genetic algorithm-based multi-objective optimisation
Multi objective genetic algorithm optimisation approach for the geometrical design of an active noise control systems
... The application of the MOGA to ANC system design demonstrates the need for some degree of preference articulation in Pareto-based evolutionary optimisation, but the speed of execution then becomes an ...
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Fault detection and diagnosis of a plastic film extrusion process
... is based on the parity relations and thus requires solving a multi-objective optimisation ...A genetic algorithm, which is an evolutionary algorithm, has been utilised for ...
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Multi-objective optimisation using the Bees Algorithm
... combine objective function and constraint information into a scalar value that is used as the fitness function o f a ...regarding Multi- Objective Optimisation with Artificial Immune Systems ...
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A simulated annealing based genetic local search algorithm for multi objective multicast routing problems
... population based meta-heuristics also appear in the multi- objective multicast routing ...colony optimisation algorithms in (Diego and Baran 2005) have shown to find more non-dominated ...
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A multi tier adaptive grid algorithm for the evolutionary multi objective optimisation of complex problems
... A large number of the second generation of Pareto-based MOEAs include advanced methods of estimating the pop- ulation density, inspired by statistical density estimation techniques. These can be mainly classified ...
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Fault detection and diagnosis of a plastic film extrusion process
... A multi-objective optimisation problem must be solved in order for the residual to be sensitive to faults but insensitive to disturbances and modelling ...a genetic algorithm for ...
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Evolving Fault Tolerant Robotic Controllers
... parameter based multi-objective optimisation ...have genetic redundancy in the genome encoding, such as NEAT/HyperNEAT in the ANN structure optimisation domain in terms of ...
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Practical application of penalty-free evolutionary multi-objective optimisation of water distribution systems
... a multi-objective evolutionary algorithm introduced by Siew and Tanyimboh (2012b) that is based on the Non-dominated Sorting Genetic Algorithm II (Deb et ...penalty-free ...
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An overview of population-based algorithms for multi-objective optimisation
... optimization algorithm can be traced back to (Holland 1962) as a mixture of automata theory and theoretical ...(or objective) function, dictates which individuals in the population would be fit to enter the ...
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Model-based controller design for a plastic film extrusion process
... a multi-objective optimisation through the application of a genetic algorithm and simulation results are presented in this paper demonstrating improvements that can be achieved by the ...
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A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems
... Pareto- based MOEAs include advanced methods of estimating the population density, inspired by statistical density estimation ...Immune-Genetic- Algorithm (HIGA) Istin et al (2011), which uses an im- ...
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Optimization of a multi-objective-multi period traveling salesman problem with pickup and delivery using genetic algorithm
... The alteration from an industrial based economy to a service based economy has been proceeding in most of the developed countries over past years. As a good instance, service industry has been continuously ...
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An investigation of multi-objective hyper-heuristics for multi-objective optimisation
... computational optimisation problems by performing a search over the space of heuristics rather than searching the solution space ...the algorithm by combining the strength of each heuristic and making up ...
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A knowledge-based NSGA-II approach for scheduling in virtual manufacturing cells
... which are dynamically generated and controlled and are not necessarily transposed into physical proximity (McLean et al., 1982). The grouping is based on a predefined logic and only exists in the production ...
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A multi-objective genetic graph-based clustering algorithm with memory optimization
... (it supposes, without loss of generality, that the nodes are numerically ordered), the algorithm generates two list: the first initially contains all nodes and the second is empty (see line 1 of Algorithm ...
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A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection
... lexicographic multi-objective algorithms is to assign different priorities to different objectives and optimizing each of the objectives in order of their ...one objective is more important than ...
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A Hybrid Multi-objective Extremal Optimisation Approach for Multi-objective Combinatorial Optimisation Problems
... hybrid multi-objective extremal optimisation (HMEO) proposal is presented herein which finds solutions through the collaborative use of EO with a local search framework, both suitable (in principle) ...
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Genetic Algorithm Based Hybrid Approach to Solve Multi-Objective Assignment Problem
... using genetic algorith ...hybrid genetic algorith m to solve bi-criteria assignment ...between genetic algorithm and linear progra mming method to generate the set of non supported efficient ...
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Web Log Mining Based on Soft Clustering and Multi-Objective Genetic Algorithm
... Abstract: Web mining can be broadly defined as discovery and analysis of useful information from the World Wide Web. Web Usage Mining can be described as the discovery and analysis of user accessibility pattern, during ...
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Physical programming for preference driven evolutionary multi-objective optimization
... Multi-objective optimisation design (MOOD) procedures are generate first choose later (GFCL) holistic strategies for multi-objective problems ...A multi-objective problem ...
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