Showing papers on "Flow shop scheduling published in 2000"
Proceedings Article•
01 Jan 2000TL;DR: This paper attempts to address the scheduling of jobs to the geographically distributed computing resources with a brief description of the three nature's heuristics namely Genetic Algorithm, Simulated Annealing and Tabu Search.
Abstract: Computational Grid (Grid Computing) is a new paradigm that will drive the computing arena in the new millennium. Unification of globally remote and diverse resources, coupled with the increasing computational needs for Grand Challenge Applications (GCA) and accelerated growth of the Internet and communication technology will further fuel the development of global computational power grids. In this paper, we attempt to address the scheduling of jobs to the geographically distributed computing resources. Conventional wisdom in the field of scheduling is that scheduling problems exhibit such richness and variety that no single scheduling method is sufficient. Heuristics derived from the nature has demonstrated a surprising degree of effectiveness and generality for handling combinatorial optimization problems. This paper begins with an introduction of computational grids followed by a brief description of the three nature's heuristics namely Genetic Algorithm (GA), Simulated Annealing (SA) and Tabu Search (TS). Experimental results using GA are included. We further demonstrate the hybridized usage of the above algorithms that can be applied in a computational grid environment for job scheduling.
378 citations
TL;DR: By incorporating the concept of similarity among individuals into the genetic algorithms using the Gannt chart, a genetic algorithm which is suitable for solving the formulated problems are proposed and are demonstrated by comparing with the simulated annealing method.
270 citations
TL;DR: This paper examines recent developments in the field of evolutionary computation for manufacturing optimization with a wide range of problems, from job shop and flow shop scheduling, to process planning and assembly line balancing.
Abstract: The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most manufacturing optimization problems are combinatorial and NP hard. This paper examines recent developments in the field of evolutionary computation for manufacturing optimization. Significant papers in various areas are highlighted, and comparisons of results are given wherever data are available. A wide range of problems is covered, from job shop and flow shop scheduling, to process planning and assembly line balancing.
264 citations
TL;DR: An intelligent agent based dynamic scheduling system that selects the most appropriate priority rule according to the shop conditions in real time, while simulated environment performs scheduling activities using the rule selected by the agent.
234 citations
TL;DR: The several scheduling policies under machine breakdowns in a classical job shop system are tested and a partial scheduling scheme under both deterministic and stochastic environments for several system configurations are investigated.
229 citations
TL;DR: The proposed local search method is based on a tabu search technique and on the shifting bottleneck procedure used to generate the initial solution and to refine the next-current solutions.
220 citations
TL;DR: This problem can be modelled as a hybrid flow shop scheduling problem with mixed no-wait/no-store constraints and mixed bottleneck/non-bottleneck machines and an approximation algorithm based on the tabu search approach is proposed.
220 citations
TL;DR: This paper surveys cyclic scheduling problems in robotic flowshops, models for such problems, and the complexity of solving these problems, thereby bringing together several streams of research that have by and large ignored one another and describing and establishing links with other scheduling problems and combinatorial topics.
Abstract: Fully automated production cells consisting of flexible machines and a material handling robot have become commonplace in contemporary manufacturing systems. Much research on scheduling problems arising in such cells, in particular in flowshop-like production cells, has been reported recently. Although there are many differences between the models, they all explicitly incorporate the interaction between the materials handling and the classical job processing decisions, since this interaction determines the efficiency of the cell. This paper surveys cyclic scheduling problems in robotic flowshops, models for such problems, and the complexity of solving these problems, thereby bringing together several streams of research that have by and large ignored one another, and describing and establishing links with other scheduling problems and combinatorial topics.
212 citations
TL;DR: A measure of schedule robustness that explicitly considers the risk of poor system performance over all potential realizations of job processing times is presented and results indicate that robust schedules provide effective hedges against processing time uncertainty while maintaining excellent expected makespan performance.
Abstract: This paper focuses on manufacturing environments where job processing times are uncertain. In these settings, scheduling decision makers are exposed to the risk that an optimal schedule with respect to a deterministic or stochastic model will perform poorly when evaluated relative to actual processing times. Since the quality of scheduling decisions is frequently judged as if processing times were known a priori, robust scheduling, i.e., determining a schedule whose performance (compared to the associated optimal schedule) is relatively insensitive to the potential realizations of job processing times, provides a reasonable mechanism for hedging against the prevailing processing time uncertainty. In this paper we focus on a two-machine flow shop environment in which the processing times of jobs are uncertain and the performance measure of interest is system makespan. We present a measure of schedule robustness that explicitly considers the risk of poor system performance over all potential realizations of...
204 citations
TL;DR: In this paper, a simulation study indicates that the relative performance of the traditional workload control methods changes completely with for instance the presence or absence of a dominant flow direction in the shop.
184 citations
12 Dec 2000
TL;DR: The paper presents the emerging field of integrated control and CPU-time scheduling, where more general scheduling models and methods that better suit the needs of control systems are developed.
Abstract: The paper presents the emerging field of integrated control and CPU-time scheduling, where more general scheduling models and methods that better suit the needs of control systems are developed. This creates possibilities for dynamic and flexible integrated control and scheduling frameworks, where the control design methodology takes the availability of computing resources into account during design and allows online trade-offs between control performance and computing resource utilization.
TL;DR: It is shown that the no-wait restrictions require several adaptations of the neighborhood structure used by simulated annealing, which indicates that simulatedAnnealing consistently gives better results for a number of realistic instances than simple heuristics within acceptable computation time.
TL;DR: A taxonomy of environments in which IIT scheduling is relevant is provided, the extant literature on I IT scheduling is reviewed, and areas of opportunity for future research are identified.
Abstract: In the context of production scheduling, inserted idle time (IIT) occurs whenever a resource is deliberately kept idle in the face of waiting jobs. IIT schedules are particularly relevant in multimachine industrial situations where earliness costs and/or dynamically arriving jobs with due dates come into play. We provide a taxonomy of environments in which IIT scheduling is relevant, review the extant literature on IIT scheduling, and identify areas of opportunity for future research.
Book•
01 Jan 2000
TL;DR: A methodology for Solving a Range of Scheduling Problems under Uncertainty and two approaches to Fuzzy Set Approaches to Lot Sizing are described.
Abstract: Fuzzy Knowledge Representation in Scheduling: I.B. Turksen, M.H.F. Zarandi, M. Dudzic: Caster Scheduling System Analysis with Fuzzy Technology.- M. Litoiu, R. Tadei: Dynamic Scheduling on Distributed Real-Time Systems by Self-Learning Fuzzy Algorithms.- Fuzzy Constraints in Scheduling: H. Fagier, C. Thierry: The Use of Possibilistic Decision Theory in Manufacturing, Planning and Control: Recent Results in Fuzzy Master Production Scheduling.- P. Fortemps: Introducing Flexibility in Scheduling: The Preference Approach.- H. Ishii: Scheduling Problems with Fuzzy Constraints.- H. Ishibuchi, T. Murata: Flowshop Scheduling with Fuzzy Duedate and Fuzzy Processing Time.- Fuzzy Uncertainty in Scheduling: G. Adamopoulos, C.P. Pappis, N.I. Karacapilidis: A Methodology for Solving a Range of Scheduling Problems under Uncertainty.- S. Chanas, A. Kasperski, D. Kuchta: Two Approaches to Fuzzy Flow Shop Problem.- M. Hapke, R. Slowinski: Fuzzy Set Approach to Multi-Objective and Multi-Mode Project Scheduling under Uncertainty.- M. Vlach: Single Machine Scheduling under Fuzziness.- L. Geneste, B. Grabot, P. Moutarlier: Scheduling of Heterogeneous Data Using Fuzzy Logic in a Customer-Subcontractor Context.- N. Kubota, T. Fukuda: Virus-Evolutionary Genetic Algorithm for Sequencing Jobs in Fuzzy Environment.- N.I. Karacapilidis, C.P. Pappis, G. Adamopulos: Fuzzy Set Approaches to Lot Sizing.
TL;DR: A method for assigning tasks or resources, based on a model of division of labor in social insects, is introduced and applied to a dynamic flow shop scheduling problem and both systems are able to adapt well to changing conditions.
Abstract: A method for assigning tasks or resources, based on a model of division of labor in social insects, is introduced and applied to a dynamic flow shop scheduling problem. The problem consists of assigning trucks to paint booths in a truck facility to minimize total makespan and the number of paint flushes. Similarities between the ant-based approach and a market-based approach are highlighted. Both systems are able to adapt well to changing conditions.
01 May 2000
TL;DR: In initial simulations TDS has been observed to generate scheduling lengths shorter than that of BIL, for communication-to-computation cost ratios (CCR) of 0.2 to 1.2, and is far more superior than BIL as far as scheduling time is concerned.
Abstract: Optimal scheduling of tasks of a directed acyclic graph (DAG) onto a set of processors is a strong NP-hard problem. In this paper we present a scheduling scheme called TDS to schedule tasks of a DAG onto a heterogeneous system. This models a network of workstations, with processors of varying computing power. The primary objective of this scheme is to minimize schedule length and scheduling time itself. The existing task duplication based scheduling scheme is primarily done for totally homogeneous systems. We compare the performance of this algorithm with an existing scheduling scheme for heterogeneous processors called BIL. In initial simulations TDS has been observed to generate scheduling lengths shorter than that of BIL, for communication-to-computation cost ratios (CCR) of 0.2 to 1. Moreover TDS is far more superior than BIL as far as scheduling time is concerned.
TL;DR: In this paper, the authors apply data mining methodologies to explore the patterns in data generated by a genetic algorithm performing a scheduling operation and to develop a rule set scheduler which approximates the genetic algorithm's scheduler.
TL;DR: This paper considers the nonpreemptive scheduling of a given set of jobs on several identical, parallel machines, under a variety of assumptions about setup and processing times, and provides a mapping of the computational complexity of these problems.
TL;DR: Six new heuristics are presented to solve the scheduling of N jobs in a V-stage hybrid flow shop with identical parallel machines, when jobs are subject to precedence constraints, several time lags, and due-dates.
TL;DR: A new branch and bound method for solving the Multi-Processor Flow-Shop based on the relaxation of the initial problem to m-machine problems corresponding to centers is presented.
Abstract: The aim of this paper is to present a new branch and bound method for solving the Multi-Processor Flow-Shop. This method is based on the relaxation of the initial problem to m-machine problems corresponding to centers. Release dates and tails are associated with operations and machines. The branching scheme consists in fixing the inputs of a critical center and the lower bounds are those of the m-machine problem. Several techniques for adjusting release dates and tails have also been introduced. As shown by our personal study, the overall method is very efficient.
TL;DR: This work shows that the problem to sequence the parts and, concurrently, schedule the robot moves in order to maximize productivity is solvable in time O( n log n ) by reducing it to the classical two-machines no-wait flow shop.
TL;DR: In this article, the authors present a similar concept for planning and scheduling problems, where a forecasting model and an optimization model are used in tandem in a simulation environment that incorporates uncertainty.
TL;DR: In this article, the problem of minimizing makespan in m -machine no-wait flowshops with multiple products requiring lot streaming is studied. But the authors conclude that while GA may deliver makespan comparable in quality to those given by heuristic methods that cleverly exploit problem features particular to lot streaming, GA loses out in computational efficiency.
TL;DR: A new solution approach using models and methods of resource–constrained project scheduling, which (approximately) solves problems of industrial size within a reasonable amount of time is proposed.
Abstract: The paper deals with batch scheduling problems in process industries where final products arise from several successive chemical or physical transformations of raw materials using multi–purpose equipment. In batch production mode, the total requirements of intermediate and final products are partitioned into batches. The production start of a batch at a given level requires the availability of all input products. We consider the problem of scheduling the production of given batches such that the makespan is minimized. Constraints like minimum and maximum time lags between successive production levels, sequence–dependent facility setup times, finite intermediate storages, production breaks, and time–varying manpower contribute to the complexity of this problem. We propose a new solution approach using models and methods of resource–constrained project scheduling, which (approximately) solves problems of industrial size within a reasonable amount of time.
01 May 2000
TL;DR: This paper presents an integrated strategy that combines backfilling with gang scheduling, using extensive simulations based on detailed models of realistic workloads, and the benefits of combining back filling and gang scheduling are clearly demonstrated over a spectrum of performance criteria.
Abstract: Two different approaches have been commonly used to address problems associated with space sharing scheduling strategies: (a) augmenting space sharing with backfilling, which performs out of order job scheduling; and (b) augmenting space sharing with time sharing, using a technique called coscheduling or gang scheduling. With three important experimental results-impact of priority queue order on backfilling, impact of overestimation of job execution times, and comparison of scheduling techniques-this paper presents an integrated strategy that combines backfilling with gang scheduling. Using extensive simulations based on detailed models of realistic workloads, the benefits of combining backfilling and gang scheduling are clearly demonstrated over a spectrum of performance criteria.
01 Aug 2000
TL;DR: This paper presents a Lagrangian relaxation-based approach for production scheduling of flexible flow shops (PSFFS) where sequence-dependent setup effects are significant and the number of part types has the most significant effect on both optimality and computation efficiency.
Abstract: This paper presents a Lagrangian relaxation-based approach for production scheduling of flexible flow shops (PSFFS) where sequence-dependent setup effects are significant. PSPFS is first formulated as a separable integer programming problem with synchronization constraints between production and machine usage. Lagrangian relaxation is then applied, and the scheduling is decomposed into part production and machine scheduling. In these subproblems, there are network flow structures in the equality constraints describing machine status change and production flow balance. Our iterative algorithm applies a minimum cost network flow algorithm to individual subproblems and adopts an efficient surrogate subgradient method to optimize Lagrangian multipliers. A machine availability-searching heuristic finally adjusts the solution to satisfy all synchronization constraints by exploiting the network structure, economic interpretation of Lagrangian multipliers, and the slack time policy. Numerical results of 16 cases, each having 20 test problems, demonstrate that differences between the schedules obtained by our approach and the true optima are on average within 15%, CPU times spent are all less than 17 min on a Pentium-II personal computer. Among the problem dimension factors, the number of part types has the most significant effect on both optimality and computation efficiency. Application of the methodology to daily scheduling of a realistic integrated circuit testing facility of 30 machines takes about 6 min of CPU time to generate a near-optimal solution.
TL;DR: Several extensions to the RCPSP aimed at modeling such problems are introduced, and a problem instance generator based on the project generator ProGen incorporating these extensions is introduced, so it becomes possible to thoroughly test solution procedures for, e.g., audit-staff scheduling, crew scheduling and timetabling problems.
TL;DR: This paper presents the description of a scheduling algorithm for the solution of the no-wait flow-shop problem and finds the heuristic to minimise the sum of the total flow-times a sensible target in applications such as agile manufacturing.
TL;DR: In this article, a genetic algorithm was developed to address the scheduling problem in manufacturing systems constrained by both machines and workers, and a set of experiments for determining the best staffing level and machine and worker assignment to jobs was performed.
TL;DR: In this paper, the tabu search technique is considered for solving job shop scheduling problems and the performance measure considered is makespan time and adjacent pairwise interchange method is used to generate neighbourhoods.
Abstract: In this paper the tabu search technique is considered for solving job shop scheduling problems. The performance measure considered is makespan time. The adjacent pairwise interchange method is used to generate neighbourhoods. The results of tabu search are compared with simulated annealing and genetic algorithms. It is concluded that the performance of tabu search is comparable to that of genetic algorithm and simulated annealing. The future research directions are also discussed.