MERGING OPTIMALITY CONDITIONS WITH GENETIC ALGORITHM OPERATORS TO SOLVE SINGLE MACHINE TOTAL WEIGHTED TARDINESS PROBLEM

1.Introduction Production sequencing and scheduling is one of the most important activities in production planning and control.Sequencing is defined as the order in which the jobs are processed through the machines.The allocation of machines over time to process a collection of jobs is defined as Scheduling.Several methods have been developed to solve the scheduling problem which can be classified as follows:1)efficient optimal methods,2)implicit and explicit,or complete enumerative methods,a…     

Unbounded batch scheduling with a common due window on a single machine*

The common due window scheduling problem with batching on a single machine is dealt with to minimize the total penalty of weighted earliness and tardiness. In this paper it is assumed that a job incurs no penalty as long as it is completed within the common due window. It is the first time for the due window scheduling to be extended to this situation so that jobs can be processed in batches. An unbounded version of batch scheduling is also considered. Hence, jobs, no matter how many there are, can be processed in a batch once the machine is free. For two cases that the location of due window is either a decision variable or a given parameter, polynomial algorithms are proposed based on several optimal properties.     

Capacitated stochastic coloured Petri net-based approach for computing two-terminal reliability of multi-state network

Classical network reliability problems assume both networks and components have only binary states,fully working or fully failed states.But many actual networks are multi-state,such as communication networks and transportation networks.The nodes and arcs in the networks may be in intermediate states which are not fully working either fully failed.A simulation approach for computing the two-terminal reliability of a multi-state network is described.Two-terminal reliability is defined as the probability that d units of demand can be supplied from the source to sink nodes under the time threshold T.The capacities of arcs may be in a stochastic state following any discrete or continuous distribution.The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and demand.To solve this problem,a capacitated stochastic coloured Petri net is proposed for modelling the system behaviour.Places and transitions respectively stand for the nodes and arcs of a network.Capacitated transition and self-modified token colour with route information are defined to describe the multi-state network.By the simulation,the two-terminal reliability and node importance can be estimated and the optimal route whose reliability is highest can also be given.Finally,two examples of different kinds of multistate networks are given.     

Hybrid Genetic Algorithms with Fuzzy Logic Controller

SYSTEMS ENGINEERING1. IMTSODUCTIONMachine scheduling problem is the study of constructing schedules of machine processing for a set of jobs inorder to ensure the execution of all jobs in a reasonable amount of time or cost. Usually, it deals with whatmachines to be allocated to which jobs and how to order the jobs in an appropriate processing sequence. Inparallel machine system, two machines are identical and a job can be processed by any one of the free machines.Each finished job …     

OPTIMAL MAINTENANCE AND REPLACEMENT OF EXTRACTION MACHINERY

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.     

Evolutionary game analysis of problem processing mechanism in new collaboration

This paper analyzes a problem processing mechanism in a new collaboration system between the main manufacturer and the supplier in the"main manufacturer-supplier"mode,which has been widely applied in the collaborative development management of the complex product.This paper adopts the collaboration theory,the evolutionary game theory and numerical simulation to analyze the decision-making mechanism where one upstream supplier and one downstream manufacturer must process an unpredicted problem without any advance contract in common.Results show that both players'decision-makings are in some correlation with the initial state,income impact coefficients,and dealing cost.It is worth noting that only the initial state influences the final decision,while income impact coefficients and dealing cost just influence the decision process.This paper shows reasonable and practical suggestions for the manufacturer and supplier in a new collaboration system for the first time and is dedicated to the managerial implications on reducing risks of processing problems.     

Stability analysis and design of time-delay uncertain systems using robust reliability method

A robust reliability method for stability analysis and reliability-based stabilization of time-delay dynamic systems with uncertain but bounded parameters is presented by treating the uncertain parameters as interval variables.The performance function used for robust reliability analysis is defined by a delayindependent stability criterion.The design of robust controllers is carried out by solving a reliability-based optimization problem in which the control cost satisfying design requirements is minimized.This kind of treatment makes it possible to achieve a balance between the reliability and control cost in the design of controller when uncertainties must be taken into account.By the method,a robust reliability measure of the degree of stability of a time-delay uncertain system can be provided,and the maximum robustness bounds of uncertain parameters such that the time-delay system to be stable can be obtained.All the procedures are based on the linear matrix inequality approach and therefore can be carried out conveniently.The effectiveness and feasibility of the proposed method are demonstrated with two practical examples.It is shown by numerical simulations and comparison that it is meaningful to take the robust reliability into account in the control design of uncertain systems.     

Capacity allocation and coordination issues for the timely processing of outsourced operations

We consider dynamic capacity booking problems faced by multiple manufacturers each outsourcing certain operations to a common third-party firm. Each manufacturer, upon observing the current state of the third-party schedule, books capacity with the objective to jointly minimize holding costs that result from early deliveries, tardiness penalties due to late deliveries, and third-party capacity booking costs. When making a reservation, each manufacturer evaluates two alternative courses of action： （i） reserving capacity not yet utilized by other manufactures who booked earlier; or （ii） forming a coalition with a subset or all of other manufacturers to achieve a schedule minimizing coalition costs, i.e., a centralized schedule for that coalition. The latter practice surely benefits the coalition as a whole; however, some manufacturers may incur higher costs if their operations are either pushed back too much, or delivered too early. For this reason, a cost allocation scheme making each manufacturer no worse than they would be when acting differently （i.e., participating in a smaller coalition or acting on their own behalf,） must accompany centralized scheduling for the coalition. We model this relationship among the manufacturers as a cooperative game with transferable utility, and present optimal and/or heuristic algorithms to attain individually and eoalitionally optimal schedules as well as a linear program formulation to find a core allocation of the manufacturers＇ costs.     

Optimal index shooting policy for layered missile defense system

In order to cope with the increasing threat of the ballistic missile(BM)in a shorter reaction time,the shooting policy of the layered defense system needs to be optimized.The main decisionmaking problem of shooting optimization is how to choose the next BM which needs to be shot according to the previous engagements and results,thus maximizing the expected return of BMs killed or minimizing the cost of BMs penetration.Motivated by this,this study aims to determine an optimal shooting policy for a two-layer missile defense(TLMD)system.This paper considers a scenario in which the TLMD system wishes to shoot at a collection of BMs one at a time,and to maximize the return obtained from BMs killed before the system demise.To provide a policy analysis tool,this paper develops a general model for shooting decision-making,the shooting engagements can be described as a discounted reward Markov decision process.The index shooting policy is a strategy that can effectively balance the shooting returns and the risk that the defense mission fails,and the goal is to maximize the return obtained from BMs killed before the system demise.The numerical results show that the index policy is better than a range of competitors,especially the mean returns and the mean killing BM number.     

LOT SIZING WITH NON-ZERO SETUP TIMES FOR REWORK

In this paper we consider a single machine multi-product lot scheduling problem in which defective items are produced in any production run of each product. In each cycle after the normal production of each product the machine is setup for the rework of the defectives of the same product and then the rework process starts. We assume that the setup time for the normal production process as well as the rework process is non-zero. Further we consider the waiting time cost of defectives for rework. This paper has two objectives. The first objective is to obtain the economic batch quantity （EBQ） for a single product. The second objective is to extend the result of the first objective to the multi-product case. Adopting the common cycle scheduling policy we obtain optimal batch sizes for each product such that the total cost of the system per unit time is minimized.     

城市供水系统弹性应对策略与仿真分析

针对城市供水系统受外界威胁导致供应能力波动的问题,建立了以优化供水系统弹性为目标的两阶段应对策略模型.第一阶段为马尔可夫决策过程水库调度模型,求解在满足期望弹性约束下以总成本最小化为目标的优化调度策略;当供应缺口超出水库调度能力时,针对供水系统在动态情景下的不确定性,建立了以供水网络弹性损失最小为目标的系统动力学第二阶段模型,通过仿真实验得到了多渠道优化策略.最后,以上海市咸潮入侵事件验证了该方法的有效性和实用性.     

考虑中断的制造型供应链协调调度模型

供应链协调调度能有效提高企业应对供应链中断的能力。以两阶段制造供应链为研究对象，研究了中断情境下具有交付时间约束的多产品类型制造供应链协调调度问题。制造商接到包含多产品类型的工件加工订单，各工件需经供应商处理为原材料工件后，交付给制造商处理为完成品，各工件均有一个独立的交付期。如果供应商单方面调整工件加工顺序，会导致制造商冲突成本的增加，需双方协商处理。以最小化供应商总拖期交付成本和最小化制造商总冲突成本为目标，基于收益共享契约协调机制，构建了考虑中断的制造型供应链协调调度模型。设计了一个融合自适应邻域搜索算子的混合自适应遗传算法。通过算例仿真，验证了所提模型与算法的有效性。     

New mixed broadcast scheduling approach using neural networks and graph coloring in wireless sensor network

Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem (BSP) is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfield network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.     

面向复杂航道的引航员与船舶集成调度优化

为提高复杂航道条件下港口的引航调度服务水平,本文研究了船舶和引航员调度的集成优化问题.本文考虑了潮汐、封航、安全距离以及单双向航道的对向避让等因素,以船舶延误成本和引航员调度成本最小化为目标,建立了整数规划模型.结合问题的特征,设计了一种两阶段变邻域搜索算法对模型进行求解.其中第一阶段讨论了引航员调度对于船舶延误的影响,求得了所有船舶和部分引航员调度方案的集合;第二阶段以传统调度规则得到的所有船舶和引航员的完整调度方案为初始解,使用变邻域搜索算法求解所有调度方案中最优的调度方案.最后,通过一系列数值试验验证了模型和算法的有效性.     

基于资源流网络与时间缓冲集成优化的鲁棒性项目调度

针对工期不确定的资源受限项目调度问题,将鲁棒性资源分配和时间缓冲插入两种方法进行有效地结合,通过设计两阶段集成优化算法构建抗干扰能力较强的鲁棒性项目调度计划.第一阶段提出MEPC(minimizing expected penalty cost)资源流网络优化算法,通过对资源进行有效配置生成稳定的资源流网络.为进一步提升调度计划的鲁棒性,第二阶段通过固定第一阶段构建的资源流网络,设计EPC(expected penalty cost)缓冲优化算法,通过迭代方式在延期风险较大的活动前插入时间缓冲,实现项目期望惩罚成本最小化.最后通过大规模仿真实验从"解"鲁棒性"质"鲁棒性两方面来验证两阶段算法的有效性和可行性,结果表明通过将资源流网络与时间缓冲进行集成优化构建的调度计划不仅具有较好的完工性并且能更有效地应对项目执行过程中各种不确定性因素的干扰.     

模糊多目标资源受限项目调度问题的优化方法

设计了一种求解模糊多目标资源受限项目调度问题的遗传局域搜索（GLS）算法，目标是生成近似有效解集以便决策者在决策过程中有更多的选择．算法利用线性加权效用函数将多目标组合优化问题转换为单目标组合优化问题，通过系统的方法生成目标权系数向量，对于每次生成的权系数向量，调用GLS算法求解以极小化效用函数为单一目标的子问题，由此生成的近似有效解集更加具有多样性．实验结果表明：本文算法可以针对多目标资源受限项目调度问题生成较好质量的近似有效解集，在多数指标上优于其它两种对照算法．     

Real-Time Pricing for Smart Grid with Multiple Companies and Multiple Users Using Two-Stage Optimization

In this paper, we focus on the real-time interactions among multiple utility companies and multiple users and formulate real-time pricing(RTP) as a two-stage optimization problem. At the first stage, based on cost function, we propose a continuous supply function bidding mechanism to model the utility companies' profit maximization problem, by which the analytic expression of electricity price is further derived. At the second stage, considering that individually optimal solution may not be socially optimal, we employ convex optimization with linear constraints to model the price anticipating users' daily payoff maximum. Substitute the analytic expression of electricity price obtained at the first stage into the optimization problem at the second stage. Using customized proximal point algorithm(C-PPA), the optimization problem at the second stage is solved and electricity price is obtained accordingly. We also prove the existence and uniqueness of the Nash equilibrium in the mentioned twostage optimization and the convergence of C-PPA. In addition, in order to make the algorithm more practical, a statistical approach is used to obtain the function of price only through online information exchange, instead of solving it directly. The proposed approach offers RTP, power production and load scheduling for multiple utility companies and multiple users in smart grid. Statistical approach helps to protect the company's privacy and avoid the interference of random factors, and C-PPA has an advantage over Lagrangian algorithm because the former need not obtain the objection function of the dual optimization problem by solving an optimization problem with parameters. Simulation results show that the proposed framework can significantly reduce peak time loading and efficiently balance system energy distribution.     

Efficiency decomposition with shared inputs and outputs in two-stage DEA

Data envelopment analysis (DEA) is an effective non-parametric method for measuring the relative efficiencies of decision making units (DMUs) with multiple inputs and outputs. In many real situations, the internal structure of DMUs is a two-stage network process with shared inputs used in both stages and common outputs produced by the both stages. For example, hospitals have a two-stage network structure. Stage 1 consumes resources such as information technology system, plant, equipment and admin personnel to generate outputs such as medical records, laundry and housekeeping. Stage 2 consumes the same set of resources used by stage 1 (named shared inputs) and the outputs generated by stage 1 (named intermediate measures) to provide patient services. Besides, some of outputs, for instance, patient satisfaction degrees, are generated by the two individual stages together (named shared outputs). Since some of shared inputs and outputs are hard split up and allocated to each individual stage, it needs to develop two-stage DEA methods for evaluating the performance of two-stage network processes in such problems. This paper extends the centralized model to measure the DEA efficiency of the two-stage process with non splittable shared inputs and outputs. A weighted additive approach is used to combine the two individual stages. Moreover, additive efficiency decomposition models are developed to simultaneously evaluate the maximal and the minimal achievable efficiencies for the individual stages. Finally, an example of 17 city branches of China Construction Bank in Anhui Province is employed to illustrate the proposed approach.     

赛汝生产系统构建与调度的研究进展

作为一种新的生产模式,赛汝生产(SERU production)因其响应快、柔性高、效率高的优势在佳能、索尼等电子产品制造企业被广泛采用并取得很好的效果,也因此引起了学术界的广泛关注.赛汝生产系统运作至少包括赛汝生产系统构建和调度两个关键决策过程,而且这两个决策过程都是NP难问题.为了降低计算复杂度,大多数已有研究都是对赛汝生产系统构建和调度进行单独决策,但赛汝生产系统构建和调度的单独决策无法产生全局最优解.为获得全局最优解,需要联合决策赛汝生产系统构建和调度.本文从赛汝生产系统构建与调度的单独决策、纯赛汝生产系统构建与调度的联合决策、混合赛汝生产系统构建与调度的联合决策三个方面,介绍和总结了赛汝生产系统构建和调度的研究进展,展望了未来的相关研究方向.     

需求率依赖价格的新能源汽车租赁系统三方协调契约

考虑由新能源汽车制造商、租赁商和政府组成的三方系统，在市场需求率为随机且依赖租赁价格下研究了租赁商的车队配置和租赁价格的最优决策以及系统协调问题。为此，分别建立了分散决策模型、集中决策模型和基于成本共担、收益共享和两部收费的联合契约协调模型。研究结果表明：分散决策下无法实现系统协调，通过引入这种联合契约，当契约参数满足一定条件时，不仅能够实现系统协调且可以使各成员收益达到帕累托改进。最后，通过算例分析验证了模型的有效性。