配送中心订单分批拣货模型及包络算法

对订单分批问题进行分析,构造了拣货作业订单分批问题的数学模型。以装箱算法为基础,考虑订单品项分布的具体位置,提出订单分批问题的包络算法,并用算例验证了算法的有效性和实用性。     

订单分批问题的数学模型及节约启发式算法

构造了拣货作业中订单分批问题的数学模型,在一些模型假设的基础上,提出了解决该问题的节约启发式算法。算例分析表明,该算法的订单分批结果优于传统的先到先服务分批结果,为实现订单优化分批拣货作业提供了新方法。     

基于聚类算法的订单分批策略研究

订单分批是物流中心提高作业分拣效率的一个有效方法。主要针对“货到人”模式下的订单分批问题,构造了基于聚类算法的数学模型,并以最小化货物搬运次数为目标函数进行求解。通过在不同规模的订单数据下,比较基于聚类算法的分批策略与采用先到先分批策略、不分批策略在拣选作业中的实际效果,表明该算法能有效提高分拣任务的作业效率。     

启发式算法在单件车间工序排序问题中的应用

本文探讨了车间作业计划的排序问题 ,深入分析和研究了启发式算法 ,结合模具车间的实际情况 ,采用基于无延迟作业计划的概率调度法 ,并进行适当的改进 ,实现对模具车间作业计划的排序 ,取得了较好的效果。     

优化批处理机排序方案的启发式算法研究

为优化带有链式先后关系约束的批处理机排序方案,对求解该方案的最优解性质进行了研究,设计了两种启发式算法.首先分析了排序方案的目标函数即为最小化加权完工时间和,然后根据最优解的性质设计了贪婪算法和优选算法.将随机生成的算例分别输入到贪婪算法、优选算法和文献已有的满批算法中进行仿真求解,验证了这些算法的有效性,并通过对仿真结果的汇总和对比分析,确认三种算法中优选算法的效果最好,可以作为实际应用中的首选.     

成组作业计划的一个启发式算法

本文描述了成组技术的基本概念和成组作业计划的基本问题.并利用动态规划方法的基本概念和基本思想,提出了一种计算量小,实用价值高的算法.     

运用聚类算法的订单归并模型研究

针对面向订单的生产管理问题,建立一套订单管理系统,对订单统一管理.在此基础上,深入研究订单归并模型,提出基于交货期和加工工艺的订单归并聚类模型,保证工件的准时交货和加工流程的统一化.实际生产时,对归并订单进行细化分组,相似加工尺寸、同名称和同型号的工件分为一个子订单,减少加工设备的调整次数,提高生产效率.该系统在某重型...     

无人仓系统订单分批问题及K-max聚类算法

为了提高订单拣选效率、降低拣选成本,研究了以自动引导小车(AGV)为搬运工具的无人仓库系统订单分批问题.分析了影响订单拣选成本和效率的两种主要因素,建立了以订单分批拣选总成本极小化为目标的整数规划模型.根据K-means聚类算法思想,结合订单分批问题的优化目标,基于每批订单中包含的商品种类和拣选每批订单需要搬运的货架信...     

基于并行拣选的自动拣选系统订单拆分优化

为减少等待时间,进一步减少整个订单的拣选时间,将原有订单拆分为多个子订单,并建立基于并行拣选的订单拆分数学模型,该模型的优化目标是通过对订单进行拆分来减少等待时间。为求解模型,提出订单拆分必要条件。在此基础上设计了启发式禁忌订单拆分算法。仿真结果显示,采用启发式算法可使拣选时间缩短14.39%～15.62%。     

时间依赖型同时取送货VRP及超启发式算法

为有效地协调正逆向物流,更好地体现城市物流配送速度时变的特点,降低物流配送成本,以时间依赖型同时取送货车辆路径问题为对象,建立其数学规划模型;设计了基于禁忌搜索的超启发式算法对其进行求解。在算法高层,设计了基于禁忌搜索评分制的选择策略及模拟退火的接收准则,实时监控底层启发式算子的性能并选择最优算子。通过基准实例测试及实验对比分析,表明了该算法能快速地找到满意解,所设计高层策略能保证算法跳出局部最优并快速收敛,从而证明了所提算法求解该问题的有效性。     

A heuristic algorithm to batching and loading problems in a flexible manufacturing system

Part type selection and machine loading are two major problems in the production planning of flexible manufacturing systems (FMS). The two problems are viewed as selecting subsets from the jobs of part types in a planning horizon and allocating jobs of the subsets among machines. In this paper, in order to develop a practical and efficient approach to solving FMS production planning problems, a heuristic algorithm is suggested that develops heuristic rules with the objective of minimisation of the number of tool changes and minimisation of the imbalance in per machine. To compare the proposed algorithm, a series of computational experiments is done on randomly generated test problems and the results show that the developed algorithm is very simple and efficient.     

A new multi-objective approach in order to balancing and sequencing U-shaped mixed model assembly line problem: a proposed heuristic algorithm

The International Journal of Advanced Manufacturing Technology - Mixed model production is the practice of assembling different and distinct models in a line without changeovers responding to...     

求解作业车间调度问题的快速启发式算法

首先将作业车间调度问题转换为一个搭积木模型,受这个直观模型的启发,提出了一个启发式的搭积木规则,该规则综合考虑了已经搭好的积木的顶高和将要搭积木的剩余高度。基于这个规则,提出了一个求解作业车间调度问题的快速启发式算法,对国际上通用的benchmark例的模拟实验结果表明,提出的算法优于经典的优先分配启发式算法。     

Mathematical model and parallel genetic algorithm for hybrid flexible flowshop lot streaming problem

Lot streaming is the technique of splitting a given job into sublots to allow the overlapping of successive operations in multi-stage manufacturing systems thereby reducing production makespan. Several research articles appeared in literature to solve this problem and most of these studies are limited to pure flowshop environments where there is only a single machine in each stage. On the other hand, because of the applicability of hybrid flowshops in different manufacturing settings, the scheduling of these types of shops is also extensively studied by several authors. However, the issue of lot streaming in hybrid flowshop environment is not well studied. In this paper, we aim to contribute in bridging the gap between the research efforts in flowshop lot streaming and hybrid flowshop scheduling. We propose a mathematical model and a genetic algorithm for the lot streaming problem of several jobs in multi-stage flowshops where at each stage there are unrelated parallel machines. The jobs may skip some of the stages, and therefore, the considered system is a complex generalized flowshop. The proposed genetic algorithm is executed on both sequential and parallel computing platforms. Numerical examples showed that the parallel implementation greatly improved the computational performance of the developed heuristic.     

求解流水车间调度问题的瓶颈指向启发式算法

针对最小化时间表长的流水车间调度问题,提出一种根据工件加工时间特征构建工件调度的瓶颈指向启发式算法。首先,为构建初始工件排序,充分利用各机器负荷一般不相等的特点,瓶颈阶段前加工时间较短而之后加工时间相对较长的工件优先开始加工;其次,当有工件等待加工时,根据工件在瓶颈机器前或后加工时间的特征调整工件加工顺序;最后,采用邻近工件成对交换和插入的方式改进初始调度。当瓶颈机器趋于中间阶段,或瓶颈机器上工件的加工时间趋于增加时,求解效果较好。数据实验表明算法是有效的。     

二维一刀切装箱问题的两阶段启发式算法

对用于二维带排样问题的Heuristic Recursive算法进行了调整,给出同一层中两个相邻浪费区域在满足一刀切约束下是否可合并的判定定理。构造了二维带排样问题的多递归层算法,并将它与一维装箱问题的最优匹配递减算法相结合,提出适应二维一刀切非旋转装箱问题的两阶段算法。在500组标准测试案例的基础上,与多种算法进行了比较。实验结果表明,所提算法在绝大多数测试案例上能够获得更好的排样布局。     

A branch-and-bound and heuristic algorithm for the single-machine time-dependent scheduling problem

The time-dependent scheduling problems have received considerable attention recently. However, machine availability, an important and practical consideration, is usually neglected. Motivated by this observation, we introduce a single-machine scheduling problem where deteriorating jobs and an availability constraint are considered. Our objective is to minimize the total completion time. In this paper, we derived optimal and near-optimal solutions for the problem, and we also gave a simulation study to show that our algorithm successfully yields the optimal solution for instances with less than 20 jobs in less than a minute. Our computational experiment also showed that the mean error percentage of the proposed heuristic algorithm for all test instances is less than 1.3% and drops to zero as the number of jobs increases.