Showing papers on "Job shop scheduling published in 1984"

ISIS—a knowledge‐based system for factory scheduling

Abstract: Analysis of the job shop scheduling domain has indicated that the crux of the scheduling problem is the determination and satisfaction of a large variety of constraints. Schedules are influenced by such diverse and conflicting factors as due date requirements, cost restrictions, production levels, machine capabilities and substitutability, alternative production processes, order characteristics, resource requirements, and resource availability. This paper describes ISIS, a scheduling system capable of incorporating all relevant constraints in the construction of job shop schedules. We examine both the representation of constraints within ISIS, and the manner in which these constraints are used in conducting a constraint-directed search for an acceptable schedule. The important issues relating to the relaxation of constraints are addressed. Finally, the interactive scheduling facilities provided by ISIS are considered.

Sequencing Rules and Due-Date Assignments in a Job Shop

Abstract: Recent research studies of job shop scheduling have begun to examine the interaction between sequencing priorities and the method of assigning due-dates. This paper surveys the tactical aspects of this interaction, focusing primarily on average tardiness as a measure of scheduling effectiveness. The discussion highlights several factors that can affect the performance of dispatching rules, such as the average flow allowance, the due-date assignment method, and the use of progress milestones. A set of simulation experiments illuminates how these factors interact with the dispatching rule, and the experimental results suggest which combinations are most effective in a scheduling system.

Tighter Bounds for the Multifit Processor Scheduling Algorithm

Abstract: This paper considers the problem of nonpreemptively scheduling n independent jobs on m identical, parallel processors with the object of minimizing the “makespan”, or completion time for the entire...

Scheduling School Buses

Abstract: In the scheduling situation considered here, we are given a set of routes, each associated with a particular school. A single bus is assigned to each route, picking up the students and arriving at their school within a specified time window. The scheduling problem is to find the fewest buses needed to cover all the routes while meeting the time window specifications. We present two integer programming formulations of the scheduling problem and apply them to actual data from New Haven, Connecticut for two different years, as well as to 30 randomly generated problems. Linear programming relaxations of these integer programs were found to produce integer solutions more than 75 percent of the time. In the remaining cases, we found that the few fractional values can be adjusted to integer values without increasing the number of buses needed. Our method reduces the number of buses needed by about 25 percent compared to the manual solutions developed by the New Haven school bus scheduler.

Scheduling independent tasks on uniform processors

Abstract: A worst-case analysis is given for the LPT (longest processing time) heuristic applied to the problem of scheduling independent tasks on uniform processors. A bound of $\frac{19}{12}$ is derived on the ratio of the heuristic to the optimal makespan and an example is given where the error is greater than $\frac{{3}}{{2}}$. A generalization of the classic result of Graham for the case of identical processors is given. Here tight bounds are derived for the ratio of the heuristic to the optimal makespan which depends on the ratio of the longest task to the makespan.

Some new results in flow shop scheduling

Abstract: The problems of finding a schedule with minimal maximum lateness, respectively with minimal mean flow time for 2-machine flow shops with no wait in process, and related problems, including versions with unit processing times and a single resource constraint, are shown to be NP-hard in the strong sense. An algorithm is presented which finds a minimum makespan schedule with no wait in process for the 2-machine unit processing time flow shop under a single resource constraint inO (n logn) time. The obtained results continue to hold for the corresponding preemptive respectively nonpreemptive cases.

Autonomous Manufacturing: Automating the Job-Shop

Abstract: The term \"factory of the future\" has lost much of its meaning because of excessive publicity heralding each new machine tool, robot, or computer-based controller. It has become increasingly difficult to differentiate between fact and fantasy. Our purpose in writing this article is to examine some of the issues involved in creating an \"autonomous manufacturing environment\" for discrete parts. We restrict the concept of autonomous manufacturing to only the activities performed on the shop floor. In particular, autonomous manufacturing pertains to the complete automation of decision making on the shop floor, whether or not the actual production is performed manually or automatically. While much of computer-aided manufacturing has been concerned with \"flexible automation,\" we are concerned with the decision-making methodologies required for planning and control. The introduction of robotic and other flexible technologies into manufacturing increases the number of ways a product can be produced and decreases the production rate. Unfortunately , flexible technologies increase the complexity of operation and production scheduling and, because of the subsequent decrease in setup times, there is less time for decision making. Today, decisions made manually in the shop are less than satisfactory, demonstrated by high in-process time of orders, low machine utilization, and high overheads. Such manual planning and control methods limit our ability to utilize the flexibility afforded by robotic technology. We investigate the issues involved in constructing software systems for the planning and control of activities in the job-shop. Manufacturing is composed of many activities that can be monitored and controlled at different levels of abstraction. A shop floor can be viewed as a group of work centers, a work center as composed of manufacturing cells, and a manufacturing cell as composed of individual machines, robots, and tools (see Figure 1). Activity planning in such an environment is a complex problem in which activities must be selected and resources must be assigned and scheduled at each level of abstraction to meet production goals. While much of this can be performed before production begins, the dynamics of the manufacturing environment tend to quickly invalidate predictive planning, forcing the shop to adapt to changes. In our discussion, we assume the existence of a shop with the following characteristics: * a set of predefined parts to be produced in small batchese * one or more sequences of manufacturing operations defined for each part; * one or more work centers in which an operation is …

A framework for the probabilistic analysis of hierarchical planning systems

Abstract: As we have argued in previous papers, multi-level decision problems can often be modeled as multi-stage stochastic programs, and hierarchical planning systems designed for their solution, when viewed as stochastic programming heuristics, can be subjected to analytical performance evaluation. The present paper gives a general formulation of such stochastic programs and provides a framework for the design and analysis of heuristics for their solution. The various ways to measure the performance of such heuristics are reviewed, and some relations between these measures are derived. Our concepts are illustrated on a simple two-level planning problem of a general nature and on a more complicated two-level scheduling problem.

The design and validation of a digital simulation model for job shop control decision making

Abstract: A previous paper (Browne et al. 1981) identified the decision making problems associated with job shop control and presented an objective function for measuring its performance. Given that definition of job shop control and cost-based objective function, simulation modelling offers the best prospect of a solution of the problem of providing a management tool to aid in the decision making associated with job shop control. This paper provides a detailed analysis of the design of such a model. The model, written in the GASP fV simulation language and running on a CDC 7600 computer, is based on the job shop of a major machine tool manufacturer and has been validated against actual job shop performance.

Optimal policies in stochastic shop scheduling

Abstract: In this paper a survey is presented of some of the recent results in stochastic open shop, flow shop and job shop scheduling. The distributions of the processing times of the jobs are known in advance, but the actual processing times are not known in advance. The jobs may have due dates. Optimal preemptive and nonpreemptive policies are determined for the minimization of various objective functions, such as the expected makespan, the expected flow time and the expected number of late jobs. The effect of various degrees of dependence between the processing times of any given job on the various machines is investigated. Under given conditions bounds are obtained for the expected makespan in the different models.

Stochastically minimizing the makespan in flow shops

Abstract: In this article, we are concerned with scheduling stochastic jobs in a flowshop with m machines and zero intermediate storage. We assume that there are n - 2 identically distributed and 2 fast stochastic jobs. Roughly, the main result states that the makespan is stochastically minimized by placing one of the fast jobs first and the other last.

Fuel Resource Scheduling, Part III-The Short-Term Problem

Abstract: The paper presents a method for optimum scheduling of fuels over a few days, subject to fuel supply limits, spanning different time periods, and unit operating constraints. Constraints over mixed and shared fuels, are also considered. Results for a 17 unit/17 contract test system over a two day study period are presented and discussed. Scheduling fuel resources, in the short term, to satisfy fuel supply and consumption constraints is a nontrivial task for planning and operating engineers of an electric utility. The complexity of the problem increases when one has to consider the fuel constraints over different time periods (hour, day, combination of days, etc.) simultaneously. When the (linear) fuel constraints are coupled with the linear and nonlinear operating constraints of the system the complexity of the scheduling problem becomes a mathematical challenge for the operation researchers and is beyond the reach of intuitive methods. The current techniques for planning the operation of generating units in a power system subject to operating and fuel supply constraints share the following common features. 1) Daily (or study period) fuel supply limits are either too broad to be constraining or so narrow that they can be specified as fixed amounts that must be consumed. Either daily limits or study period limits (but not both) can be specified in a given study. 2) All hourly fuel supply constraints are translated as hourly constraints on the capacity of individual units. 3) Price of the fuel to be used by a unit is known apriori.

Impact of New Energy Technologies on Generation Scheduling

Abstract: Certain practices for the scheduling and dispatching of electric generation have become commonplace in the utility industry. These methods all take advantage of the fact that the generation for a power system is normally supplied from a small number of large units connected to the high voltage transmission system. Most of the new generation technologies, however, are much smaller in unit size and may be well dispersed. In this paper a critical examination is made of the impact of these new technologies on the generation scheduling methods. No particular technology is examined in detail but the general characteristics of all the new technologies are taken into consideration. The scheduling practices considered range from the real time load frequepcy control and economic dispatch to the weekly (short term) and yearly (long term) scheduling of generating units. It is shown that the impact will be significant and the exact effects will depend on the level of penetration, the extent of dispersion, ownership, and the weather dependency of the technologies selected.

An Air Force Crew Allocation and Scheduling Problem

Abstract: This paper considers an airline crew allocation and scheduling problem faced by certain divisions of the United States Air Force. Two variants of the problem under consideration were posed to us by the U.S. Air Force. This paper reports our experience with two heuristic methods developed, each applicable to either variant of the problem. Although the problem described herein is peculiar to this situation, the heuristic scheduling and dispatching rules developed have been found to be very effective and are generally applicable in other related contexts of routeing and crew and vehicle scheduling problems as well. The two algorithms developed have been applied to a coded set of real world data. The results indicate that each one of the two methods is preferable to the other for one of the two variants of the problem. This suggests an overall effective composite technique.

Operation planning of large-scale hydroelectrical systems

Abstract: This paper presents the methodology and models developed to solve the operations scheduling problem for the Brazilian system. A chain of four individual programs ranging from hourly transmission-constrained dispatch to multi-year reservoir optimization has been used. The output of the programs at higher levels impose targets or constraints on the lower level programs. In addition, feedback links from lower level to higher level programs help ensure a global optimization of the scheduling process. The techniques employed to solve the scheduling problems at each level include stochastic dynamic programming, Dantzig-Wolfe decomposition, network flows and multistage stochastic Benders decomposition.

Short term production scheduling of an automated manufacturing facility

Abstract: We describe extensions to the on-line hierarchical scheduling scheme for flexible manufacturing systems of Kimemia and Gershwin. Major improvements to all levels of the algorithm are reported, including algorithm simplification, substantial reductions of off-line and on-line computation time, and improvement of performance. Simulation results based on a detailed model of an IBM printed circuit card assembly facility are summarized.

Inequalities and bounds in stochastic shop scheduling

Abstract: In this paper, stochastic shop models with m machines and n jobs are considered. A job has to be processed on all m machines, while certain constraints are imposed on the order of processing. The effect of the variability of the processing times on the expected completion time of the last job (the makespan) and on the sum of the expected completion times of all jobs (the flow time) is studied. Bounds are obtained for the expected makespan when the processing time distributions are New Better (Worse) than Used in Expectation.

A Generalized Goal Programming Approach to the Minimal Interference, Multicriteria N × 1 Scheduling Problem

Abstract: The conventional approach to the modeling and solution of most scheduling problems involves the development of a mathematical model which (1) employs discrete variables (e.g., linear integer programs), and (2) includes only a single objective to be maximized or minimized (e.g., minimization of makespan). Unfortunately, models involving discrete variables are inherently combinatorially explosive (i.e., methods such as branch-and-bound will exhibit computation times which grow exponentially with problem size). Further, scheduling problems encountered in the real world invariably involve multiple conflicting objectives, and thus using a single-objective representation can lead to gross oversimplification. In this paper we address a specific class of scheduling problem encountered in several real-world applications that may be efficiently addressed as a linear multiobjective model having only continuous variables. The model and its solution are compared with those of a highly acclaimed recent approac...

State dependent priority rules for scheduling

Abstract: : The purpose of this thesis is to enhance the priority setting procedures for job shop scheduling systems. The new state dependent priority rules extend the concept of a myopic dispatching heuristic by allowing a wide choice of forecasting and planning horizons and by encompassing indirect or direct load information, even performance feedback, while maintaining the flexibility and robustness of the dispatching approach. Preliminary results are proven in the special case of proportionate flow shops with pre-emption. Many optimal rules for lateness and tardiness problems are extended from the single machine case to flow shops. Appropriate lead time estimation used in setting operation due dates can be shown to guarantee the achievement of a global optimum when applying a myopic rule locally. In more general job shop environments, we study scheduling with due dates when jobs have different tardiness penalties. Advanced slack evaluation methods have been developed for our Apparent Urgency rule and for the modified CoverT rule. First, waiting line analysis furnishes the use of indirect load information, such as the distribution of the jobs' weights and processing times, in assigning static priority-based waiting time estimates for each operation. Second, the waiting time estimation and look-ahead parameters of the rules are further adjusted on the basis of direct, periodically updated state information, such as the anticipated queue lengths in the shop. Third, an iterative scheme is used to revise new lead time estimates based on the jobs' realized waiting times in successive schedules. This lead time iteration provides also feedback from the performance of the rule for the coordination of the priority assignments.

Minimizing the makespan in a 2-machine flowshop with time lags and setup conditions

Abstract: A special case of the flowshop problem of sequencingn jobs on two machines, to minimize the makespan, is solved under setup considerations and with time lags.