A Massively Parallel Population-Based Approach to Operations Scheduling

基于大规模并行群体的操作调度方法

• 批准号: 9505668
• 负责人: V Ramesh
• 金额: $ 7.27万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-10-01 至 1998-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9505668&HistoricalAwards=false
• 关键词: Massively; Parallel; Population; Based; Approach

9505668 Ramesh The operations scheduling problem concerns the scheduling of generating units in the most economic manner subject to several constraints. The problem is to identify which units should be ON (committed) in each our over a period of time ranging from a day to a week, and to determine the generation level of each committed unit in each hour. The main difficulty in solving the problem is that it is a large mixed-integer nonlinear programming (MINLP) problem, and is compute-intensive. Because of this, the algorithmic techniques currently employed do not model many relevant constraints, and use several approximations which lead to suboptimal solutions. The main objectives of this research are: a) to investigate and develop a new population-based optimization technique for MINLP problems, and b) to use a comprehensive model encompassing most, if not all, relevant constraints for the operations scheduling problem. The new combinatorial optimization technique that we will explore in this research is a decomposition methodology that evaluates a population of solutions, in parallel, for each subproblem of the over-all problem. The approach will be applied to solve a comprehensive model of the operations scheduling problem. We will investigate the complexity and optimality of the proposed technique. ***

小行星9505668 发电机组运行调度问题是指在一定的约束条件下，以最经济的方式对发电机组进行调度。 问题是要确定在一天到一周的一段时间内，哪些单元应该在每个our中处于ON（已提交）状态，并确定每个已提交单元在每个小时中的生成级别。 求解该问题的主要困难在于它是一个大型的混合整数非线性规划（MINLP）问题，并且是计算密集型的。 正因为如此，目前采用的算法技术没有模拟许多相关的约束，并使用几个近似，导致次优的解决方案。 本研究的主要目标是：a）调查和开发一种新的基于人口的MINLP问题的优化技术，和B）使用一个全面的模型，包括大多数，如果不是所有的，相关的约束操作调度问题。 新的组合优化技术，我们将在这项研究中探索的是一种分解方法，评估人口的解决方案，并行，为每个子问题的整体问题。 该方法将被应用于解决一个综合模型的操作调度问题。 我们将研究所提出的技术的复杂性和最优性。 ***