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.

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.

A Trip-Chain Based User Equilibrium Traffic Assignment Model with Flexible Activities Scheduling Order

This study developed a user equilibrium traffic assignment model based on trip-chains with flexible activity scheduling order and derived the corresponding optimality conditions. We based on the gradient projection method to develop a solution algorithm, the accuracy of which was verified using the test network of UTown. This model could be used to estimate the transportation demands with and without activities scheduling restriction between OD （origin-destination） pairs based on trip-chains, as well as based on trips. Thus, the proposed model is more generalization than conventional trip based or trip-chain based traffic assignment models.

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.

An Approximation Algorithm for the Parallel-Machine Customer Order Scheduling with Delivery Time and Submodular Rejection Penalties

In this paper,we consider the parallel-machine customer order scheduling with delivery time and submodular rejection penalties.In this problem,we are given m dedicated machines in parallel and n customer orders.Each order has a delivery time and consists of m product types and each product type should be manufactured on a dedicated machine.An order is either rejected,in which case a rejection penalty has to be paid,or accepted and manufactured on the m dedicated machines.The objective is to find a solution to minimize the sum of the maximum delivery completion time of the accepted orders and the penalty of the rejected orders which is determined by a submodular function.We design an LP rounding algorithm with approximation ratio of n+1 for this problem.

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.

Freight Vehicle Routing Optimization for Sporadic Orders Using Floating Car Data

The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers,which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce the total shipping cost as well as traffic congestions in urban area, flexible methods and optimal vehicle routing strategies should be adopted to improve the efficiency of distribution effort. An optimization solution for vehicle routing and scheduling problem with time window for sporadic orders (VRPTW- S) was provided based on time-dependent travel time extracted from floating car data (FCD) with ArcGIS platform. A VRPTW-S model derived from the traditional vehicle routing problem was proposed, in which uncertainty of customer orders and travel time were considered. Based on this model, an advanced vehicle routing algorithm was designed to solve the problem. A case study of Shenzhen, Guangdong province, China, was conducted to demonstrate the vehicle operation flow,in which process of FCD and efficiency of delivery systems under different situations were discussed. The final results demonstrated a good performance of application of time-dependent travel time information using FCD in solving vehicle routing problems.

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.

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.

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.

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。

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。

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%.

面向部分工序无序加工的柔性作业车间批量调度方法

实际的车间调度问题往往具有更高的复杂度,调度算法需要考虑更多的约束条件,因此增加了问题的求解难度。为解决柔性作业车间批量调度场景中不同批次、不同工序之间可以无序加工的难题,进而突破现有车间机器使用率低、同类型机器负载不均衡的难点,文中构建了一种面向部分工序无序加工的柔性作业车间等量分批调度模型。首先,基于广泛使用的快速非支配排序遗传算法(NSGA-Ⅱ),提出了一种融合批次、批量和工序排序信息的两段编码结构,采用优先级规则方法获得初始种群,并以最小化完工时间、机器负载均衡率、机器总负荷为优化目标,采用贪心算法求解模型最优值,进而动态构建不同批次的加工路径;然后,对优化目标函数进行排序,再逐步加入非支配排序过程,以解决多个优化目标函数之间难以同时优化的问题,提高求解效率;最后,以某印刷包装企业的木制品加工车间为例,面向现场作业信息,采用仿真手段实现调度过程。结果表明,与优先级调度规则相比,文中所提方法的完工时间平均缩短了6.6%、机器负载均衡方差平均减小了10.7%,文中所提方法的机器负载均衡方差比遗传算法平均减小了53.3%,从而验证了文中方法的可行性,且该方法可以满足印刷包装企业柔性作业车间的高性能调度需求。

外卖平台在线订单分配及骑手调度优化

新兴技术(大数据/人工智能/移动互联网等)的发展和本地生活服务O2O(Online to Offline)商业模式兴起,催生了即时配送新兴物流形态,而外卖配送平台线上强履约要求成为即时配送业务痛点之一.考虑了实时外卖订单和动态变化的骑手等因素,将问题建模为带取送约束和时间约束的实时车辆调度优化问题.基于滚动时域机制将连续时间的动态问题划分为一系列离散静态子问题,设计了邻域搜索启发式算法进行求解.最后,基于大连市某外卖平台的订单业务数据对算法进行了验证,与已有文献中的方法相比,算法能有效降低平均配送时间及超时订单数量,在大规模问题场景下求解算法对平台履约影响更大,高效的调度优化算法有利于外卖平台降本增效.

考虑订单接受的云制造调度研究

为了使云制造模式更面向商业实际和保证云制造任务实际执行率,考虑实际生产和交易订单接受要求,在云制造资源调度问题中引入订单接受与调度问题的解决思路,提出考虑订单接受的云制造联合调度问题。从服务提供者订单接受逻辑角度出发,考虑生产连续性的影响,以最大化用户满意度和平台资源利用率为目标构建了云制造调度模型,引入Circle混沌映射和模拟退火机制设计了一种改进的蜣螂优化算法实现对模型的优化求解。使用铸造云的实例进行测试,验证所提方法有效,优于不考虑订单接受的调度目标,改进算法更高效,获得了更优适应度。

考虑同层后道工序的柔性设备网络综合调度算法

针对柔性设备网络综合调度算法,难以合理选择加工设备加工相关工序进而影响产品完工时间的问题,该文提出考虑同层后道工序的柔性设备网络综合调度算法(SP-FENIS)。首先,采用逆序层优先策略,将各工序分配至逆序层待调度工序集;然后,提出均值逆序紧后路径策略,确定了各逆序层待调度工序集中工序的调度顺序;最后,提出最早完工时间策略和设备空闲插入策略,当工序在柔性设备上最早完工时间相同时,考虑了在柔性设备上的加工时间和同层后道工序的加工设备,确定了目标工序的加工设备以及加工时间。实例表明,和已有算法相比,该算法能够缩短产品完工时间。