Showing papers on "Job shop scheduling published in 1983"
TL;DR: The results for mean tardiness indicate that the modified operation due date (MOD) rule compares very favorably with other prominent dispatching methods, and appears to be more robust than the other rules to changes in the tightness of due dates, and similar results occurred at both high and low utilizations.
182 citations
TL;DR: A cyclic scheduling method that takes advantage of the flow character of the process and is predicated upon the requirement that during each cycle the shop should perform all of the tasks required to complete a job, although possibly on different jobs.
178 citations
TL;DR: In this article, the optimal preventive maintenance scheduling problem (OMSP) is addressed and the importance of OMSP is due to the fact that system reliability and operating cost of an electric utility are affected by the maintenance outage of generating facilities.
Abstract: This paper addresses the optimal preventive maintenance scheduling problem (OMSP). The importance of OMSP is due to the fact that system reliability and operating cost of an electric utility are affected by the maintenance outage of generating facilities.
127 citations
TL;DR: A polynomial time algorithm for constructing an optimal schedule, if a feasible schedule exists, for the following multimachine scheduling problem: n unit-time jobs, with arbitrary release times and deadlines, and m identical parallel machines.
Abstract: We present a polynomial time algorithm for constructing an optimal schedule, if a feasible schedule exists, for tthe following multimachine scheduling problem. There are n unit-time jobs, with arbitrary release times and deadlines, and m identical parallel machines. A feasible schedule is one in which no job is started before it is released, each job is completed by its deadline, and no job is interrupted once it begins to run.
99 citations
TL;DR: A branch-and-bound algorithm for a two-machine scheduling problem by Grabowski is generalized to the case of an arbitrary number of machines and an approach to strengthen these lower bounds is developed.
Abstract: A branch-and-bound algorithm for a two-machine scheduling problem by Grabowski is generalized to the case of an arbitrary number of machines. The lower bounds are obtained by the relaxation of the capacity constraints on the machines. An approach to strengthen these lower bounds is developed. Computational experience with 6-, 10-, 15-, 20-, 30-, 40-, 50-job problems is presented.
77 citations
TL;DR: The technique is able to "translate" the electrical problems at the short-term level into a constraint to be added to the mid-term scheduling problem, called a Benders cut, which allows a "feedback" between the short and mid- term models with only a few modifications required in the specialized algorithms used at each level.
Abstract: This paper describes a methodology for coordinating the mid and short-term scheduling of hydrothermal systems. The technique is able to "translate" the electrical problems at the short-term level into a constraint to be added to the mid-term scheduling problem. This constraint, called a Benders cut, only refers to weekly target variables in the mid-term problem. The Benders decomposition therefore allows a "feedback" between the short-and mid-term models with only a few modifications required in the specialized algorithms used at each level. A case study with the Brazilian Southeast Network is presented and discussed.
73 citations
TL;DR: This paper considers the problem of minimizing a linear combination of flow times and max-mum tardiness of a given number of jobs on a single machine and presents a branch-and-bound technique to arrive at an optimal solution.
Abstract: Most scheduling research is done with one criterion; however, the real-world situations demand consideration of multicriterion problems because there are generally many costs associated with scheduling decisions. This paper considers the problem of minimizing a linear combination of flow times and max-mum tardiness of a given number of jobs on a single machine and presents a branch-and-bound technique to arrive at an optimal solution. The computational results are also reported.
65 citations
TL;DR: A variation of the MULTIFIT algorithm derived from bin packing is analyzed, and it is proved that its worst-case performance bound is within 1.4 of the optimum.
Abstract: The authors examine the nonpreemptive assignment of n independent tasks to a system of m uniform processors with the objective of reducing the makespan, or the time required from the start of execution until all tasks are completed. Since the problem of finding a minimal makespan has been shown to be np-hard, and hence unlikely to permit an efficient solution procedure, near-optimal heuristic algorithms have been studied. It is known that lpt (longest processing time first) schedules are within twice the length of the optimum. They analyze a variation of the multifit algorithm derived from bin packing, and prove that its worst case performance bound is within 1.4 of the optimum. 10 references.
57 citations
TL;DR: Surrogate duality bounds for the job shop scheduling problem are obtained by replacing certain constraints by their weighted sum and strengthening the aggregate constraint by iterating over all possible weights.
56 citations
01 Apr 1983
TL;DR: In this paper, a mixed-integer formulation of the mine scheduling problem is discussed and applied for the purpose of optimizing both the mine production sequencing and the mill blending and processing problems simultaneously.
Abstract: A mixed-integer formulation of the mine scheduling problem is discussed and applied for the purpose of optimizing both the mine production sequencing and the mill blending and processing problems simultaneously. Previous attempts at solving these problems separately, although successful, fail to take into account the interrelationships between these problems. Project structure serves as the outline of this paper. Generalized in its organization, this concept is useful for long, intermediate, and short range scheduling. Actual applications that show the concept also is applicable to mining a variety of ore are mentioned.
54 citations
TL;DR: Research in the modeling of organizations, constraint- based job-shop scheduling, organization simulation, user interfaces, and system architecture is described, and examples of working systems are provided.
TL;DR: A branch and bound algorithm is presented to obtain the optimal schedule that minimizes the maximum tardiness with minimum number of tardy jobs.
TL;DR: In this article, two simple versions of this two-stage hierarchical scheduling problem are presented, and heuristic solution methods are described and their performance is asymptotically optimal both in expectation and in probability.
Abstract: Certain multistage decision problems that arise frequently in operations management planning and control allow a natural formulation as multistage stochastic programs. In job shop scheduling, for example, the first stage could correspond to the acquisition of resources subject to probabilistic information about the jobs to be processed, and the second stage to the actual allocation of the resources to the jobs given deterministic information about their processing requirements. For two simple versions of this two-stage hierarchical scheduling problem, we describe heuristic solution methods and show that their performance is asymptotically optimal both in expectation and in probability.
01 Jan 1983
TL;DR: ISIS is described, a scheduling system capable of incorporating all relevant constraints in the construction of job shop schedules and both the representation of constraints within ISIS and the manner in which these constraints are utilized in conducting a constraint-directed search for an acceptable schedule are examined.
Abstract: 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 number and variety of constraints. Schedules are influenced by such diverse factors as due date requirements, cost restrictions, production levels, machine capabilities, operation precedences, 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. The authors examine both the representation of constraints within ISIS, and the manner in which these constraints are utilized 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. (Author)
IBM1
TL;DR: The traffic scheduling problem in an SS/TDMA system with interfering beams is studied and the first step can be solved in polynomial time in most cases, while the second step is proved to be NP-complete, even for very simple interference patterns.
Abstract: In this paper we study the traffic scheduling problem in an SS/TDMA system with interfering beams. We investigate a twostep approach, the first step being the assignment of orthogonal polarization to reduce the interference, and the second step being the scheduling of traffic, taking into account the "resultant" interference. The first step we show can be solved in polynomial time in most cases, while the second step we prove to be NP-complete, even for very simple interference patterns. We suggest several suboptimal algorithms for this second step and, by experimental trials on randomly generated traffic patterns, show that on the average they produce close to optimal solutions.
21 Jun 1983
TL;DR: In this article, the authors describe ISIS, a scheduling system capable of incorporating all relevant constraints in the construction of job shop schedules, and examine both the representation of constraints within ISIS, and the manner in which these constraints are utilized in conducting a constraint-directed search for an acceptable schedule.
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 number and variety of constraints. Schedules are influenced by such diverse factors as due date requirements, cost restrictions, production levels, machine capabilities, operation precedences, 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. The authors examine both the representation of constraints within ISIS, and the manner in which these constraints are utilized 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. (Author)
19 Jul 1983
TL;DR: This work is motivated by ongoing research with ISIS, an intelligent scheduling and information system currently being applied to the problem of scheduling job shops, and examples throughout the paper are drawn from this domain.
Abstract: : This paper examines the role of temporal knowledge in regard to the representation and utilization of constraints within time dependent problem domains. The author first considers the representation of constraints whose interpretations may vary in different temporal regions of the solution space. A representation that organizes constraint variants via the temporal relationships among them is presented and seen to support a simple mechanism for determining the applicable variant at any point in time. He then turns his attention to the management of temporal constraints that are dynamically imposed as various commitments are made by the reasoning system (e.g. as resources are allocated to activities in a plan). Constraint propagation techniques which collectively insure consistency in the hypotheses under development are presented and discussed. These techniques are driven by the temporal relationships present in the domain model. This work is motivated by ongoing research with ISIS, an intelligent scheduling and information system currently being applied to the problem of scheduling job shops, and examples throughout the paper are drawn from this domain. (Author)
TL;DR: The empirical results indicate that the proposed heuristic algorithms reduce CPU time as well as the number of iterations with only a slight loss in optimality.
Abstract: The column generation algorithm for the multi-item lot-size scheduling problem under resource constraints is examined and improved upon by augmenting simpler heuristic routines in place of the time-consuming Wagner-Whitin dynamic programming routine. The heuristic algorithms thus developed are tested by controlling problem size, setup time, demand variability, and capacity change costs in test problems. The empirical results indicate that the proposed heuristic algorithms reduce CPU time as well as the number of iterations with only a slight loss in optimality.
TL;DR: The algorithm, which is recommended for middle-size problems, is embedded in a dedicated minicomputer-based practical system meant for real time production control in a discrete part manufacturing system environment.
TL;DR: There does not seem to exist any such efficient algorithm to solve an n-job one machine scheduling problem in which processing times are random variables because the problem can be shown to be NP-complete.
Abstract: In 1973, Balut gave an algorithm to solve an n-job one machine scheduling problem in which processing times are random variables and the objective is to minimize the number of tardy jobs with a specified certainty level. This note, however, presents an example for which his algorithm fails to give an optimal schedule. Furthermore, there does not seem to exist any such efficient algorithm because the problem can be shown to be NP-complete.
TL;DR: An interactive job shop scheduling program and a new approach to due-date selection which is implemented in the program, which was designed for a labour constrained workshop at the University of Stellenbosch are described.
01 Dec 1983
TL;DR: A practical method for generating optimal schedules for online train traffic control in disturbed situations and it is shown that each subproblem generated in the second part, which is a linear programming problem, can be easily calculated without using the ordinary simplex method.
Abstract: A practical method for generating optimal schedules for online train traffic control in disturbed situations is proposed. This scheduling problem is formulated to a 0-1 mixed integer programming problem. The method of solution proposed here is mainly divided into two parts: the first part generates a suboptimal solution by a heuristic method based upon "Production System", and the second produces an optimal one by the branch-and-bound method using the above sub-optimal value for the initial bound. It is shown that each subproblem generated in the second part, which is a linear programming problem, can be easily calculated without using the ordinary simplex method. Some examples show that the proposed method has enough efficiency for practical use in both computational time and storage.
TL;DR: The proposed method for this problem is based on a new definition of composite jobs and Sidney's theory about series parallel algorithms, and can solve a version of the problem where each job has setup times not included in the processing times and a series-parallel precedence relation is specified among jobs in a group.
Abstract: The following two-machine flow-shop scheduling problem is solved. Given jobs are classified into groups, and each machine needs some setup before the first job in a group is started processing. If a job in a group is started its process, all jobs in the group must be finished before a job in another group is processed. Each job may have a specified lag time between machines. Moreover, a series-parallel precedence relation may be specified among groups. Find inter- and intra-group schedules minimizing the total elapsed times on both machines. The proposed method for this problem is based on a new definition of composite jobs and Sidney's theory about series parallel algorithms. The proposed method can also solve a version of the problem where each job has setup times not included in the processing times and a series-parallel precedence relation is specified among jobs in a group.
TL;DR: In this article, the authors determine the sequence of set-ups and quantity to produce in each setup if two products are to be produced on a single facility, considering the effects of learning and forgetting.
Abstract: The paper determines the sequence of set-ups and quantity to produce in each setup if two products are to be produced on a single facility, considering the effects of learning and forgetting. The cost expression which is to be minimized, consists of three factors: set-up cost, carrying cost and the cost of idle facility. A solution procedure is developed and the analysis is extended for the n-product system.
TL;DR: An empirical test is carried out to see whether transport operating cost between two points can be estimated from the corresponding straight-line distance, as often assumed in V.S.P. algorithms which have a cost-minimising objective.
Abstract: This paper is concerned with the use of straight-line distances in algorithms concerned with the solution of the vehicle scheduling problem (V.S.P.). An empirical test is carried out to see whether transport operating cost between two points can be estimated from the corresponding straight-line distance, as often assumed in V.S.P. algorithms which have a cost-minimising objective. The use of variance in V.S.P. algorithms is also discussed, especially in relation to travelled times on links and limits on goods vehicle drivers' hours.
TL;DR: This work presents methods which aim to answer the question of how well permutations perform as strategies in stochastic processing, based on earlier results by Glazebrook.
Abstract: A collection of stochastic jobs is to be processed by a single machine in a manner which is consistent with a precedence relation on the job set. Costs are incurred as jobs are processed and rewards are earned when they complete. The problem of finding optimal processing strategies is in general very complex. However, algorithms exist which in many cases yield the strategies which are optimal among those which are simply permutations of the job set. In light of this, the question of how well permutations perform as strategies is an important one. We present methods which aim to answer this question. They are based on earlier results by Glazebrook.
TL;DR: The two-machine, minimum-schedule-length case, where both open-shop and flow-shop scheduling problems belong to SP, is proved to be binary TISP-complete under a route-dependent open- shop discipline.
Abstract: Open-shop scheduling, where the processing times of the operations constituting a job depend on the route by which it passes through the machines, is proved to be the master problem of which both open-shop and flow-shop scheduling are special cases. The two-machine, minimum-schedule-length case, where both open-shop and flow-shop scheduling problems belong to SP, is proved to be binary TISP-complete under a route-dependent open-shop discipline. An 0(n) algorithm is presented for a special case of the latter problem with a dominating machine.
15 Aug 1983
TL;DR: Computational results show that the myopic heuristic performed well vis-a-vis other rules such as the Earliest Due Date Rule, Weighted Shortest Processing Time Rule and two versions of Montagne's Rule.
Abstract: : The authors study the problem of scheduling jobs on parallel identical machines to minimize weighted tardiness. There are no known heuristics for this problem. The heuristic rule developed is simple. It can be used in the dispatch mode which makes it very practical. Characterizations of optimal solutions are presented. Computational results show that the myopic heuristic performed well vis-a-vis other rules such as the Earliest Due Date Rule, Weighted Shortest Processing Time Rule and two versions of Montagne's Rule. Reported are computational results and also the performance of the heuristic in comparison to high computational benchmarks. (Author)
01 Jan 1983
TL;DR: In this article, a hierarchical scheduling model is considered, where the decision at the aggregate level to acquire a number of identical machines has to be based on probabilistic information about the jobs that have to be scheduled on these machines at the detailed level.
Abstract: In the hierarchical scheduling model to be considered, the decision at the aggregate level to acquire a number of identical machines has to be based on probabilistic information about the jobs that have to be scheduled on these machines at the detailed level. The objective is to minimize the sum of the acquisition costs and the expected average completion time of the jobs. In contrast to previous models of this type, the second part of this objective function corresponds to a well-solvable scheduling problem that can be solved to optimality by a simple priority rule. A heuristic method to solve the entire problem is described, for which strong asymptotic optimality results can be established.
TL;DR: This paper analyzes approximation algorithms for two types of scheduling problems and proposes an approximation algorithm for general n/2/F/Lmax and derives its worst case bound.
Abstract: In this paper, we analyze approximation algorithms for two types of scheduling problems. The first is the n jobs scheduling problem with due dates on m identical machines to minimize the maximum lateness. For this problem n/m/I/Lmax, we propose two approximation algorithms and derive their worst case bounds. The second is the 2 x n flow shop scheduling problem with due dates to minimize the maximum lateness. For this problem n/2/F/Lmax' we first give a solvable case in the sense that the optimal schedule can be easily found. Then we again propose an approximation algorithm for general n/2/F/Lmax and derive its worst case bound.