基于蚁群算法的物流多任务分配中路径规划研究

新时期,物流在人们生活中发挥着举足轻重的作用,研究物流任务分配和路径规划具有实际应用意义。研究了在物流配送中多任务下任务分配中路径规划问题,利用Floyd算法求出两点之间的欧几里德距离,利用蚁群算法求出任务的最优距离。实验数据表明,结合两种算法,在多任务分配下可以为快递员提供最优的路径决策方案。     

基于大数据分析及多目标优化的厂级负荷优化分配系统

厂网分开、竞价上网已经成为必然的趋势,这就要求火电厂必须对各种企业资源建立完善的管理网络,使各个方面资源得到充分调配、平衡和控制.以大唐托克托电厂1～10号机组为研究对象,建立一种基于大数据分析及多目标优化的厂级负荷优化分配系统,对全厂并网机组进行负荷调度,利用开发完成的大数据分析技术及其软硬件集成系统,对厂内不同机组...     

多系列并行生产系统负荷分配优化软件

本文介绍在资源紧缺或产品销路受到限制时，用于多系列并行生产系统负荷分配优化的软件系统，并简要介绍了应用情况。     

复杂环境下路径规划问题的遗传路径规划方法

本文主要研究复杂环境下路径规划问题的遗传算法求解方法．介绍了适于求解路径 规划问题的遗传算法,针对复杂环境的特点设计了有效的路径遗传算子,在此基础上提出一 种新的度量路径个体适应度的计算方法．试验表明,该算法有很强的鲁棒性,适合于复杂环 境下的路径规划．     

移动机器人路径规划方法

路径规划方法是移动机器人导航技术研究的核心问题之一。本文针对移动机器人路径规划的一些方法进行了归纳,分别对全局规划方法、局部规划方法及其他规划方法进行了介绍。     

多电机负荷分配的耦合特性与控制策略分析

针对多电机的耦合特性复杂、负荷易失衡的特点,采用总线通信实时控制的方式对电机转矩与转速进行调节.通过分析多电机负荷分配中刚性耦合与柔性耦合的特点,提出了与其对应的总线通信转矩控制和总线通信转速控制的负荷分配控制策略,并对这两种控制策略的稳定性做出了理论性分析.最后通过观测现场实时数据证明了控制策略的可行性.     

板带轧机负荷分配方法的综述

负荷分配是轧制规程设定计算的核心,合理的负荷分配能够充分发挥轧机生产能力,稳定生产过程,提高产品质量。参考国内外的理论研究及工程实践,将负荷分配方法按照其发展进程进行分类和综述,分为能耗曲线方法、基于轧制理论分配方法、传统优化分配方法和智能优化分配方法。其中在传统优化分配方法中按优化目标不同进行分类,包括能耗最小目标、等负荷轧制目标、相对等负荷轧制目标、综合等负荷函数目标、板型良好目标、最小轧制道次目标和综合多目标;在智能优化分配方法中按照优化方法进行分类,包括遗传算法、神经网络、模糊理论等智能算法。最后指出多目标优化和智能优化是今后负荷分配的发展方向。     

一种车型机器人路径规划方法

在自主移动机器人的许多应用中,路径规划技术顺序地设置一套分散的路径点来引导机器人以最短的时间从起始位置到达目标点。针对移动机器人路径规划问题,提出了一种非完整型机器人路径规划技术,该技术采用基本原子操纵方法来解决车型机器人路径规划问题,并采用平滑路径规划方法来产生更多的连续路径用以解决基本原子操纵技术在做路径规划时具有很不连续的缺点从而为机器人获得最优路径。仿真结果证明了该方法的有效性和实用性。     

电力系统经济负荷分配的族群优化方法

经济负荷分配（Economic Load Dispatch,ELD）是电力系统中一种重要的优化问题,它可归为一类高维、离散、非线性的多约束函数优化问题。针对这类问题,提出了一种基于线性截取策略的改进族群进化算法——EGEA/LT,并使用EGEA/LT对IEEE的3机、6机和15机3个仿真系统进行了优化实验,将实验结果与其他典型算法优化结果进行比较,说明了EGEA/LT是一种求解ELD问题的有效方法。     

无碰路径规划的拓扑方法

本文介绍无碰路规划的拓扑方法。首先理论上讨论降维法,其次给出计算机程序实现的方法及其结果。     

一种集成FMS零件分批与机器装载的新方法

提出一种解决FMS零件分批与机器装载问题的新思路.建立了问题的混合整数规划模型,研究了基于遗传算法的求解方案.在遗传算法的编码策略中,引入了虚工件和虚工序的概念,并设计了相应问题特征的交叉算子与变异算子.仿真结果验证了方案的有效性.     

Network-based hybrid genetic algorithm for scheduling in FMS environments

Scheduling in flexible manufacturing systems (FMS) must take account of the shorter lead-time, the multiprocessing environment, the flexibility of alternative workstations with different processing times, and the dynamically changing states. The best scheduling approach, as described here, is to minimize makespan t _M, total flow time t _F, and total tardiness penalty p _T. However, in the case of manufacturing system problems, it is difficult for those with traditional optimization techniques to cope with this. This article presents a new flow network-based hybrid genetic algorithm (hGA) approach for generating static schedules in a FMS environment. The proposed method is combined with the neighborhood search technique in a mutation operation to improve the solution of the FMS problem, and to enhance the performance of the genetic search process. We update the change in swap mutation and the local search-based mutation ration. Numerical experiments show that the proposed flow network-based hGA is both effective and efficient for FMS problems.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

New Algorithm for FMS Scheduling Based on Multiagent System Architecture

Redefined benefit-driven function is used to study the dynamic scheduling of FMS based on multiagent architecture. Each agent is dedicated to a work center, i.e. a set of the manufacturing system. In one hand, each agent selects locally and dynamically the dispatching rule(DR) that seems to be most suited to the operating conditions, production objectives and current shop status. On the other hand, each task should bring certain amount of benefit for the manufacturer. So, it is reasonable to have the dynamic scheduling of FMS relying upon multiagent architecture using the benefit-driven function as a strategy. Well, today's manufacturing corporation, especially the high & new technology one and deep machining one, the cost of their products is mainly determined by how much the knowledge is input From this viewpoint, we redefined the benefit-driven function, hi the end, this approach is compared with other existing DRs on a job-shop problem, already used in other research works.     

Real time fuzzy scheduling rules in FMS

This paper presents a real-time fuzzy expert system to scheduling parts for a flexible manufacturing system (FMS). First, some vagueness and uncertainties in scheduling rules are indicated and then a fuzzy-logic approach is proposed to improve the system performance by considering multiple performance measures. This approach focuses on characteristics of the system's status, instead of parts, to assign priorities to the parts waiting to be processed. Secondly, a simulation model is developed and it has shown that the proposed fuzzy logic-based decision making process keeps all performance measures at a good level. The proposed approach provides a promising alternative framework in solving scheduling problems in FMSs, in contrast to traditional rules, by making use of intelligent tools.     

Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems

Recently, there has been an increasing effort to address integrated problems that are composed of multiple interrelated sub-problems. Many integrated problems in the real world have a multileveled structure. This paper proposes a new method of solving integrated and multileveled problems. The proposed method is named Multileveled Symbiotic Evolutionary Algorithm (MSEA). MSEA is an evolutionary algorithm that imitates the process of symbiotic evolution, including endosymbiotic evolution. It is designed to promote the balance of population diversity and population convergence. To verify its applicability, MSEA is applied to loading problems of flexible manufacturing systems with various flexibilities. Through computer experiments, the features of MSEA are shown and their effects on search capability are discussed. The proposed algorithm is also compared with existing ones in terms of solution quality. The experimental results confirm the effectiveness of our approach.     

基于多Agent的FMS建模仿真方法研究

对FMS进行层次分解,将功能独立、具有自主决策能力的设备作为研究FM：5的主体,并利用FSA描述主体的状态及演化,从而建立主体的行为模型。在此基础上,主体实现了符合HLA／RTI规范的网络接口,从而构建FMS的Agent模型,并使模型具有互操作性和可重用性,从而具备协同求解的能力。最后提出了基于多Agent的FMS仿真的基本框架,以便能快速建     

Solution of scheduling problems of job-shop type FMS with alternative machine tools

FMS is now expected as one of the measures to cope with the recent requirements for the production. To elevate the performance of the FMS, it is necessary to establish its design methodology by which the flexibility and compatibility of the system functions can be determined. In this regard, one of the most important technical subjects is how to solve problems arising from machine breakdown to ensure optimum use of the system performance.

This paper deals with a scheduling problem of a job-shop type FMS with machine breakdown, taking into account alternative machine tools for each machining process of parts. The problem is solved by a discrete event simulation using SLAM II simulation language. Performance of the system is measured in terms of the machine utilization, mean flow time, total production, number of workpieces in-progress, and makespan.     

A Novel Approach to Solve the FMS Formation Problem

We propose in this paper a genetic algorithm (GA)-based approach to solve the Flexible Manufacturing System (FMS) formation problem. First, we divide the unity of machines into small groups or cells using Group Technology (GT). And an option for considering the minimization of workload variation between cells is included. Then the implementation is done using GA. When using GA, the designer is allowed to specify the number of cells and impose lower and upper bounds on cell size. This makes the GA scheme flexible for solving the FMS formation problems.     

A CONWIP model for FMS control

Production inventory control is one of the most important aspects of a flexible manufacturing system (FMS) design. CONstant Work In Process (CONWIP), which is a hybrid of push-and-pull type systems, offers an alternative to effective utilization of the expensive FMS equipment while still meeting customer requirements. In the selection of an FMS control method, material handling often becomes one of the capacity constraints which forms the basis of various research interests. In this paper, a structure-based model for a CONWIP-controlled FMS is proposed, and within it, the node type characteristics concept is used to describe the constraints in FMS. Furthermore, simulation is used to determine the card number based on the structure-based model. The simulation results demonstrate that the model is suitable for the design and operation of FMS. The model can be used as a manufacturing execution system of enterprise resources planning. An architecture for this integrated design based on Internet/Intranet systems is also proposed.     

一种新的FMS混合调度算法

在综合一种新的Petri网模型以及另一种新的混合优化策略的基础上,提出了一种具有全局优化特征的PMS调度算法,最后,仿真结果验证了该算法的有效性以及良好的研究与应用前景。