Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62272
Title: Heuristics-guided evolutionary approach to multiobjective generation scheduling
Authors: Srinivasan, D. 
Tettamanzi, A.
Keywords: Heuristics-guided evolutionary algorithm
Multiobjective generation scheduling
Issue Date: 1996
Source: Srinivasan, D.,Tettamanzi, A. (1996). Heuristics-guided evolutionary approach to multiobjective generation scheduling. IEE Proceedings: Generation, Transmission and Distribution 143 (6) : 553-559. ScholarBank@NUS Repository.
Abstract: A novel approach for multiobjective generation scheduling is presented. The work reported employs a simple heuristics-guided evolutionary algorithm to generate solutions to this nonlinear constrained optimisation problem where the objectives are mutually conflicting and equally important. The algorithm produces a cost-emission frontier of pareto-optimal solutions, any of which can be selected based on the relative preference of the objectives. Within this framework, an efficient search algorithm has been developed to deal with the combinatorial explosion of the search space such that only feasible schedules are generated based on heuristics. This approach has been evaluated by successful experiments with three test systems containing 11, 19 and 40 generating units. Attaching importance to heuristics results in producing high quality solutions in a reasonable time for this large scale tightly constrained problem. © IEE, 1996.
Source Title: IEE Proceedings: Generation, Transmission and Distribution
URI: http://scholarbank.nus.edu.sg/handle/10635/62272
ISSN: 13502360
Appears in Collections:Staff Publications

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