A Multi-Object Genetic Algorithm for the Assembly Line Balance Optimization in Garment Flexible Job Shop Scheduling

Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is not high,and the production organization is not up to expectations.Aiming at the problem of flexible process route planning in garment workshops,a multi-object genetic algorithm is proposed to solve the assembly line bal-ance optimization problem and minimize the machine adjustment path.The encoding method adopts the object-oriented path representation method,and the initial population is generated by random topology sorting based on an in-degree selection mechanism.The multi-object genetic algorithm improves the mutation and crossover operations according to the characteristics of the clothing process to avoid the generation of invalid offspring.In the iterative process,the bottleneck station is optimized by reasonable process splitting,and process allocation conforms to the strict limit of the station on the number of machines in order to improve the compilation efficiency.The effectiveness and feasibility of the multi-object genetic algorithm are proven by the analysis of clothing cases.Compared with the artificial allocation process,the compilation efficiency of MOGA is increased by more than 15%and completes the optimization of the minimum machine adjustment path.The results are in line with the expected optimization effect.

Flow shop rescheduling problem under rush orders

In the environment of customization, disturbances such as rush orders and material shortages often occur in the manufacturing system, so rescheduling is necessary for the manufacturing system. The rescheduling methodology should be able to dispose of the disturbance efficiently so as to keep production going smoothly. This aims researching flow shop rescheduling problem (FSRP) necessitated by rush orders. Disjunctive graph is employed to demonstrate the FSRP. For a flow shop processing n jobs, after the original schedule has been made, and z out of n jobs have been processed in the flow shop, x rush orders come, so the original n jobs together with x rush orders should be rescheduled immediately so that the rush orders would be processed in the shortest time and the original jobs could be processed subject to some optimized criteria. The weighted mean flow time of both original jobs and rush orders is used as objective function. The weight for rush orders is much bigger than that of the original jobs, so the rush orders should be processed early in the new schedule. The ant colony optimization (ACO) algorithm used to solve the rescheduling problem has a weakness in that the search may fall into a local optimum. Mutation operation is employed to enhance the ACO performance. Numerical experiments demonstrated that the proposed algorithm has high computation repeatability and efficiency.

Research on Fuzzy Decision of Resources Selection in Job-sh op Scheduling for a One-of-a-Kind and Order-Oriented Production System

In a one-of-a-kind and order-orient ed production corporation, job shop scheduling plays an important role in the prod uction planning system and production process control. Since resource selection in job shop scheduling directly influences the qualities and due dates of produc ts and production cost, it is indispensable to take resource selection into acco unt during job shop scheduling. By analyzing the relative characteristics of res ources, an approach of fuzzy decision is proposed for resource selection. Finall y, issues in the application of the approach are discussed.

The Planning and Scheduling of Business Process in Agile Supply Chain System

The rapidly developing global competition is leadin g to the worldwide enterprise alliance, with which the geographical dispersion of production, assembly and distribution operations comes into being. Supply chain system is such a kind of enterprise alliance, managing the material and informat ion flows both in and between enterprises, such as vendors, manufacturing and assembly plants and distribution centers. In the present research work, we can see that supply chain system can quickly respond to customer needs and adapt to the dynamic change of the market so as to improve the competence of enterprises in the chain. Thus, in supply chain system, it’s most important to enhance the speed with which the products are produced and distributed to the customers who order them and reduce the operating costs at the same time. However, because of the special characteristics, such as dynamic and distributed , etc., often in Agile Supply Chain System (ASCS), there are many dynamic tasks, and many urgent changes of the processes, which make the planning work and mana gement become very difficult and complex. Thus, in Agile Supply Chain System, we first need an efficient planning work, which can program the processes properly to get a primary scheme. And then the local scheduling work based on the primar y scheme will play a important role to deal with the dynamic and distributed pro blems in the business process in ASCS. So, this paper will be organized as below . At the first of this paper, we will discuss the situation in which Agile Suppl y Chain System is applied, and then we will elaborate the characteristics of Agi le Supply Chain System. With that, the shortcomings of the process managements t hat are, at present, used in Supply Chain Systems will be displayed clearly. Sec ond, we will introduce the planning methods in our research work. And then, the local scheduling will be discussed in detail, based on the primarily planned wor kflow. To realize the goal, first we build the mathematic model to describe the scheduling goal of system optimum, based on the categories of the cooperating-r elation among the operation nodes, which we defined in our research work, in Agi le Supply Chain System. And then the optimized algorithm to solve the model woul d be introduced, in succession. At the final of this paper, we will introduce some knowledge of the process mana gement and the realization of ASCS and summarize our work.

Optimization Model in Manufacturing Scheduling for the Garment Industry

The garment industry in Vietnam is one of the country’s strongest industries in the world.However,the production process still encounters problems regarding scheduling that does not equate to an optimal process.The paper introduces a production scheduling solution that resolves the potential delays and lateness that hinders the production process using integer programming and order allocation with a make-to-order manufacturing viewpoint.A number of constraints were considered in the model and is applied to a real case study of a factory in order to viewhowthe tardiness and latenesswould be affected which resulted in optimizing the scheduling time better.Specifically,the constraints considered were order assignments,production time,and tardiness with an objective function which is to minimize the total cost of delay.The results of the study precisely the overall cost of delay of the orders given to the plant and successfully propose a suitable production schedule that utilizes the most of the plant given.The study has shown promising results that would assist plant and production managers in determining an algorithm that they can apply for their production process.

Rule-and PSO Algorithm-based Dynamic Spatial Rescheduling Method for Hull Curved Block Construction

Due to no effective rescheduling method in hull curved block construction planning, existing scheduling planning can’t be applied in practical production effectively. Two-dimensional layout and dynamic attributes of block construction planning are considered to develop a spatial rescheduling method, which is based on the spatial points searching rule and the particle swarm optimization(PSO) algorithm. A dynamic spatial rescheduling method is proposed to solve the manufacturing problem of rush-order blocks. Through spatial rescheduling, the rescheduling start time, the current processing information set and rescheduling blocks set can be obtained automatically. By using and updating the data of these sets, the rescheduling method combines the PSO algorithm with the spatial points searching rule to determine the rescheduling start time and layout of the blocks. Three types of dynamic events, including rush-order block delay, existing block delay and existing block position changes, are used to address problems with different function goals by setting different function weights. Finally, simulations based on three types of rush-order block events are performed to validate this method, including single rush-order block, multi rush-order blocks at the same time and multi rush-order blocks at different times. The simulation results demonstrate that this method can solve the rush-order block problems in hull block construction and reduce the interference to the existing manufacturing schedule. The proposed research provides a new rescheduling method and helps instruct scheduler to make production planning in hull block construction.

Rule-based scheduling of multi-stage multi-product batch plants with parallel units

A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.

A new polynomial algorithm for a parallelidentical scheduling problem

A precedence order is defined based on the release dates of jobs＇ direct successors. Using the defined precedence order and Heap Sort, a new polynomial algorithm is provided which aims to solve the parallel scheduling problem P｜pj = 1, r j, outtree｜ ∑Cj Cj. The new algorithm is shown to be more compact and easier to implement.

Scheduling problem for hot-rolling seamless steel tube production

Taking the seamless tube plant of Baoshan Iron & Steel Complex in China as the background,we analyze the characters of hot rolling seamless steel tube:multi varieties,low volume,complicated production process,flexible production routes.Then integrated scheduling problem for hot rolling seamless steel tube production is studied,which covers two key points;order-grouping problem and solution method for flowshop/jobshop scheduling problem.On the basis of these two problems,integrated scheduling decision system is developed.The design idea,function flow sheet,data processing method,and functional module of visualized human-computer interactive scheduling system implemented in seamless steel tube plant of Shanghai Baoshan Iron & Steel Complex are described into detail.Compared with manual system,the performance of system shows the applicability and superiority in several criteria.

Scheduling Jobs with a Common Due Date via Cooperative Game Theory

Efficient values from Game Theory are used, in order to find out a fair allocation for a scheduling game associated with the problem of scheduling jobs with a common due date. A four person game illustrates the basic ideas and the computational difficulties.

考虑拆解故障的退役产品人机混流线插单调度

多源异构退役3C产品服役阶段产生的结构变形可能引发自动拆解设备故障,性能漂移失效会扰动拆解工艺规划和生产调度.以退役3C产品人机混流拆解线为研究对象,研究退役产品拆解故障导致的插单调度问题.构建量化不确定性拆解序列和拆解深度的AND/OR节点网络模型.以最大化工位利用率为优化目标,拆解故障产品缓存搬运阈值为变量,建立人机混流线插单调度模型.采用二维实数编码方式编码,选用遗传算法求解.选取58种品系退役智能手机的人机混流聚类拆解产线数据实例验证.结果表明,构建的人机混流线插单调度模型能有效制定工位利用率最大的阈值插单调度方案.实例聚类的3类混流拆解线优化后的最大工位利用率分别为80.3%、73.2%、81.3%.

海水淡化厂与区域水-能耦合系统的协同调度

海水淡化厂具有能量密集、运行灵活的特点,是理想的电力需求响应资源。然而,现有关于淡化厂与电网协同运行的研究大多关注电网和淡化厂的一体化调度、无法适应双方自主决策的工程场景,对淡化厂运行约束的刻画也比较粗糙。该文研究反渗透淡化厂与区域水-能耦合系统(waterenergy nexus,WEN)的协同运行方法。首先,考虑淡化厂的生产流程、调节特性和运行约束,分别建立传统及新能源淡化厂的水-能管理模型;其次,在保障两类淡化厂和区域WEN自主决策和信息隐私的条件下,提出以双方调度计划互动为载体的“激励型”和“价格型”两种协同运行机制及调度模型,并提出基于二阶锥松弛和McCormick包络的求解方法。用算例验证所提协同运行机制、调度模型及求解方法的有效性。

含SOP的交直流混合配电网日前优化调度

为实现交直流混合配电网的高效运行,提出一种含智能软开关的交直流配电网优化调度方法。在对应用于交直流配电网的智能软开关工作原理进行阐述的基础上,建立含智能软开关的交直流配电网优化调度模型。通过线性化和凸松弛技术,将所建立的非线性优化模型转化为二阶锥规划模型,并且采用改进的50节点算例分析验证模型的有效性。算例结果表明,基于所建模型得到的智能软开关运行策略能够降低配电网运行损耗及改善电压越限的情况,显著提高混合配电网的经济性。

面向关隘地形的分层调度多机器人路径规划

针对关隘地形下多机器人路径规划存在的高度耦合性,引入调度次序优化思想构造了分层的多机器人路径求解与优化算法。首先,在优化层采用遗传算法生成所有机器人的调度次序,并根据适应度对调度次序进行迭代和进化。其次,根据优化层制定的调度次序,在规划层采用改进的层级协作A*(IHCA*)算法进行路径求解,并将求解结果返回上层以对该次序的适应度进行更新。最后,通过上下层相互配合,逐步提升问题求解成功率并降低路径耗时。此外,提出搜索熔断机制,避免原始HCA*算法在关隘地形中陷于反复无效搜索的状态,可进一步提升求解效率。研究结果表明,所提算法在高耦合关隘环境下具有较高的求解成功率,且路径总耗时更少。

Integrated schedule of order picking and delivery for instant delivery

In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,which integrates order delivery by depicting order location dispersion in an online order picking strategy.Order delivery,including delivery person assignment and route planning,is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time.A rule-based online order picking strategy is established,and a customized ant colony optimization(ACO)algorithm is proposed to optimize order delivery.Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective.

基于高频车站及时间窗的立体轨道交通系统智能调度算法

立体轨道交通系统的车辆调度方法还未见报道,已有车辆调度算法的实时性较差。针对立体轨道交通车辆的调度问题,研究了一种结合高、低频车站判定的订单分配算法和一种结合时间窗的Dijkstra路径规划算法,即智能调度算法,以提高车辆的运行效率。首先,使用订单分配算法为订单选择合适的执行车辆,减少乘客的等待时间。其次,在订单分配算法的基础上增加了高、低频车站的判定,提前给高频车站调度车辆,以保证供需平衡。然后,将普通Dijkstra算法和时间窗判断相结合,以实现多车辆的无冲突路径规划。最后,对OpenTCS软件进行二次开发,并进行了调度算法的仿真。结果表明,当有乘客叫车时,若只有订单分配算法,乘客平均等待时间为8.043 s;结合高、低频车站进行车辆提前调度后,平均等待时间降到了5.724 s,每位乘客减少了2.319 s的等待时间。路径规划时,无论是普通的Dijkstra算法还是结合时间窗的Dijkstra算法,规划耗时都在1 ms以内,而结合时间窗的Dijkstra算法在只增加约0.1 ms耗时的情况下,解决了车辆的路径冲突问题。研究的智能调度算法减少了乘客的等待时间,提高了车辆的运行效率,实时性好,能满足立体轨道交通车辆的调度要求。

基于RPA与滚动时间窗的零售电商订单动态调度仿真

为了提高零售电商订单的整体交付效率,提出基于RPA与滚动时间窗的零售电商订单动态调度方法。在RPA机器人技术框架的应用层逻辑端中,通过基于滚动时间窗的订单调度优先级排序方法,将订单以滚动时间窗划分的方式,分解为多个订单调度任务,并执行订单优先级排序。将排序后订单作为零售电商订单拣选与配送车辆联合动态调度方法的调度对象,构建订单交付时间最小化、全部订单均被交付的订单动态调度目标函数。由改进共同进化遗传算法,从订单拣选、配送车辆联合动态调度的角度,求解满足条件的订单拣选与配送车辆联合动态调度方案。实验验证,此方法调度下,零售电商客户订单配送交付时,交付时间均靠近客户对订单产品期望时间窗下界,无订单遗漏问题,全部订单均被高效拣选、配送。

基于改进的禁忌搜索算法在有序用电中的应用

国家电力系统负荷与日俱增,用户用电数据海量增长,需要高性能优化算法来解决此类复杂的有序用电问题.为了填补有序用电系统调度中的负荷缺口,提高供电效能并合理选择用户,本文提出了一种改进的禁忌搜索算法来求解电力供需平衡的多目标优化调度问题.使用融入了莱维飞行的野狗优化算法对禁忌搜索算法中的初始化阶段进行优化,得到一种改进的禁忌搜索算法.该方案增强了原始算法的搜索能力,加快了算法的收敛速度,提供了一种更优的解决方案.最后通过消融实验以及与5个经典的启发式算法进行对比实验来验证所提出的算法的性能.

基于分布式新能源与配网网络重构的降损技术

考虑分布式新能源出力随机性对调控策略执行效果的影响,研究了基于电压风险评估和主动重构的日前调度技术。基于光伏出力预测和负荷预测,以电压安全概率风险最小为目标,以开合联络开关为控制变量,应用二阶锥松弛过的Distflow潮流模型进行求解,获取电压安全概率风险最小的配网重构方案。通过对IEEE 33节点配网进行算例分析,仿真结果验证了所提基于电压风险评估与主动重构的日前降损策略的可行性。