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Multi-objective evolutionary algorithms
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Part 2 of ebook "Introduction to evolutionary computing (Second edition)" provides readers with contents including: Chapter 7 - Parameters and parameter tuning; Chapter 8 - Parameter control; Chapter 9 - Working with evolutionary algorithms; Chapter 10 - Hybridisation with other techniques, memetic algorithms; Chapter 11 - Nonstationary and noisy function optimisation; Chapter 12 - Multiobjective evolutionary algorithms; Chapter 13 - Constraint handling;...
164p
daonhiennhien
03-07-2024
1
1
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This paper presents the integrated, multiobjective, multi-product, multi-echelon environment optimization model for steel distribution network. Model formulated covers retail supply chain processes applicable for steel products starting from production of different grades of material, its transfer to company warehouse, then to distributor warehouse cum service centre and finally to retailer
10p
longtimenosee10
26-04-2024
3
1
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This study proposes the application of an evolutionary algorithm in optimizing the construction process with Gantt charts to meet the multi-target requirements. The multi-target function is built based on single target criteria and is used as the cost function of the evolutionary algorithm. Application results with specific projects show multi-target optimization by using evolutionary algorithms that allow automatically building a suitable and balanced construction schedule between targets.
11p
visharma
20-10-2023
6
4
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This demonstrates that using the multi-objectives approach with a combination of the Discrete Differential Evolution mutation and the Memetic Algorithm evolutionary is a suitable approach for solving multiobjectives CPMP.
20p
spiritedaway36
28-11-2021
13
4
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This paper we proposed the usage of a multi-objective algorithm to solve Vietnamese spam detection problems. The problem taking into account the specific Vietnamese, English and Chinese characterises was analyzed, then a multiobjective problem for the Vietnamese spam detection was modelled.
14p
viengland2711
23-07-2019
20
0
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This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation.
138p
phoebe75
19-02-2013
48
5
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