Generating all efficient solutions of a rescheduling problem on unrelated parallel machines

In this paper, we consider a rescheduling problem where a set of jobs has already been assigned to unrelated parallel machines. When a disruption occurs on one of the machines, the affected jobs are rescheduled, considering the efficiency and stability measures. Our efficiency measure is the total flow time and stability measure is the total reassignment cost caused by the differences in the machine allocations in the initial and new schedules. We propose a branch and bound algorithm to generate all efficient solutions with respect to our efficiency and stability measures. We improve the efficiency of the algorithm by incorporating powerful reduction and bounding mechanisms. Our computational tests on large sized problem instances have revealed the satisfactory behaviour of our algorithm.     

Flow shop rescheduling under different types of disruption

Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimise the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand, and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.     

Match-up approaches to a dynamic rescheduling problem

This article considers the problem of inserting arriving jobs into an existing schedule of a real world manufacturer. A number of match-up strategies, which collect the idle time on machines of a current schedule for the insertion of new jobs, are proposed. Their aim is to obtain new schedules with a good performance which are at the same time highly stable, meaning that they resemble as closely as possible the initial schedule. Basic rescheduling strategies such as ‘total rescheduling’, ‘right shift’ and ‘insertion in the end’ deliver either good performance or stability, but not both. Contrarily, our experimentation and statistical analysis reveal that the proposed match-up strategies deliver high performing schedules with a high stability. An analysis of the problem parameters that determine the behaviour of the proposed match-up algorithms is included in this article.     

A review of: “Engineering Reliability: Fundamentals and Applications”. By R. RAMAKUMAR (Prentice-Hall, 1993) [Pp. xiii + 482].

In this work, an algorithm for rescheduling the affected operations in a job shop is presented and its performance, with respect to measures of efficiency and stability, is compared with that of Total Rescheduling and Right-Shift Rescheduling. Algorithms for all three methods are implemented in a rescheduling program which, based on keyed-in disruption information, produces three new schedules and outputs their related performance measures. A designed factorial experiment is performed on benchmark scheduling problems to study the effect of different rescheduling methods as well as various problem characteristics and disruption scenarios on the performance of the new schedules. The results demonstrate that the Affected Operations Algorithm overcomes the disadvantages associated with other rescheduling methods.     

The model of maintenance planning and production scheduling for maximising robustness

The accuracy of prediction and detection capability have a strong influence over the efficiency of the bottleneck, all equipment and the production system. The function of predictive scheduling is to obtain stable and robust schedules for a shop floor. The first objective is to present an innovative maintenance planning and production scheduling method. The approach consists of four modules: a database to collect information about failure-free times, a prediction module of failure-free times, predictive scheduling and rescheduling module, a module for evaluating the accuracy of prediction and maintenance performance. The second objective is to apply the proposed methods for a job shop scheduling problem. Usually, researchers who are concerned about maintenance scheduling do not take unexpected disturbances into account. They assume that machines are always available for processing tasks during the future-planned production time. Moreover, researches use the criteria that are not effective to deal with the situation of unpredicted failures. In this paper, a method based on probability theory is proposed for maintenance scheduling. For unpredicted failures, a rescheduling method is also proposed. The evaluation module which gives information about the degradation of each performance measure and the stability of a schedule is proposed.     

Coordination activities of human planners during rescheduling: case analysis and event handling procedure

This paper addresses the process of event handling and rescheduling in manufacturing practice. Firms are confronted with many diverse events, such as new or changed orders, machine breakdowns, and material shortages. These events influence the feasibility and optimality of schedules, and thus induce rescheduling. In many manufacturing firms, schedules are created by several human planners. Coordination between them is needed to respond to events adequately. In this paper, the practice of coordination during event handling is analysed by an extensive case study. The study shows that human planners spend much time in communicating events and in negotiating rescheduling solutions. Because many events demand a quick response, the possibilities for coordination are restricted by time constraints. The paper proposes a procedure to structure the event handling process. This procedure helps a scheduler to select an appropriate response to an event by evaluating its influence on schedule feasibility and the time available for coordination and rescheduling. The use of the procedure in the case company has led to improved rescheduling performance through a reduction of scheduler interactions and increasing coordination efficiency. The procedure contributes to traditional planning frameworks and paradigms, and supports the conscious selection and use of rescheduling methods in manufacturing practice.     

Dynamic co-ordinated scheduling in the supply chain considering flexible routes

In Supply chain (SC) environments, schedules inevitably experience various unexpected disruptions. In these cases, rescheduling is essential to minimise the negative impact on the performance of the system. In this study, a hybrid rescheduling technique is developed for solving coordinated manufacturing tasks scheduling problems with due date changes and machine breakdowns. According to the dynamic features of this problem, a strategy combined with event and periodic driven methods is proposed to improve the stability and robustness of manufacturing performance in a coordinated SC. Moreover, an application case is introduced to test and evaluate the effect of different initialisations in two types of disruption scenarios. The experimental results show that the proposed rescheduling technique has good effectiveness and efficiency in the coordinated manufacturing environment.     

Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives

We consider a machine rescheduling problem that arises when a disruption such as machine breakdown occurs to a given schedule. Machine unavailability due to a breakdown requires repairing the schedule as the original schedule becomes infeasible. When repairing a disrupted schedule a desirable goal is to complete each disrupted job on time, i.e. not later than the planned completion time in the original schedule. We consider the case where processing times of jobs are controllable and compressing the processing time of a job requires extra processing cost. Usually, there exists a nonlinear relation between the processing time and manufacturing cost. We solve a bicriteria rescheduling problem that trades off the number of on-time jobs and manufacturing cost objectives. We give a mixed-integer second-order cone programming formulation for the problem. We develop a heuristic search algorithm to generate efficient solutions for the problem. Heuristic algorithm searches solution space by moving and swapping jobs among machines. We develop cost change estimates for job moves and swaps so that the heuristic implements only promising moves and hence generates a set of efficient solutions in reasonably short CPU times.     

Coordinating production and distribution of jobs with bundling operations

We consider an integrated scheduling and distribution model in which jobs completed by two different machines must be bundled together for delivery. The objective is to minimize the sum of the delivery cost and customers' waiting costs. Such a model not only attempts to coordinate the job schedules on both machines, but also aims to coordinate the machine schedules with the delivery plan. Polynomial-time heuristics and approximation schemes are developed for the model with only direct shipments as well as the general model with milk-run deliveries.     

Minimising interference for scheduling two parallel machines with a single server

In this paper, we consider the problem of scheduling a set of jobs on two parallel machines with set-up times. The set-up has to be performed by a single server. The objective is to minimise the forced idle time. The problem of minimising the forced idle time (interference problem) is known to be unary NP-hard for the case of two machines and equal set-up and arbitrary processing times. We propose a mixed integer linear programming model, which describes a special class of schedules where the jobs from a list are scheduled alternatively on the machines, and a heuristic algorithm is tested on instances with up to 100,000 jobs. The computational results indicate that the algorithm has an excellent performance even for very large instances, where mostly an optimal solution is obtained within a very small computational time.     

Coordinated scheduling of customer orders with decentralized machine locations

We consider a scheduling model with two machines at different locations. Each job is composed of two tasks where each task must be processed by a specific machine. The finished tasks are shipped to a distribution center in batches before they are bundled together and delivered to customers. The objective is to minimize the sum of the delivery cost and customers' waiting costs. This model attempts to coordinate the production and delivery schedules on the decentralized machines while taking into consideration the shipping cost as well as the waiting time of the customers. We develop polynomial-time heuristic algorithms for this problem and analyze their worst-case performance. Computational experiments are conducted to test the effectiveness of the heuristics and to evaluate the benefits obtained by coordinating the production and delivery of the two decentralized machines.     

Predictable scheduling of a single machine with breakdowns and sensitive jobs

Production schedules released to the shop floor have two important functions: allocating shop resources to different jobs to optimize some measure of shop performance and serving as a basis for planning external activities such as material procurement, preventive maintenance and delivery of orders to customers. Schedule modification may delay or render infeasible the execution of external activities planned on the basis of the predictive schedule. Thus it is of interest to develop predictive schedules that can absorb disruptions without affecting planned external activities while maintaining high shop performance. We present a predictable scheduling approach, that inserts additional idle time into the schedule to absorb the impacts of breakdowns. The effects of disruptions on planned support activities are measured by the deviations of job completion times in the realized schedule from those in the predictive schedule. We apply our approach to minimizing total tardiness on a single machine with stochastic machine failures. We then extend the procedure to consider the case where job processing times are affected by machine breakdowns, and provide specialized rescheduling heuristics. Extensive computational experiments show that this approach provides high predictability with minor sacrifices in shop performance.     

Scheduling railway traffic at a construction site

We consider the problem of rescheduling trains in the case where one track of a railway section consisting of two tracks in opposing directions is closed due to construction activities. After presenting an appropriate model for this situation we derive a polynomial algorithm for the subproblem of finding an optimal schedule with minimal latenesss if the subsequences of trains for both directions outside the construction site are fixed. Based on this algorithm we propose a local search procedure for the general problem of finding good schedules and report test results for some real world instances. Received: December 8, 1999 / Accepted: May 2, 2001     

A new method for workshop real time scheduling

Workshop real time scheduling is one of the key factors in improving manufacturing system efficiency. This is especially true for workshops in which various products are processed simultaneously, and use multipurpose machines. Real time scheduling is appropriate to handle perturbations in the environment of the manufacturing process, a major issue at the shop floor level. The products to be processed have release times and due dates and the resources are multipurpose machines. A decision support system for real time scheduling is described. It is based on an original approach, aiming at searching for characteristics of a set of schedules compatible with the main manufacturing constraints to be satisfied. This set of schedules is obtained by defining sequences of groups of permutable operations for every resource. A method to find such a set is described. We emphasize the use of this group sequence as a decision support system. Significant states and events requiring real time decisions are identified and three main types of decisions are analysed. For each of them, the proposed decision support system is detailed and explained.     

Distributed supply‐chain project rescheduling: Part I—impacts of information‐sharing strategies

A supply‐chain project normally involves a number of independent and autonomous enterprises that share information to varying levels. The initial project schedule (preschedule) established at the time of forming the supply‐chain often requires a series of amendments due to unexpected or abrupt disturbances such as temporary resource outage (e.g. machine break), arrival or cancellation of orders from customers, and change in an operation's processing time (e.g. rework). Rescheduling or adaptive scheduling is a process of updating/repairing the preschedule to adapt to the disturbances. Appropriate rescheduling methods must be chosen and applied depending on the specific protocol of sharing information agreed between the enterprises in the supply chain. This paper is concerned with the impacts of different levels of information sharing on the performance of supply‐chain project rescheduling problems. Three rescheduling methods are examined in the research. They are distributed AOR (Affected Operations Rescheduling), negotiation‐based rescheduling (NEG), and centralized total rescheduling (TR). These three rescheduling algorithms represent three typical information‐sharing scenarios: little information sharing, limited information sharing and complete information sharing, respectively. A comprehensive computational study is conducted under different experimental settings. The results show that NEG and distAOR outperforms the TR rescheduling in terms of total cost minimization and stability of schedule and contractual relationship. NEG is superior in both rescheduling efficiency and effectiveness due to the effect of a moderate level of information sharing.     

A discrete time reactive scheduling model for new order insertion in job shop,make-to-order industries

This research presents a new reactive scheduling methodology for job shop, make-to-order industries. An integer linear programming formulation previously developed by the authors to schedule these types of industries is extended to address the problem of inserting new orders in a predetermined schedule, which is important in order-driven industries. A reactive scheduling algorithm is introduced to iteratively update the schedules. Numerical results on realistic examples of job shops of different sizes illustrate the effectiveness of the approach. In each case, different alternatives for inserting a set of new orders in an initial schedule are optimally generated, enabling the user to choose the most convenient one. Solutions are characterised by measures of scheduling efficiency as well as stability measures that assess the impact of rescheduling operations in a previously defined scheduling solution.     

Extending the boundaries between scheduling and dispatching: hedging and rescheduling techniques

While deterministic scheduling models have been well studied, the use of these models is not well documented in manufacturing environments. Previous research has indicated that deterministic scheduling approaches quickly lose their advantage compared to dispatching rules when processing time uncertainty is present. This research presents the case of a Printed Wiring Board Manufacturer’s drilling operation, which is a group of unrelated parallel machines. The manufacturer wishes to minimise makespan, number of late jobs, total overtime, average machine finishing time and machine utilisation when stochastic uncertainty is present. While deterministic scheduling has been shown to be a good solution approach when processing time variability is low, this research attempts to extend the boundaries in which scheduling is useful by investigating job and machine hedges as well as periodic and event driven rescheduling policies. The success of the approach is evaluated using a simulation model to evaluate the performance over a number of sequential schedules under various distributional assumptions.     

An Analysis of Scheduling Policies In Multiechelon Production Systems

Results of a simulation study of the economics of frequency of rescheduling Material Requirements Planning (MRP) systems are presented for a single-product, two-stage system in which demand is uncertain. The results indicate that for systems with moderate demand uncertainty, frequent rescheduling to maintain customer service may be uneconomical when compared with the alternative of more stable schedules in conjunction with safety stock. This result arises primarily because the cost of “emergency” production setups which occur when rescheduling is frequent exceeds the cost of safety stock required to “protect” stable schedules.     

Research on rush order insertion rescheduling problem under hybrid flow shop based on NSGA-III

Rush order insertion is widespread in the enterprises that apply make-to-order production mode which affects the stability of production system. This article studies rush order insertion rescheduling problem (ROIRP) under hybrid flow shop (HFS) with multiple stages and multiple machines. A mathematical model simultaneously considering constraints such as lots, sequence-dependent set-up times and transportation times with objectives to minimise makespan, total transportation time and total machine deviation between the initial scheduling plan and the event-driven rescheduling plan is developed and NSGA-III is applied to solve the problem. Three groups of experiments are carried out which verify the suitability of NSGA-III for HFS scheduling problem with multi-objective and multi-constraint, the effectiveness of NSGA-III for the proposed ROIRP and the feasibility and effectiveness of the proposed model and algorithm in solving the ROIRP of a realistic ship pipe parts manufacturing enterprise.     

反相容工件系统的加权完工时间和的重新排序问题(英文)

重新排序问题是指在原始工件已经安排好的情形下,新到的工件集与原始工件集一起重新再排序,这是实际工作中常见一类优化问题。本文考虑了单机上当工件加工时间与权重反相容时,在最大错位量约束下的加权完工时间和最小化的重新排序问题。对于提出的四个问题,即在最大序列错位、最大时间错位、总序列错位和总时间错位约束下的加权完工时间和重新排序,基于问题的结构性质,运用动态规划方法分别给出了这些问题的多项式时间或拟多项式时间算法。