Skip to main content
Article thumbnail
Location of Repository

A Heuristics-Guided Evolutionary Approach To Multi-Objective Generation Scheduling

By D. Srinivasan and A. Tettamanzi

Abstract

A novel approach for multi-objective generation scheduling is presented. The work reported here employs a simple heuristics-guided evolutionary algorithm to generate solutions to this nonlinear constrained optimization 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 tightlyconstrained problem. 2 I. INTRODUCTION The primary objective of current day operation ..

Year: 1996
OAI identifier: oai:CiteSeerX.psu:10.1.1.19.5849
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://mago.crema.unimi.it/pub... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.