this paper, we start the runtime analysis of evolu- tionary algorithms for bi-level optimisation problems. We examine the NP-hard generalised minimum spanning tree problem and analyse the two approaches presented by Hu and Raidl [7] in the context of parameterised complexity (with respect to the number of clusters) that distinguish each other by the chosen representation of possible solutions. Our results show that a (1+1) EA working with the spanning nodes representation is not a fixed-parameter evolutionary algorithm for the problem, whereas the global structure rep- resentation enables to solve the problem in fixed-parameter time. Furthermore, we present hard instances for each ap- proach and show that the two approaches are highly com- plementary by proving that they solve each other’s hard in- stances very efficiently.; Dogan Corus, Per Kristian Lehre, Frank Neumann

Shape optimisation with multiresolution subdivision surfaces and immersed finite elements

Bandara, Kosala; R?berg, Thomas; Cirak, Fehmi
Fonte: Elsevier Publicador: Elsevier
Tipo: Article; accepted version
EN
Relevância na Pesquisa
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This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.cma.2015.11.015; We develop a new optimisation technique that combines multiresolution subdivision surfaces for boundary description with immersed finite elements for the discretisation of the primal and adjoint problems of optimisation. Similar to wavelets multiresolution surfaces represent the domain boundary using a coarse control mesh and a sequence of detail vectors. Based on the multiresolution decomposition efficient and fast algorithms are available for reconstructing control meshes of varying fineness. During shape optimisation the vertex coordinates of control meshes are updated using the computed shape gradient information. By virtue of the multiresolution editing semantics, updating the coarse control mesh vertex coordinates leads to large-scale geometry changes and, conversely, updating the fine control mesh coordinates leads to small-scale geometry changes. In our computations we start by optimising the coarsest control mesh and refine it each time the cost function reaches a minimum. This approach effectively prevents the appearance of non-physical boundary geometry oscillations and control mesh pathologies...

Boundary element based multiresolution shape optimisation in electrostatics

Bandara, Kosala; Cirak, Fehmi; Of, G?nther; Steinbach, Olaf; Zapletal, Jan
Fonte: Elsevier Publicador: Elsevier
Tipo: Article; published version
EN
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This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jcp.2015.05.017; We consider the shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. The geometry of the domain is described with subdivision surfaces and different resolutions of the same geometry are used for optimisation and analysis. The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. For shape optimisation the geometry is updated starting from the coarsest control mesh with increasingly finer control meshes. The multiresolution approach effectively prevents the appearance of non-physical geometry oscillations in the optimised shapes. Moreover, there is no need for mesh regeneration or smoothing during the optimisation due to the absence of a volume mesh. We present several numerical experiments and one industrial application to demonstrate the robustness and versatility of the developed approach.; We gratefully acknowledge the support provided by the EU commission through the FP7 Marie Curie IAPP project CASOPT (PIAP-GA-2008-230224). K.B. and F.C. thank for the additional support provided by EPSRC through #EP/G008531/1. J.Z. thanks for the support provided by the European Regional Development Fund in the IT4Innovations Centre of Excellence project (CZ.1.05/1.1.00/02.0070) and by the project SPOMECH ? Creating a Multidisciplinary R&D Team for Reliable Solution of Mechanical Problems...

A comparative study of marriage in honey bees optimisation (MBO) algorithm in multi-reservoir system optimisation

Dariane,Alireza B; Farahmandfar,Zeinab
Fonte: Water SA Publicador: Water SA
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2013 EN
Relevância na Pesquisa
37.2%
Contemporary reservoir systems often require operators to meet a variety of goals and objectives; these in turn frequently complicate water management decision-making. In addition, many reservoir objectives have non-linear relationships and are therefore difficult to implement using traditional optimisation techniques. A practical application of the marriage in honey bees optimisation (MBO) algorithm is being utilised for Karkheh multi-reservoir system, south-western Iran, where supplying irrigation water for agricultural areas and maintaining a minimum in-stream flow for environmental purposes is desired. Optimal monthly reservoir release information by MBO is highlighted and the results compared to those of other evolutionary algorithms, such as the genetic algorithm (GA), ant colony optimisation for continuous domains (ACO R) particle swarm optimisation (PSO) and elitist-mutation particle swarm optimisation (EMPSO). The results indicate the superiority of MBO over the algorithms tested.