Nearly every nucleotide-based computing problem attempted thus far has involved the prearranged assignment of nucleotide sequences to represent bits. However, no general program is yet available to optimize those bit ...
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In this paper we propose and evaluate an evolutionary-based hyper-heuristic approach, called EH-DVRP, for solving hard instances of the dynamic vehicle routing problem. A hyper-heuristic is a high-level algorithm, whi...
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We repurposed an adversarial evolutionary algorithm, Gremlin, from finding driving scenarios where a model of an autonomous vehicle drove poorly to troubleshooting driving quality evaluation criteria. We evaluated the...
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This work primarily aims at introducing an algorithm for surface construction in conjunction with hybrid Growing Grid network and evolutionary Algorithm, called Growing Grid-evolutionary network. The process of surfac...
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An evolutionary algorithm-based robust local structure modeling technique is proposed to improve the performance of the active shape model (ASM). The proposed algorithm can extract boundary of an object under adverse ...
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ISBN:
(纸本)3540213783
An evolutionary algorithm-based robust local structure modeling technique is proposed to improve the performance of the active shape model (ASM). The proposed algorithm can extract boundary of an object under adverse condition, such as noisy corruption, occlusions, and shadow effect. The principle idea of the evolutionary algorithm is to find the global minimum of an objective function by evolving from a large set of populations rather than a single solution which may cause a local minimum. The proposed algorithm has been tested for various images including a sequence of human motion to demonstrate the improved performance of object tracking based on the evolutionary ASM.
General optimal power flow (OPF) is an important problem in the operation of electric power grids. Solution methods to the OPF have been studied extensively that mainly solve steady-state situations, ignoring uncertai...
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In this paper a novel constructive hyperheuristic for CVRP is proposed. This hyperheuristic, called HyperPOEMS, is based on an evolutionary-based iterative local search algorithm. Its inherent characteristics make it ...
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ISBN:
(纸本)9781450319645
In this paper a novel constructive hyperheuristic for CVRP is proposed. This hyperheuristic, called HyperPOEMS, is based on an evolutionary-based iterative local search algorithm. Its inherent characteristics make it capable of autonomously searching a structured space of low-level domain specific heuristics for their suitable combinations that produce good solutions to particular problem instance. Hyper- POEMS was tested on standard benchmarks and compared to two existing constructive hyperheuristic, HHC-VRP and EHH-VRP. The results show that HyperPOEMS outperforms both compared hyperheuristics and produces solutions competitive to solutions obtained by specialized metaheuristics designed for CVRP.
This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along with a user interface designed for it. Ne...
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ISBN:
(纸本)3540650784
This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along with a user interface designed for it. New results are given concerning repair of poor recombination choices during local search. New methods are described and evaluated that allow timetables to be produced which have minimal changes compared to a full or partial reference timetable. The paper concludes with a discussion of scale-up issues, and gives some initial results that are very encouraging.
A real-coded multi-parent tri-hybrid evolutionary algorithm (EA) for problem optimization is presented. The hybrid EA algorithm combines the features of simplex, stochastic relaxation and multi-parent EA reproduction ...
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This paper presents a novel algorithm to solve dynamic multiobjective optimization problems. In dynamic multiobjective optimization problems, multiple objective functions and/or constraints may change over time, which...
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