摘要
以节能、经济、环保三大原则为目标,给出多目标优化调度模型,用多目标粒子群优化算法对模型进行求解。避免人为设定目标满意度和协调度定义中的理想值,摒弃传统算法中仅以协调度为目标进行问题转化的思路,将满意度约束合理融入协调度,实现模型转化。算例证明,改进的方法能够提高决策方案的可行性,有效减轻决策者负担,适用于多目标优化调度。
Taking energy-saving,environmental protection and economic principles as objectives,an optimal multi-objective scheduling model and multi-objective particle swarm optimization algorithm （MOPSO） are presented. Traditionally,only coordination degree was considered as the final target for transforming the multi-objective optimization problem into a single-objective one. In this paper,model is improved by adding the satisfaction requirements with coordination degree,and removing the ideal value used in the definition of satisfaction and coordination. In such a way,the feasibility of decision-making is improved,and the decision burden of decision-makers is alleviated effectively. Results of the case study proves that the improved method proposed can be suitable to adopt in the multi-objective optimization dispatch.
出处
《电工技术学报》
EI
CSCD
北大核心
2010年第9期151-156,共6页
Transactions of China Electrotechnical Society
基金
国家自然科学基金(50677062)
教育部新世纪优秀人才支持计划(NCET-07-0745)
国家863计划(2008AA05Z210)
浙江省自然科学基金(R107062)资助项目
关键词
节能
经济
环保
多目标优化
多目标粒子群优化算法
Energy saving
economy
environmental protection
mulit-objective optimization
MOPSO algorithm
