Hybrid MODE Algorithms for Optimizing Resource Trade-offs
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This book investigated the potential use of various advanced techniques to improve multiple objective Differential Evolution. Three hybrid multiple objective Differential Evolution (MODE) algorithms that integrate chaotic maps, opposition-based learning technique and Artificial Bee Colony are introduced to solve the resource scheduling problems. Numerous real construction case studies including time-cost-quality tradeoff, time-cost tradeoffs in resource-constrained, time-cost-labor utilization tradeoff and time-cost-environment impact tradeoff problems are used to demonstrate the proposed mode...
This book investigated the potential use of various advanced techniques to improve multiple objective Differential Evolution. Three hybrid multiple objective Differential Evolution (MODE) algorithms that integrate chaotic maps, opposition-based learning technique and Artificial Bee Colony are introduced to solve the resource scheduling problems. Numerous real construction case studies including time-cost-quality tradeoff, time-cost tradeoffs in resource-constrained, time-cost-labor utilization tradeoff and time-cost-environment impact tradeoff problems are used to demonstrate the proposed models
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