一类串行生产线的最优调度问题的注记

本讨论了[1]中串行生产线最优调度问题，给出了生产线生产周期的显示公式，对两个变量时最优调度的解的特性进行了研究。     

一种在有限网络中求解出租车调度的算法

出租车的最优调度以满足所需服务问题是一类资源优化问题，对此，本文采用了动态规划的求解方法并给出了一个具体算例，结果表明对于在有限网络中求解出租车调度可以通过该方案求出最优解。     

一种改进的多模式项目反应性调度问题

既有的项目反应性调度问题只关注了基准调度方案的稳定性,而忽略了项目调度目标的最优实现。本文提出了一种两阶段多模式资源受限项目反应性调度问题。第一阶段,在新的项目执行环境下,对项目进行完全重调度,得到新的最优调度目标值。第二阶段,以新的最优调度目标值为约束,以最大化调度稳定性为目标,求得新的最优调度方案。针对问题特点,基于IBM ILOG优化编程语言OPL和CPLEX V12.8.0,设计出该问题的求解程序。最后,基于标准算例,对本文提出的反应性调度方法、既有的反应性调度方法、完全重调度方法进行了充分的比较测试,结果表明本文提出的反应性调度方法在缩短项目工期、保护基准方案的稳定性方面具有明显优势。     

调度系统n/m/P/Cmax[ω]在一类线性摄动下的鲁棒性

用实数集R上一个含幺元的Abelian半群的性质来研究调度系统n/m/P/Cmax[ω]在一类线性摄动下的鲁棒性.根据实际问题的需要,提出了一类线性摄动模型,由系统输出表达式及其性质和最优鲁棒调度的定义,证明了:摄动系统的最优鲁棒调度必是标称系统n/m/P/Cmax[ω,1,0]的最优调度;标称系统的越韩最优调度必是它的最优鲁棒调度.     

多入口多出口串行生产线的最优节奏控制

本文用极大代数方法讨论了多入口多出口情况下带存储器有阻塞串行生产线的最优节奏控制问题,给出了串行生产线的状态方程,批量生产的生产周期公式及其函数形式,最后应用陈文德(1997)提出的算法对生产线实现了最优节奏控制。     

二机系统调度在一类线性摄动下具有鲁棒性的一个充要条件

用实数集R上一个含幺Abelian半群的性质研究了n／2／F／Cmax调度在一类线性摄动下具有鲁棒性的条件．由最优鲁棒调动的定义,证明了标称系统的最优鲁棒调度与标称系统的越-韩最优调度是等价的．     

基于遗传算法的浸染生产排缸策略

针对目前印染企业在浸染生产过程中产品种类和加工设备多、调度复杂的特性，建立了一种用于浸染生产调度的数学模型，并应用遗传算法进行排缸调度求解。以生产任务的分配优先级顺序作为染色体的编码来求解多个生产任务在多个染缸上的调度分配命题，从而得出了最优排缸策略，适用于快速、高效地解决实际生产中大量生产任务调度问题。仿真结果表明了该策略的有效性和实用性。     

一类有时间窗口约束的多资源动态调度模型与方法

含时间窗口的多资源调度，是一个包括资源分配和时间窗口分配的两阶段优化过程。在初始调度方案执行过程中，由于新的任务需求的到达，需要对初始方案进行调整．以使整个调度方案最优。本针对这种情况，分析了该问题中的主要约束条件．建立了含时间窗口的多资源动态调度模型，给出了一种启发式迭代修改求解方法；并以含时间窗口的多机调度问题为例．对模型和算法进行了验证。     

中型水库系统运行管理随机动态决策模型的研究

本文针对中型水库系统优化调度中的难点问题，提出了相应的解决方法，由此给出简单易行的系统最优运行决策模型。     

基于改进混合遗传算法安排生产调度

研究了某工厂生产调度问题,建立了数学模型.针对这一实际问题,通过引入小生境技术、最优保存策略、近优淘汰策略、自适应调整交叉概率和变异概率,设计了用于求解多个最优顺序的混合遗传算法,用所设计的混合遗传算法对该模型进行了计算,获得了许多最优顺序,这就使得生产调度安排灵活机动,便于智能调度,同时生产量比原来大幅度提高.这表明使用混合遗传算法安排生产调度是非常有效的.     

The new Fundamental Tree Algorithm for production scheduling of open pit mines

The problem of annual production scheduling in surface mining consists of determining an optimal sequence of extracting the mineralized material from the ground. The main objective of the optimization process is usually to maximize the total Net Present Value of the operation. Production scheduling is typically a mixed integer programming (MIP) type problem. However, the large number of integer variables required in formulating the problem makes it impossible to solve. To overcome this obstacle, a new algorithm termed “Fundamental Tree Algorithm” is developed based on linear programming to aggregate blocks of material and decrease the number of integer variables and the number of constraints required within the MIP formulation. This paper proposes the new Fundamental Tree Algorithm in optimizing production scheduling in surface mining. A case study on a large copper deposit summarized in the paper shows substantial economic benefit of the proposed algorithm compared to existing methods.     

Optimal scheduling of parallel machines with constrained resources

This paper analyzes a manufacturing system consisting of parallel machines, which produce one product-type with controllable production rates subject to continuously-divisible, time-dependent resources. The objective is to produce the required amount of product-type units by a due date while minimizing inventory, backlog and production related costs over a production horizon. With the aid of the maximum principle, a number of analytical rules of the optimal scheduling is derived whereby the continuous-time scheduling is reduced to discrete sequencing and timing. As a result, a polynomial-time algorithm is developed for solving the problem.     

Integrated production and maintenance planning for parallel machine system considering cost of rejection

Production scheduling and maintenance planning have interdependencies but been often considered and optimized independently in practice and in the literature. Furthermore, product quality has direct relationship with maintenance planning. This paper proposes an integrated approach for production scheduling and maintenance planning for parallel machine system considering the effect of cost of rejection. The approach aims to determine optimal production schedule and maintenance plan such that overall operations cost is minimized. A simulation-based optimization approach is used to solve the problem. A numerical investigation is performed to illustrate the approach. The integrated approach shows between 0.6 and 35.8% improvement in term of overall operations cost over independent approach for various scenarios. The results indicate that simultaneous consideration of production scheduling and maintenance planning results into better system performance.     

A Worst-case Performance of the Shortest-processing-time Heuristic for Single Machine Scheduling

This paper analyses a worst-case performance of the shortest-processing-time (SPT) heuristic in minimizing a quadratic function of job lateness for single machine scheduling. A sufficient condition on processing-plus-wait due dates is found for the SPT sequence to be optimal. A worst-case lower bound to the optimal solution is derived from the SPT sequence. It is then shown that the SPT sequence is asymptotically optimal. Extensive computational experiments suggest that the SPT heuristic may be a good choice for just-in-time production.     

A profit-maximizing economic lot scheduling problem with price optimization

The economic lot scheduling problem (ELSP) is a well known problem that focuses on scheduling the production of multiple items on a single machine such that inventory and setup costs are minimized. In this paper, we extend the ELSP to include price optimization with the objective to maximize profits. A solution approach based on column generation is provided and shown to produce very close to optimal results with short solution times on a set of test problems. The results are discussed and recommendations for further research are provided.     

Hybrid evolutionary optimization of the operation of pipeless plants

Pipeless plants are a new production concept in chemical engineering in which automated guided vehicles (AGVs) transport the substances in mobile vessels between processing stations. In the operation of such plants, decisions have to be made on the scheduling of the production, the assignment of the equipment and the routing of the AGVs that carry the vessels. The large number of interacting degrees of freedom prohibit the use of exact mathematical algorithms to compute optimal schedules. This paper describes the combination of an evolutionary scheduling algorithm with a simulation based schedule builder. The algorithm is tested on a real-life example and on a benchmark problem from the literature and yields considerably shorter makespans than a heuristic solution.     

Optimal Production and Setup Scheduling: A One-Machine, Two-Product System

This paper studies the scheduling problem for two products on a single production facility. The objective is to specify a production and setup policy that minimizes the average inventory, backlog, and setup costs. Assuming that the production rate can be adjusted during the production runs, we provide a close form for an optimal production and setup schedule. Dynamic programming and Hamilton–Jacobi–Bellman equation is used to verify the optimality of the obtained policy.     

Tracking Demands in Optimal Control of Managerial Systems with Continuously-Divisible, Doubly Constrained Resources

The paper addresses problems of allocating continuously divisible resources among multiple production activities. The resources are allowed to be doubly constrained, so that both usage at every point of time and cumulative consumption over a planning horizon are limited as it is often the case in project and production scheduling. The objective is to track changing in time demands for the activities as closely as possible. We propose a general continuous-time model that states the problem in a form of the optimal control problem with non-linear speed-resource usage functions. With the aid of the maximum principle, properties of the solutions are derived to characterize optimal resource usage policies. On the basis of this analytical investigation, numerical scheduling methods are suggested and computationally studied. This revised version was published online in July 2006 with corrections to the Cover Date.     

Cyclic scheduling for F.M.S.: Modelling and evolutionary solving approach

This paper concerns the domain of flexible manufacturing systems (FMS) and focuses on the scheduling problems encountered in these systems. We have chosen the cyclic behaviour to study this problem, to reduce its complexity. This cyclic scheduling problem, whose complexity is NP-hard in the general case, aims to minimise the work in process (WIP) to satisfy economic constraints. We first recall and discuss the best known cyclic scheduling heuristics. Then, we present a two-step resolution approach. In the first step, a performance analysis is carried out; it is based on the Petri net modelling of the production process. This analysis resolves some indeterminism due to the system’s flexibility and allows a lower bound of the WIP to be obtained. In the second step, after a formal model of the scheduling problem has been given, we describe a genetic algorithm approach to find a schedule which can reach the optimal production speed while minimizing the WIP. Finally, our genetic approach is validated and compared with known heuristics on a set of test problems.