基于petri网装配序列灰色聚类决策研究

利用petri网直观图形化特点建立装配模型,并根据petri网原理得出可行装配序列。影响可行装配序列的大部分因素是定性的、模糊的、非数值的,将装配序列看作灰色系统,采用灰色聚类决策方法对可行序列进行评估。分析了影响因素的灰色分类并且研究了灰色聚类决策步骤。实例分析表明,该方法为petri网原理所得可行序列进行正确的评估并且得出决策向量。     

基于规则对象Petri网的柔性制造系统建模

针对FMS建模中存在的问题，通过分析FMS的组成和活动特点，提出了规则对象Petri网的建模方法。该方法集中了Petri网和面向对象技术的优点，并融系统决策规则子模型中。利用规则对象Petri网，建立了FMS的资源对象模型、动态行为模型和调度决策模型，为设计、分析和调度控制提供了有效的工具。     

飞机移动装配线资源水平问题的建模研究

针对飞机总装移动装配线的资源水平问题,以最小化资源成本为目标,提出并建立了具有空间约束的资源水平问题的数学模型。针对问题特点,提出了非关键任务调度优先级规则,并以遗传算法为框架,优化非关键任务调度优先级。在解码中,提出利用区间细分的方式来确定非关键任务位置,以提高计算效率,提出并设计了当前任务调度对全局资源水平影响的评估公式,极大提高了未调度任务在后续调度过程中选择更佳调度位置的几率。针对空间约束,构建了包含当前关键任务的局部调整方法。最后通过数据实验验证了算法的有效性和优越性。     

随机动态环境下项目前摄性与反应性调度权衡优化

针对随机动态项目环境,采用前摄性调度方法可以提高基准进度鲁棒性降低执行阶段调整成本,但会导致较高的鲁棒性成本;相反,采用反应性调度方法可以降低鲁棒性成本但却会增加调整成本。考虑上述两种调度方法在应对不确定因素中的权衡关系,从成本经济角度出发构建了权衡模型,通过两种调度方法在使用中产生的成本表示其分别承担的工作量并进一步反映两种调度方法之间的权衡关系。实测结果表明,根据承包商对成本的敏感程度,前摄性调度与反应性调度在应对不确定性中的承担工作量会随着权衡比SR的变化而发生改变,逐渐从前摄性方法为主过渡到以反应性方法为主。     

多知识库系统的调度

利用目标网方法将多知识库系统的模块调度表示成宏观推理网络,通过执行调度规则实现调度。讨论了模块调度的实现方法,并应用于故障诊断专家系统中。     

第三方物流联盟中物流任务的优化调度

为了提高物流服务水平、降低物流运作成本,针对由多个第三方物流服务商组建而成的第三方物流联盟中物流任务与物流服务资源的优化调度问题展开研究,综合考虑各第三方物流服务商资源节点提供物流活动服务成本和物流服务总时间,以时间最短和成本最低为优化目标,提出了基于时间和成本的多目标优化调度模型,针对目前物流任务调度优化模型中只考虑各物流服务资源节点本身的服务成本和时间,而未考虑执行各个物流活动之间的物流资源节点之间的衔接时间与衔接成本的问题,提出一种计算不同物流服务资源节点之间的物流服务衔接时间和衔接成本的方法,在模型中,考虑了物流资源服务时间窗限制问题.最后提出了一个改进的遗传算法进行模型求解,并通过算例验证了研究的有效性.     

配网调度管理存在问题分析和优化方法

随着电网的不断发展、规模快速扩张，原有的配网调度管理模式已逐步不适应供电可靠性和故障快速复电的要求。文章从配网调度管理的现状及存在问题出发，通过探讨配网调度若干关键问题，对配网调度管理模式进行了深入的分析和探讨，具有良好的实践指导意义。     

基于遗传禁忌算法考虑转运约束的并行机批量调度问题研究

在多品种混流生产车间里，广泛存在着各种批量的任务在多台并行机上调度优化问题。这种并行机批量调度需要考虑批量大小设置、加工顺序优化、设备充分利用等多种要素，是一类典型NP-hard问题，且当任务加工完后还需要考虑转运过程时，问题将变得更加复杂。为了减少并行机生产过程中任务拖期和在制品积压，寻求更好的生产调度方案，针对典型并行机生产和转运场景，以最小化加权完工时间及拖期工件的惩罚费用、作业切换成本、库存成本之和为优化目标，设计了基于启发式规则的仿真程序与遗传禁忌算法相结合的优化算法，研究单工序不相关并行机调度环境下车间批量调度的最优调度方案，再通过案例验证了本文优化算法的有效性。结果表明，优化算法得出的并行机批量调度方案使得作业切换次数和拖期订单大大减少，减少在制品库存的同时提高了转运资源的利用率。     

不确定性周期性家庭护理资源调度

面对逐渐兴起的家庭医疗护理服务产业,本文针对服务中的不确定性周期性资源调度问题,提出了面向随机性周期重复需求的家庭护理资源调度模型并进行求解。研究目标是在满足部分客户的服务日期存在变化因素的情况下,规划下一个周期内成本期望最小的服务资源(如服务人员)对客户的服务次序和线路。方法是在合理的禁忌搜索框架下,使用蒙特卡洛仿真方法进行评价,找出符合现实中情况的最优解。通过多种规模的数值实验,验证了所提出算法的有效性。     

资源受限的多项目合作调度收益分配研究

在数字化的背景下，项目资源可以通过资源云化等打破信息的壁垒和空间的束缚，客观上为项目间实现资源共享提供了条件，从而可以提高资源使用效率、创造更多的收益。同时，资源共享创造的收益需要在项目间进行合理的分配。本文首先以各个项目拥有的资源为基础，建立了集中资源最大化额外收益的资源受限的项目活动合作调度模型，获得了合作调度的最优或次优方案及对应的额外收益。其次以额外收益为特征函数建立合作博弈模型，分析了项目调度的合作博弈的性质并运用核心、Shapley值、核仁及按比例收益分配等方法作为额外收益的分配方案。结果表明，通过集中资源合作调度，大部分项目组能够实现项目集体收益的增加。另外，随着资源的减少，有些项目靠自身的资源可能无法独立完成，而通过集中资源合作调度能在资源有限的情况下执行更多的项目。研究结果为项目管理者基于数字化资源共享平台实现资源合作调度和寻求合理的收益分配方案提供了支持，具有一定的理论与实践意义。     

Due-date assignment scheduling involving job-dependent learning effects and convex resource allocation

ABSTRACT

This article addresses single machine resource allocation scheduling problems with learning effects, where learning effects mean job-dependent position-based learning effects. For the common due-date assignment (CON) and slack due-date assignment (SLK) methods, a bi-cost analysis of the scheduling cost and the total weighted resource consumption cost is provided. The objective is to determine the optimal job sequence and the resource allocation simultaneously, such that the scheduling cost (the total weighted resource consumption cost) is minimized subject to the total weighted resource consumption cost (the scheduling cost) being limited. Solution procedures are provided for the problems under consideration.     

Managing and modelling general resource transfers in (multi-)project scheduling

Most approaches to multi-project scheduling are based on the assumption that resources can be transferred between projects without any expense in time and cost. As this assumption often is not realistic, we generalise the multi-project scheduling problem (RCMPSP) by additionally including transfer times and cost. To integrate this aspect, in a first step, we develop a framework for considering resource transfers in single- and multi-project environments. It includes managerial approaches to handle resource transfers, a classification of resource transfer types and new roles that resources can take in these transfers. Afterwards, we define the multi-project scheduling problem with transfer times (RCMPPTT) and formulate it in a basic and an extended version as integer linear programmes. Eventually, it is supplemented for the first time by cost considerations and introduced as resource constrained multi-project scheduling problem with transfer times and cost (RCMPSPTTC). Computational experiments compare the presented managerial approaches and prove the necessity of explicitly considering transfer times in project scheduling already during the planning phase. Moreover, the experiments evaluate the presented MIP models and show that specialised solution procedures are vital.     

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

In a one-of-a-kind and order-oriented production corporation, job shop scheduling plays an important role in the production planning system and production process control. Since resource selection in job shop scheduling directly influences the qualities and due dates of products and production cost, it is indispensable to take resource selection into account during job shop scheduling. By analyzing the relative characteristics of resources, an approach of fuzzy decision is proposed for resource selection. Finally, issues in the application of the approach are discussed.     

Scheduling manufacturing systems with blocking: a Petri net approach

This paper introduces a Petri net-based approach for scheduling manufacturing systems with blocking. The modelling of the job routings and the resource and blocking constraints is carried out with the Petri net formalism due to their capability of representing dynamic, concurrent discrete-event dynamic systems. In addition Petri nets can detect deadlocks typically found in systems with blocking constraints. The scheduling task is performed with an algorithm that combines the classical A* search with an aggressive node-pruning strategy. Tests were conducted on a variety of manufacturing systems that included classical job shop, flexible job shop and flexible manufacturing scheduling problems. The optimisation criterion was makespan. The experiments show that the algorithm performed well in all types of problems both in terms of solution quality and computing times.     

A note on resource allocation scheduling with position-dependent workloads

In this note, single machine scheduling with concurrent resource allocation and position-dependent workloads is studied. The aim is to find jointly the optimal sequence and the optimal resource allocation. A bicriteria analysis of the problem is provided where the first criterion is to minimize the scheduling cost (i.e. makespan, total completion time, total absolute differences in completion times, total absolute differences in waiting times) and the second criterion is to minimize the total resource consumption cost. It is proved that four bicriteria problems can be solved efficiently.     

基于资源限制的多目标网络计划优化模型

目前网络计划优化研究要么没有考虑资源限定的柔性,要么只是集中于单纯的工期优化或资源优化等单目标优化。本文针对传统网络计划建模资源限制缺少柔性、优化目标单一等问题进行了深入的研究。在柔性资源的限制下,为使得工程网络计划达到总体最优,考虑工程项目的工期、成本、项目净现值、资源的均衡等多个目标,建立其网络计划优化模型,并采用粒子群算法予以求解。根据拓扑排序算法生成满足时序约束的活动序列并计算活动的时间参数。对于产生资源冲突的活动,依照执行优先权解决冲突资源的执行顺序,更新时间参数。采用随机权重的方法,让粒子群算法种群的多个个体进行随机转化,从而保持解的多样性。采用国际上通用的Patterson问题库中benchmark算例对本文提出的方法进行验证。结果表明,与初始方案相比,优化后的方案分别在工期上缩减了20%,成本上缩减了11.17%,净现值增加了11.82%,资源均衡度减少了18.29%。由此可见,提出的基于粒子群算法的优化模型对资源限制下的网络计划中的工期、成本、净现值、资源均衡度等多个目标均实现了不同程度的优化。     

Petri nets and genetic algorithms for complex manufacturing systems scheduling

In this paper we propose the GAPN (genetic algorithms and Petri nets) approach, which combines the modelling power of Petri nets with the optimisation capability of genetic algorithms (GAs) for manufacturing systems scheduling. This approach uses both Petri nets to formulate the scheduling problem and GAs for scheduling. Its primary advantage is its ability to model a wide variety of manufacturing systems with no modifications either in the net structure or in the chromosomal representation. In this paper we tested the performance on both classical scheduling problems and on a real life setting of a manufacturer of car seat covers. In particular, such a manufacturing system involves features such as complex project-like routings, assembly operations, and workstations with unrelated parallel machines. The implementation of the algorithm at the company is also discussed. Experiments show the validity of the proposed approach.     

Adaptive production scheduling of virtual production systems using object-oriented Petri nets with changeable structure

Virtual Production Systems (VPSs) are logically constructed by organizing production resources belonging to one or more physical manufacturing systems. VPSs can enhance the agility of manufacturing systems. However, an effective scheduling approach is required to cope with disturbance and changes to these systems. An adaptive production scheduling method is proposed. Object-oriented Petri nets with changeable structure (OPNs-CS) formulate the scheduling problem of VPSs. To resolve resource constraints in a VPS, the OPNs-CS is modified by introducing limited token available time and by revising the enabling and firing rules. The artificial intelligent heuristic search (A*) algorithm is modified and applied to generate the optimal or near optimal schedule. When a VPS encounters any disturbance, an estimate of the effects of the disturbance can be estimated by simulation on the OPNs-CS model. If the scheduling target (completion time) is not affected, rescheduling is not required. Whenever there is a change to the VPS, the TOPNs-CS model is updated to refresh VPS schedule. A case study is presented to demonstrate the procedures for applying the proposed scheduling approach. The given case study shows that the proposed approach is capable of scheduling a VPS dynamically in response to disturbances and changes are involved.     

Convex resource allocation scheduling in the no-wait flowshop with common flow allowance and learning effect

We study the problem of two-machine no-wait flowshop scheduling with learning effect and convex resource-dependent processing times. Under the condition of the due-date assignment with common flow allowance (i.e. slack (SLK) due-date assignment), we provide a bi-criteria analysis where the first criterion is to minimise the scheduling criteria (i.e. the weighted sum of earliness, tardiness and flow allowance costs), and the second criterion is to minimise the resource consumption cost (i.e. the weighted sum of resource consumption cost). The objective is to determine the optimal job sequence, resource allocations and common (flow allowance) slack time that minimise the three different versions of the two criteria. We prove that these problems can be solved in polynomial time.     

A Multi-Resource Project Scheduling Algorithm

A heuristic algorithm for scheduling a multi-resource project is described where the objective is to minimize the project cost for any project duration between some specified time range. Input conditions are realistic and include alternative resource combinations (ARCs) for each activity, resource cost functions and hiring and dismissal costs for changes in resource quantities. The algorithm selects that combination of activity ARCs that gives the minimum cost solution for any feasible project duration, and eventually generates the Variable Cost-Time trade-off relationship from which the minimum cost conditions for the project can be found.