化工学报 ›› 2013, Vol. 64 ›› Issue (12): 4578-4584.DOI: 10.3969/j.issn.0438-1157.2013.12.046

• 过程系统工程 • 上一篇    下一篇

多目标零等待间歇生产过程多任务调度

杨玉珍, 顾幸生   

  1. 华东理工大学化工过程先进控制与优化技术教育部重点实验室, 上海 200237
  • 收稿日期:2013-08-13 修回日期:2013-08-20 出版日期:2013-12-05 发布日期:2013-12-05
  • 通讯作者: 顾幸生
  • 作者简介:杨玉珍(1986- ),女,博士研究生。
  • 基金资助:

    国家自然科学基金项目(61174040,61104178);中央高校基本业务费专项基金项目。

Multi-objective no-wait multi-task scheduling problem of batch process

YANG Yuzhen, GU Xingsheng   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2013-08-13 Revised:2013-08-20 Online:2013-12-05 Published:2013-12-05
  • Supported by:

    supported by the National Natural Science Foundation of China (61174040,61104178).

摘要: 间歇生产过程已经成为化工生产制造技术的基础和关键,该过程生产出大量产品来满足日常生活需要。然而经济全球化使得传统的化工生产过程产业面临严重的挑战。为了保持竞争力,每个企业必须优化生产技术,加强管理。其中调度是化工企业生产管理的核心技术。针对化工过程自身的多目标和零等待等特性,研究了间歇生产过程中的多目标零等待多任务调度,并提出该问题的模型和优化方法。通过将该问题分解成两个子问题来解决:采用非延迟非秩序混合方法来解决时间表分配问题以及用带存储的完全局部搜索解决排序问题。此外多目标占优采用基于SPEA2中的策略。通过大量算例的仿真实验证明了该算法的可行性和有效性。

关键词: 间歇生产过程, 多目标, 多任务, 零等待, 邻域搜索

Abstract: Batch processes,where a great number of products are produced to meet human demands in daily life,have become significant in chemical manufacturing.However economy globalization has resulted in growing serious competitions in traditional chemical process industry.In order to keep competitive in the global market,each company must optimize the production technique and management.And scheduling is the core of production management in chemical processes.Considering the character of such processes,this paper studies the multi-objective no-wait multi-task scheduling problem of batch processes.Model and optimization methods are introduced and the problem is decomposed into two sub-problems,the sequencing and timetabling problem and used hybrid non-order strategy and modified complete local search with memory to solve the two problems separately.In addition SPEA2-based multi-objective selection is present.A large number of experiments on benchmark problems proved the feasibility and effectiveness of this algorithm.

Key words: batch process, multi-objective, multi-task, no-wait, local search

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