用遗传算法解决一类模糊流水车间调度问题

对同时考虑模糊加工时间和模糊交货期的模糊流水车间调度问题进行了研究 ,模糊加工时间用三角模糊数来表示 ,模糊交货期用梯形模糊数来表示。应用遗传算法搜索最优排序 ,在适应度函数处理中引入模糊数处理方法 ,以平均满意度最大作为优化目标。最后给出了实验结果和结论     

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

SCHEDULING PROBLEMS - AN OVERVIEW

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition,     

一种求解资源受限工程调度问题的遗传算法

针对资源受限工程调度问题的特点，设计了一种改进的遗传算法，对算法的编码方式和解码规则，适值函数，遗传算法、初始种群的产生方法进行了详细的说明，利用被普遍应用的标准问题对该算法进行了大量的测试，分析了算法参数和问题参数对算法效果的影响，取得了令人满意的结果。     

A Nonprecedence－based Query Schedule Algorithm on Heterogeneous Multiprocessor System

ＡＮｏｎｐｒｅｃｅｄｅｎｃｅ－ｂａｓｅｄＱｕｅｒｙＳｃｈｅｄｕｌｅＡｌｇｏｒｉｔｈｍｏｎＨｅｔｅｒｏｇｅｎｅｏｕｓＭｕｌｔｉｐｒｏｃｅｓｓｏｒＳｙｓｔｅｍ￥ＨｅＪｕｎ；ｂａｎｇＤｉｎｇｘｉｎｇ＆ＺｈｅｎｇＷｅｉｍｉｎ（ＤｅｐａｒｔｍｅｎｔｏｆＣｏｍｐ...     

应用禁忌粒子群算法的车间调度及其并行化实现

为了解决批量生产、制造、装配等车间调度问题,基于Hadoop集群,提出应用禁忌粒子群算法的车间调度及其并行化实现.以某装载机制造车间最小化完成时间为目标,通过使用禁忌粒子群算法对车间调度问题进行求解.结果表明：在车间批量大的情况下,禁忌粒子群算法可得出有效的调度方案,避免算法陷入局部最优解.与现有的智能算法相比,禁忌粒子群算法更有利于实现全局最优解.     

连续滚动生产作业安排中初始状态非平凡的P//C_(max)问题

以实际中连续滚动生产为背景,研究了一类新的平行机作业安排问题,即初始状态非平凡的Ｐ∥Ｃ_ｍａｘ问题。基于经典的Ｂｉｎ－ｐａｃｋｉｎｇ（装箱）理论和技巧,提出改进的Ｍｕｌｔｉｆｉｔ算法及相应的ＩＦＦＤ装法,并分析算法在最坏情况下的性能指标上界为４／３．最后,提出连续生产中周期滚动式作业安排的实施算法,实现了设备不空闲而连续运行。     

并行流程式生产线调度问题的概率分析求解算法

并行生产线调度问题兼有并行机器和流程车间调度问题的特点 ,是一类新型的调度问题·针对工件在各工序具有任意加工时间的一般并行生产线调度问题 ,构造了整数规划模型 ,设计了基于概率分析的求解算法·对随机生成的测试问题进行求解的实验结果表明了算法的有效性     

带机器准备时间的同类机在线与半在线排序问题

研究带机器准备时间的m台同类机(uniform machines)在线和半在线排序问题，目标函数为极小化最大机器(工件)完工时间。对于在线情形，证明了LS算法的最坏情况为ρ=｛（1 √5）/2，m=2,1 √2m-2/2,m≥3，并且当m=2，LS算法是最好的近似算法；当m=2，3，…，6时界是紧的，特别地，当s1=s2=…=sm-1,sm≥l时，证明了LS算法的最坏情况界为ρ=｛（1 √5）/2，m=2,3-4/m 1,m≥3，而且界是紧的；对于已知加工时间递减的半在线排序问题，证明了LS算法的最坏情况界为2—2/(m 1)。     

物流配送车辆优化调度的综述

物流配送车辆优化调度问题是一类具有广泛应用的强NP难题,本文综合国内外多种参考文献,阐述了该问题的定义和分类,具体介绍了不同情况下的常见模型和主要算法,并就目前该问题的研究发展情况做了简要分析和进一步的展望.