基于遗传算法的生产调度系统建模及优化

生产调度系统的优化一直是学术界研究的热点,特别是伴随着Agent技术网络化、敏捷化、智能化的现代先进制造系统中,生产调度面临着更大的难题.文章利用归约法对生产调度问题进行了优化,并在此基础上利用遗转算法进行了建模及求解.     

离散制造业机械装备企业车间生产调度问题与方法研究——以广东科达机电为例

生产计划与调度是离散制造业企业生产管理的核心及技术难点。文章介绍了生产调度的定义、发展历史与现状、特点、分类、优化目标等,并以广东科达机电为例分析目前离散制造行业生产计划与调度的问题,提出了离散制造业改进的生产管理模式及提高生产管理效率的方法。     

基于遗传算法的物流运输与调度优化研究

物流优化是物流企业降低物流成本的主要方式之一,通过物流优化进一步提高物流公司的服务能力,已经是许多物流企业提升竞争力的一项有效举措。本文依据现实中的物流运输问题,建立了基于运输成本和时间的一般函数模型,利用遗传算法进行求解,寻求最优运输路线。算例结果表明使用遗传算法优化运输方式,可以改善现有的调度模式,在满足时间约束的条件下,实现物流运输成本最小。     

论企业铁路调车自动化与调车安全防护

本文就企业铁路调车自动控制方式与调车作业安全防护方面进行探讨,重点在于将企业铁路基础信息、现车以及所有车辆信息纳入整体信息管理之中,结合车辆属性类型、线路实时情况自动选择车列行走径路,使用无线数据传输方式将实时站场情况和调车计划等传送至相应的调车机上,并在此基础上实现调车作业的安全防护。     

基于OpenMP的并行蚁群物流调度算法研究

物流中心调度问题是物流管理的核心问题,基于OpenMP并行编程规范,提出了基于蚁群的物流调度并行优化算法,挖掘多核高性能计算能力,提高物流过程中物件的动态分配效率,提高物流调度系统的可扩展性。     

Supply optimization for the production of raw sugar

Based on a case study from Venezuela, the production of raw sugar is investigated. Ideally, sugar mills operate at a constant production rate. However, safety stocks of the raw material cannot be maintained as sugar cane quality deteriorates very rapidly. Sugar cane is therefore continuously sourced in diverse quantities and qualities from hundreds of geographically dispersed haciendas and supplied to the milling process. Furthermore, due to weather conditions changing throughout the year, tight time windows must be observed for harvesting.The approach presented in this paper aims at preserving a constant supply while minimizing the associated costs. The entire planning problem is structured in a hierarchical fashion: (1) cultivation of the haciendas, (2) harvesting, and (3) dispatching of the harvesting crews and equipment. The corresponding optimization models and solution procedures are introduced and applied to the case study problem.     

一种解决配送规划问题的改进节约算法

车辆优化调度问题（VSP）是物流配送中广泛存在的一类问题，VSP问题属于NP一困难问题。在描述了简单VSP模型的基础上，对启发式算法中的C-W节约算法进行改进，将AK算法的思想运用其中，使计算结果的优化程度明显提高。     

Locating drivers in a trucking terminal network

We consider the problem of determining the home locations, or domiciles, of truck drivers for a less-than-truckload carrier. Domiciling decisions are complex, in part due to regulations and union rules restricting driver schedules, but have a significant impact on the operating costs of less-than-truckload carriers. We present an iterative scheme, using driver dispatch technology in each iteration, to allocate drivers to terminals and to determine drivers’ bids so as to satisfy union requirements. Computational experiments demonstrate the value of the iterative scheme and quantify the impact of union rules on the number of drivers required (and the resulting operating costs).     

Shift designs for freight handling personnel at air cargo terminals

This paper presents an integrated mixed integer linear programming (MILP) model for determining manpower requirements and related personnel shift designs for the build-up and break-down of the unit load devices (ULDs) at the air cargo terminal to minimize manpower costs. To utilize the manpower resources efficiently, we implement a new mechanism for demand leveling. In addition, we consider the qualification hierarchy between build-up and break-down workers. A case study based on the real-life data shows that the model is useful for manpower planning at air cargo terminals and the integrated approach is far superior to a traditional two-stage approach.     

Managing demand uncertainty through order overplanning

Most techniques for managing demand uncertainty require a certain degree of stability in the environment, since they are completely or partially based on the observation of historical data. When applied to a context characterized by irregular and sporadic demand these techniques show poor performances. In fact, in such a case uncertainty management calls for the gathering of information that directly anticipates future requirements. Although contexts with irregular and sporadic demand have received only minor attention in the past, they are currently gaining ever more importance and extending their occurrence. This paper illustrates and discusses a method, called order overplanning, specifically designed to cope with uncertainty in these environments. It consists of an articulate and coherent set of forecasting procedures, planning principles and slack control techniques. From a Master Production Scheduling (MPS) perspective, order overplanning is similar to hedging and option overplanning: gross requirements are larger than expected demand. The major difference is that order overplanning uses two distinct units in the MPS and forecasting procedures: while the MPS unit is an end item or a module, the forecasting unit is a customer order. This makes order overplanning able to exploit early information generated by each customer during its purchasing process, information that otherwise would be lost. This marked advantage comes to the detriment of an increased effort of integration between Sales and Manufacturing, especially for controlling the slack created to handle uncertainty.The paper first infers the principles and procedures of order overplanning by analysing the case study of an Italian telecommunications manufacturer. Then, it discusses the main advantages and disadvantages of this method, in order to identify the main factors affecting its performances and to determine the planning environments where it fits coherently.