Showing papers on "Flow shop scheduling published in 1990"

Job shop scheduling with alternative machines

Abstract: SUMMARY In this paper we investigate the problem of minimizing the mean flow time in a general job shop type machining system with alternative machine tool routeings. An analytical formulation of the problem as a mixed integer programming is developed. An efficient algorithm based on this formulation is developed to solve the problem by decomposing it into subproblems that are easier to solve. The algorithm solves large problems in relatively short time. A second algorithm based on the SPT rule is developed and its performance is compared with the first algorithm. A greedy procedure is also developed for the case when a penalty cost is associated with adding alternative machines. Numerical examples are given to demonstrate the use of the above algorithms.

Genetic algorithms and job shop scheduling

Abstract: We describe applications of Genetic Algorithms (GAs) to the Job Shop Scheduling (JSS) problem. More specifically, the task of generating inputs to the GA process for schedule optimization is addressed. We believe GAs can be employed as an additional tool in the Computer Integrated Manufacturing (CIM) cycle. Our technique employs an extension to the Group Technology (GT) method for generating manufacturing process plans. It positions the GA scheduling process to receive outputs from both the automated process planning function and the order entry function. The GA scheduling process then passes its results to the factory floor in terms of optimal schedules. An introduction to the GA process is discussed first. Then, an elementary n-task, one processor (machine) problem is provided to demonstrate the GA methodology in the JSS problem arena. The technique is then demonstrated on an n-task, two processor problem, and finally, the technique is generalized to the n-tasks on m-processors (serial) case.

Heuristic algorithms for continuous flow-shop problem

Abstract: In this article we present two heuristic algorithms for scheduling in the constrained or continuous flow shop to minimize total flow time of jobs. Two heuristic preference relations are used as the basis for job insertion to build up a schedule by the heuristics. When evaluated over a large number of problems of various sizes, the heuristics are found to be very effective in yielding near-optimal solutions.

Multiobjective flow-shop scheduling

Abstract: Previous research on the scheduling of multimachine systems has generally focused on the optimization of individual performance measures. This article considers the sequencing of jobs through a multimachine flow shop, where the quality of the resulting schedule is evaluated according to the associated levels of two scheduling criteria, schedule makespan (Cmax) and maximum job tardiness (Tmax). We present constructive procedures that quantify the trade-off between Cmax and Tmax. The significance of this trade-off is that the optimal solution for any preference function involving only Cmax and Tmax must be contained among the set of efficient schedules that comprise the trade-off curve. For the special case of two-machine flow shops, we present an algorithm that identifies the exact set of efficient schedules. Heruistic procedures for approximating the efficient set are also provided for problems involving many jobs or larger flow shops. Computational results are reported for the procedures which indicate that both the number of efficient schedules and the error incurred by heuristically approximating the efficient set are quite small.

Automated re-work shop order scheduling system

Abstract: A computer implemented system analyzes shop dispatch rules using current status and a simulation system for the shop floor to establish the dispatch rules to be used to mini­mize tardiness. When re-work orders are introduced into the system, the shop floor orders have to compete for the same resources, and so the sequence for dispatch may have to be modified to meet the new demands on the shop floor resources. The system provides the capability such that minimum impact is felt on existing orders while maintain­ing management objectives. The system provides feedback to the user and the up-stream planning system if major changes need to be made on the shop floor schedules. The system develops revised dispatch rules to be followed and the associated sequence of operations to be followed after the introduction of re-work shop orders. The approach taken is repeated interactively and forms what may be characterized as a "bottoms up" approach to analyze the floor schedule taking into consideration the re-work orders and feeds the information to the original planning process. The system automatically creates a list of alternative processes that any production order can follow and establishes optimum process flows in the event of introduction of re-work shop orders. The system automati­cally passes the information to the planning system which then re-calculates the revised order release sequence for the remaining orders in the release process.

Scheduling Multiple Variable-Speed Machines

Abstract: We examine scheduling problems where we control not only the assignment of jobs to machines, but also the time used by the job on the machine. For instance, many tooling machines allow control of the speed at which a job is run. Increasing the speed incurs costs due to machine wear, but also increases throughput. We discuss some fundamental scheduling problems in this environment and give algorithms for some interesting cases. Some cases are inherently difficult so for these we give heuristics. Our approach illustrates the exploitation of underlying network structure in combinatorial optimization problems. We create heuristics that optimally schedule a large portion of the jobs and then attempt to fit in the remainder. This also gives a method for quickly finding valid inequalities violated by the linear relaxation solution. For the problem of minimizing the sum of makespan and production costs, a rounding heuristic is within a constant factor of optimal. Our heuristics are compared to other classical heuristics.

Path-based scheduling for synthesis

Abstract: A path-based scheduling algorithm for synchronous digital systems is presented. It yields solutions with the minimum number of control steps, taking into account arbitrary constraints that limit the amount of operations in each control step. The result is a finite-state machine that implements the control. Although the complexity of the algorithm is proportional to the number of paths in the control-flow graph, it is shown to be practical for large examples with thousands of nodes. >

Scheduling jobs with simple precedence constraints on parallel machines

Abstract: A methodology is presented for scheduling jobs on identical, parallel machines. Each job comprises a small number of operations that must be processed in a specified order. The objective is to minimize the total weighted quadratic tardiness of the schedule, subject to capacity and precedence constraints. The procedure presented is an efficient near-optimal method based on the Lagrangian relaxation technique and the list-scheduling concept. In addition, the resulting job-interaction information can be used to provide quick answers to what-if questions and to reconfigure the schedule to reincorporate new jobs and other dynamic changes. This scheduling methodology has been implemented in a knowledge-based scheduling system. Typical sizes of problems involve 35 to 40 machines and 100 to 200 jobs, each with 3 to 5 operations. >

Optimal and Heuristic Models for Lot Splitting in a Flow Shop

Abstract: This paper investigates optimal lot-splitting policies in a multiprocess flow shop environment with the objective of minimizing either mean flow time or makespan. Using a quadratic programming approach to the mean flow time problem, we determine the optimal way of splitting a job into smaller sublots under various setup times to run time ratios, number of machines in the flow shop, and number of allowed sublots. Our results come from a deterministic flow shop environment, but also provide insights into the repetitive lots scheme using equal lot splits for job shop scheduling in a stochastic environment. We indicate those conditions in which managers should implement the repetitive lots scheme and where other lot-splitting schemes should work better.

An investigation of dynamic group scheduling heuristics in a job shop manufacturing cell

Abstract: SUMMARY The objective of this study is to develop dynamic scheduling heuristics for cellular manufacturing environments (group scheduling or family heuristics) and compare them with existing family heuristics under various shop floor conditions. The proposed family heuristics stress good due date performance while reducing overall set-up time. Computer simulation is used to test three queue selection rules in conjunction with three dispatching rules under eight experimental conditions in a job shop cell. The results indicate that several of the proposed heuristics substantially improve the performance of the cell over the best previously suggested family heuristic under all experimental conditions.

A comparison of dispatching rules for job shops with multiple identical jobs and alternative routeings

Abstract: SUMMARY In general job shop scheduling, n jobs have to be scheduled on m machines. We consider the job shop scheduling problems in which there are orders with sizes greater than one (therefore there are multiple identical jobs), and in which each operation can be processed on several machines (therefore there are alternative routeings for the operations). These characteristics of the problems impose special precedence relationships among operations. We compare various dispatching rules for list scheduling algorithms and test several methods for defining successors of an operation using the precedence relationships. Mean tardiness, mean flow time, and number of tardy jobs are used as performance measures in the comparison.

Scheduling Parts in a Combined Production-transportation Work Cell

Abstract: This paper is concerned with a combined production-transportation scheduling problem. The problem comprises a simple, two-machine, automated manufacturing cell, which either stands alone or is a subunit of a complete flexible manufacturing system. The cell consists of two machines in series with a dedicated part-handling device such as a crane or robotic arm for transferring parts from the first machine to the second. The loading of a new piece on the first machine and the ejection of a finished piece from the second machine are performed by dedicated automated mechanisms. The introduction of parts into the system is done n at a time, whereby the parts are reshuffled into a sequence that minimizes completion time. All processing and transfer times are considered deterministic—a reasonable assumption for a cell comprising a robotic transfer device and two CNC machining units. What complicates the problem is the assumption of a non-negligible time for the transfer device to return (empty) from the second machine to the first. The operation is a generalization of a two-machine flowshop problem, and is formulated as a specially structured, asymmetric travelling salesman problem. An approximate polynomial time 0(n log n) algorithm is proffered. The procedure incorporates a lower bound using the Gilmore–Gomory algorithm for the no-wait, two-machine flowshop problem.

A Simulation and Learning Technique for Generating Knowledge about Manufacturing Systems Behavior

Abstract: One of the most important difficulties when developing knowledge based systems in manufacturing scheduling or control, is finding the required knowledge. We address here the problem of acquiring knowledge about the behavior of manufacturing systems. Learning algorithms are proposed to generate, from simulation experiments, a set of production rules. This set may be considered as a simulation meta-model, and may be used either directly by the shop manager, or inserted into a knowledge base. This approach is illustrated by the use of the learning program GENREG. It generates rules related to the behavior of a simplified flow shop when different dispatching rules are applied.

Synthesis using path-based scheduling: algorithms and exercises

Abstract: Path-based scheduling algorithms consider all possible sequences of operations (called paths) in a control-flow graph. Unlike most scheduling techniques used in high-level synthesis, they stress optimization across conditional branches. This paper presents several path-based algorithms. An exact algorithm finds the minimum number of control steps required for each possible path being executed. Heuristic solutions were also implemented. Extensive application of these algorithms to the benchmarks of the High-Level Synthesis Workshop showed the practical feasibility of such methods.

Cyclic sequencing problems in the two‐machine permutation flow shop: Complexity, worst‐case, and average‐case analysis

Abstract: In this article, we formalize the cyclic sequencing problem in the two-machine flow shop. When jobs are processed in a repetitive cycle, the size of a scheduling problem is significantly reduced, and the resulting schedule is easy to implement because of its simplicity. Two types of cyclic sequencing problems are considered: the no-wait problem and the minimum-wait problem. The no-wait problem maximizes the throughput rate subject to the condition that there is no buffer space between the two machines. The minimum-wait problem minimizes the average WIP level subject to the conditions that the maximum throughput rate is maintained and that the FIFO dispatching rule is used in the intermediate buffer space. The no-wait problem is a well-known special case of the traveling salesman problem (TSP) and is polynomially solvable. The minimum-wait problem is shown to be NP-hard; therefore, we develop a heuristic procedure along with the analysis of its worst-case and average-case performance. Here, the average-case analysis is based on the expected length of the Hamiltonian tour for this special case of the TSP. The average-case analysis indicates that when the number of jobs in a cycle is small, the derived cyclic schedule yields a low WIP level.

Scheduling parallel machines with major and minor setup times

Abstract: This article discusses the problem of scheduling a large set of parts on an FMS so as to minimize the total completion time. Here, the FMS consists of a set of parallel identical machines. Setup time is incurred whenever a machine switches from one type of part to another. The setup time may be large or small depending on whether or not the two part types belong to the same family. This article describes a fast heuristic for this scheduling problem and derives a lower bound on the optimal solution. In computational tests using random data and data from an IBM card test line, the heuristic archieves nearly optimal schedules.

Dynamic-level scheduling for heterogeneous processor networks

Abstract: Dynamic-level scheduling is an effective compile-time scheduling technique which accounts for interprocessor communication overhead when mapping precedence-constrained, communicating tasks onto arbitrarily interconnected processor networks. Scheduling and routing are performed simultaneously to account for limited interconnections between processors, and communications are scheduled along with computations to eliminate shared-resource contention. The paper extends the dynamic-level scheduling methodology to encompass heterogeneous processing environments, and presents two techniques designed to enhance scheduling performance: forward/backward scheduling, and precedence constraint appendage. >

Design of a scheduling system for flexible manufacturing cells

Abstract: SUMMARY The objective of this paper is to describe an effective scheduling system for flexible manufacturing cells (FMC). Based on FMC characteristics, cell scheduling can be categorized for a dynamic, modified flow shop working in a real-time environment. A heuristic static cell scheduling methodology for minimizing mean flowtime is first proposed. This is then modified to allow dynamic cell scheduling to reflect the real-world situation of continuous job introduction to the cell. Computational results show that the proposed algorithms yield optimal or near optimal job sequences in a very short period of time, thus satisfying a real-time need of rapid computation.

Part assignment to electronic insertion machines: two machine case

Abstract: SUMMARY Modern electronic circuit board production typically uses computerized insertion machines to insert electronic components into circuit boards in a flow shop type of production line. This paper studies the problem of assigning components to insertion machines with the aim of maximizing output. The paper initially examines the two machine assignment case, identifying requirements sufficient to ensure an optimal solution for two technological scenarios. Moreover, it is noted that the sequencing issue of different board types in a production cycle is immaterial, given large machine capacity. Solution procedures for this components assignment problem are described and tested on data obtained from a real life industrial setting. The resulting solutions are within 0-5% from optimality.

Manufacturing systems with forbidden early shipment: implications for choice of scheduling rules

Abstract: SUMMARY Recent progress in manufacturing systems research has identified the feature of forbidding early shipment (FES) of orders as a prevalent characteristic of real systems. This report examines the implications of this feature on the choice of scheduling rules within a job shop. Simulation results of a simplified job shop reconfirm the superiority of the modified due date approach when the criterion is mean job tardiness. However, when the criterion is system inventory, the slack time per remaining operation ratio approach performs slightly better than modified due date. The shortest operation processing time yields very poor results in job shops that include the FES assumption.

Algorithms for end-to-end scheduling to meet deadlines

Abstract: In a multiprocessor or distributed system, jobs may need to be executed on more than one processor. When all the jobs execute on different processors in turn in the same order, the problem of end-to-end scheduling on the processors is known as the flow-shop problem. The paper describes two optimal polynomial-time algorithms for scheduling jobs in flow shops to meet deadlines, for two special cases where the scheduling problem is tractable. For the general case, where an optimal polynomial-time algorithm is unlikely to be found, a heuristic algorithm is presented. >

A model of the F18 mission computer software for pre-run-time scheduling

Abstract: The development of pre-run-time schedulers for certain hard real-time applications is investigated This scheduling scheme requires the modeling of the program as a set of processes with corresponding timing specifications, such as release times, computation times, and deadlines The models must specify precedence and exclusion constraints between pairs of processes It is processed by an offline pre-run-time scheduling algorithm that computes a schedule for use at run time, ensuring that all static timing constraints of the system are observed The technique works best in cases in which most processes are periodic, which is true for the F-18 A modeling process for the M18 Mission Computer software that is designed to lead the application of pre-run-time scheduling to the software and is applicable to other such hard systems is described >

Scheduling job operations in an automatic assembly line

Abstract: The problem of scheduling job operations in an automatic assembly line used for manufacturing a small to medium volume of mixed workparts is addressed. An assembly line model is discussed. This model differs from the classical flow shop model in the following three aspects: there are no buffers at machine stations; constraints associated with the material transport system are included; and, for each batch of production, workparts are distinguished in groups, rather than individually. An optimal algorithm that requires very little computation is derived first by minimizing the total finish time for two machine assembly lines. This result is then generalized to the problem of scheduling an assembly line with m>2 machines processing single-operation jobs. In order to reduce the computational complexity of the latter problem, heuristic algorithms are proposed and shown to work quite well for all the cases considered. A heuristic solution to the problem of scheduling an assembly line with m>2 machines processing multioperation jobs is discussed. >