Showing papers on "Job shop published in 1995"
01 Jan 1995
TL;DR: In this paper, a heuristic technique based on genetic algorithms was used to solve the problem of job shop scheduling, which is strongly NP-hard problem of combinatorial optimization and one of the most well-known machine scheduling problems.
Abstract: Scope and Purpoee--Job shop scheduling is a strongly NP-hard problem of combinatorial optimization and one of the most well-known machine scheduling problems. Scope of this paper is to present some improvements obtained in dealing with this problem using a heuristic technique based on Genetic Algorithms.
394 citations
TL;DR: Improvements obtained in dealing with job shop scheduling using a heuristic technique based on Genetic Algorithms are presented.
381 citations
TL;DR: In this article, a new representation called permutation with repetition (P-R) is presented, which is similar to the permutation scheme of the traveling salesman problem (TSP) in the sense that it cannot produce illegal operation sequences.
Abstract: In order to sequence the tasks of a job shop problem (JSP) on a number of machines related to the technological machine order of jobs, a new representation technique — mathematically known as “permutation with repetition” is presented. The main advantage of this single chromosome representation is — in analogy to the permutation scheme of the traveling salesman problem (TSP) — that it cannot produce illegal operation sequences. As a consequence of the representation scheme a new crossover operator preserving the initial scheme structure of permutations with repetition will be sketched. Its behavior is similar to the well known Order-Crossover for simple permutation schemes. Actually theGOX operator for permutations with repetition arises from aGeneralisation ofOX. Computational experiments show, that GOX passes the information from a couple of parent solutions efficiently to offspring solutions. Together, the new representation and GOX support the cooperative aspect of genetic search for scheduling problems strongly.
294 citations
TL;DR: In this paper, the authors present a model of the environmental impact of machining processes, which integrates aspects of the process mechanics, wear characteristics and lubricant flows, including energy utilization, process rate, primary mass flow, and secondary flow of process catalysts.
227 citations
TL;DR: In this article, the authors studied the one machine scheduling problem with release and delivery times and the minimum makespan objective, in the presence of constraints that for certain pairs of jobs require a delay between the completion of the first job and the start of the second (delayed precedence constraints).
Abstract: We study the one machine scheduling problem with release and delivery times and the minimum makespan objective, in the presence of constraints that for certain pairs of jobs require a delay between the completion of the first job and the start of the second (delayed precedence constraints). This problem arises naturally in the context of the Shifting Bottleneck Procedure for the general job shop scheduling problem, as a relaxation of the latter, tighter than the standard one-machine relaxation. The paper first highlights the difference between the two relaxations through some relevant complexity results. Then it introduces a modified Longest Tail Heuristic whose analysis identifies those situations that permit efficient branching. As a result, an optimization algorithm is developed whose performance is comparable to that of the best algorithms for the standard one-machine problem. Embedding this algorithm into a modified version of the Shifting Bottleneck Procedure that uses the tighter one-machine relaxa...
145 citations
TL;DR: In this article, an effective tabu search approach to the job shop scheduling problem is presented, which starts from the best solution rendered by a set of 14 heuristic dispatching solutions and then makes use of the classical disjunctive network representation of the problem and iteratively moves to another feasible solution by reversing the order of two adjacent critical path operations performed by the same machine.
Abstract: In the job shop scheduling problem we desire to minimize the makespan where a set of machines perform technologically ordered operations unique to each member of a set of jobs. Each operation has a fixed time duration, no machine can perform more than one operation at a time, and preemption is not allowed. In this paper, an effective tabu search approach to the job shop scheduling problem is presented. The procedure starts from the best solution rendered by a set of 14 heuristic dispatching solutions. It then makes use of the classical disjunctive network representation of the problem and iteratively moves to another feasible solution by reversing the order of two adjacent critical path operations performed by the same machine. The concepts of historical generators and search restart are used in conjunction with a contiguous spectrum of short term memory values to enhance the overall exploration strategy. Computational results are presented and areas for future investigation are suggested.
133 citations
TL;DR: From the computational results, it can conclude that the large-step optimization methods outperform the simulated annealing method and find more frequently an optimal schedule than the other studied methods.
133 citations
TL;DR: In this paper, the problem of scheduling n jobs on m machines in order to minimize the maximum completion time or mean flow time of jobs was studied, and the main result of this paper is an NP-hardness proof for scheduling 3 jobs on 3 machines, whether preemptions of operations are allowed or forbidden.
102 citations
TL;DR: A solution approach for a joint process plan selection and job shop scheduling problem, taking both operations cost and makespan into account within a multi-objective framework is proposed.
Abstract: The job shop scheduling literature deals with problems characterized by a fixed linear process plan for each job: it is assumed that the process planning problem has been solved before scheduling, and no flexibility in the process plan is considered. Our aim here is to propose a solution approach for a joint process plan selection and job shop scheduling problem, taking both operations cost and makespan into account within a multi-objective framework. Due to the complexity of the problem, a two-phase hierarchical method is proposed. In the first phase, a relaxed version of the problem is solved, yielding an approximation of the set of efficient process plans with respect to cost and load balancing objectives. Each process plan is then considered and the corresponding scheduling problem is solved by tabu search; the process plan selection is improved by a two-level hierarchical tabu search algorithm.
86 citations
TL;DR: This paper deals with the heuristic solution of the classical job shop problem by applying insertion techniques combined with beam search to generate paths in a particular neighbourhood graph instead of investigating the neighbourhood completely.
79 citations
TL;DR: A critical aspect of job shop scheduling research is reviewed, namely the decision regarding release timing of orders to the manufacturing shopfloor, and tables describing the release rules and summarizing the characteristics of the simulation research are reviewed.
Abstract: Reviews a critical aspect of job shop scheduling research, namely the decision regarding release timing of orders to the manufacturing shopfloor. Covers articles specifically addressing the order release problem; the information should prove helpful for researchers employing order release policies in their research. The release decision literature is classified into three areas: descriptive studies including case and survey research, analytical or optimization‐based research, and simulations of theoretical and empirically derived job shops. Presents tables describing the release rules and summarizing the characteristics of the simulation research. Identifies a number of topics within the order release research area in need of further investigation, including the comparison of larger sets of release rules, the use of more realistic simulation models such as the dual resource constrained job shop model, the need for further empirical identification of release policies, and the use of release policies that c...
TL;DR: This paper deals with the design and operational control of Automated Guided Vehicle (AGV) systems, and reports on the results of a case study, in which track layout and transportation control are the main issues.
TL;DR: In this paper, a forecasting approach to flowtime prediction in a job shop is presented, which considers both job characteristic and shop loading information, and a lateness feedback approach is also developed to dynamically estimate the variance of forecast error.
Abstract: This paper presents a forecasting approach to flowtime prediction in a job shop. The flowtime prediction relationship developed considers both job characteristic and shop loading information. Forecast errors are shown to be approximately normally distributed. A lateness feedback approach is also developed to dynamically estimate the variance of forecast error. The estimated distribution of forecast error is used to set delivery safety allowances which are based on a desired level of delivery performance. Results show that the lead times required to maintain a desired level of delivery performance are lowest when due-date dependent dispatch is used.
TL;DR: Three “intelligent” backtracking schemes are shown to further reduce the average complexity of the backtrack search procedure, enable the system to efficiently solve problems that could not be solved otherwise due to excessive computation cost, and be more effective at solving job shop scheduling problems than other look-back schemes advocated in the literature.
01 Jul 1995
TL;DR: Three different algorithms for simulated annealing for job shop scheduling are developed and implemented on the distributed task sharing system (DTSS) running on a network of 18 Sun workstations.
Abstract: Job shop scheduling belongs to the class of NP-hard problems. There are a number of algorithms in literature for finding near optimal solution for the job shop scheduling problem. Many of these algorithms exploit the problem specific information and hence are less general. However, the simulated annealing algorithm for job shop scheduling is general and produces better results in comparison with other similar algorithms. But one of the major drawbacks of the algorithm is that the execution time is high. This makes the algorithm inapplicable to large scale problems. One possible approach to reduce the execution time of the algorithm is to develop distributed algorithms for simulated annealing. In the paper, the authors discuss approaches to developing distributed algorithms for simulated annealing for solving the job shop scheduling problem. Three different algorithms have been developed. These are the temperature modifier, the locking edges and the modified locking edges algorithms. These algorithms have been implemented on the distributed task sharing system (DTSS) running on a network of 18 Sun workstations. The observed performance showed that each of these algorithms performs well depending on the problem size. >
TL;DR: In this article, the authors evaluated ten different priority dispatching rules with respect to six different performance criteria under light, medium and heavy shop loads and found that the rules that perform well in average and r.m. tardiness perform poorly under percentage of jobs-late criterion.
Abstract: Priority dispatching rules and shop load affect job-shop performance. This paper evaluates ten different priority dispatching rules with respect to six different performance criteria under light, medium and heavy shop loads. Simulation was used as a tool to determine the rankings of the dispatching rules for a given shop load and performance criteria. A comparative study was conducted to investigate the performance of these rules. Two rules, ‘shortest processing time” and ‘least work remaining’, performed well under criteria related to the processing time. It was found that the rules that perform well in average and r.m.s. tardiness perform poorly under percentage-of-jobs-late criterion. The experimental results are conveyed with critical comments on the performance of the dispatching rules under different loading conditions of the shop.
TL;DR: In this article, the authors investigate issues related to acquiring a flexible work-force in those dual resource constrained (DRC) jobshops that have high learning costs and the presence of worker attrition.
Abstract: Worker flexibility is an attractive option for enhancing manufacturing performance, since it provides several strategic advantages, and also allows the firm to buffer against uncertainty. In this paper, we investigate issues related to acquiring a flexible work-force in those dual resource constrained (DRC) job-shops that have high learning costs and the presence of worker attrition. Our results show that significant improvement in traditional shop related measures can be attained at even very high attrition rates by incrementally training each worker in one additional department. However, this improvement comes at the expense of productivity losses which shop managers may not be willing to accept. The nature of the tradeoffs that exist in acquiring this incremental worker flexibility are addressed. Two strategies for improving shop performance, based on incrementally training workers or reducing attrition rates, are also recommended for the DRC shop modelled in our study. Conditions under which either of...
TL;DR: This paper suggests a backward approach in which the operations are scheduled backward, and discusses some details that must be considered when applying the backward approach to problems with due dates and suggest several methods of defining parameters needed in the backward Approach.
TL;DR: A hybrid approach between two new techniques, genetic algorithms and artificial neural network is described for generating job shop schedules in a discrete manufacturing environment based on nonlinear multiobjective function and results indicate that the proposed approach is consistently better than those of heuristic algorithms used extensively in industry.
29 Nov 1995
TL;DR: The application of adaptive optimization methods to production scheduling has recently become a research topic of broad interest and a temporal decomposition of the nondeterministic problem leads to a scheduling control that combines simulation and adaptive search.
Abstract: The application of adaptive optimization methods to production scheduling has recently become a research topic of broad interest. Genetic Algorithm approaches to scheduling concentrate on static problems, whereas real-world scheduling tends to be dynamic. This paper briefly outlines the application of a genetic algorithm to the dynamic job shop problem. In a second step the job shop is regarded as a non-deterministic optimization problem arising from the occurrence of job releases. A temporal decomposition of the nondeterministic problem leads to a scheduling control that combines simulation and adaptive search.
TL;DR: In this article, the authors examined the role of both the planning and shop floor control systems in the operation and performance of a dual resource constrained (DRC) job shop and showed that the ORR rules' performance is strongly dependent on the planning system.
Abstract: This paper examines the role that both the planning and shop floor control systems play in the operation and performance of a dual resource constrained (DRC) job shop. Using causal analysis, the results show an effective planning system, as it accounts for the largest gain in shop performance. Generating and releasing smoothed schedules (work loads) allows the use of simplified shop floor control procedures such as Order Review/Release (ORR), job dispatching and labour assignment rules without adversely affecting performance. This study uses the results to resolve the current paradox surrounding ORR systems and shows that the ORR rules' performance is strongly dependent on the planning system, and that ORR rules can be considered moderating variables. Further, the study develops a variance control framework that indicates the necessary managerial actions to improve shop performance. This paper demonstrates that the planning system, not the shop floor control system, is the major determinant of shop perfor...
TL;DR: In this article, three load-smoothing approaches with two levels of control for each approach are proposed and tested with two order review/release decisions in a bottleneck job shop.
Abstract: Most of the past research on job shop scheduling has assumed the shop environment where the load-smoothing function in the production planning and control system is ignored and consequently no visibility is provided to the shop. In practice, some kind of load-smoothing is used to smooth the work load level of the shop across the periods, by pulling jobs forward or pushing jobs back. In this study, three load-smoothing approaches with two levels of control for each approach are proposed and tested with two order review/release decisions in a bottleneck job shop. No smoothing becomes a benchmark. Also, the effectiveness of a feedback loop between load-smoothing and the shop floor is investigated. Experiments were conducted in a six-machine job shop simulation model. Results showed that the employment of load-smoothing is important, and pulling jobs forward in a valley period is better than pushing back jobs in a peak period. Controlling the release of jobs to the shop floor in the order review/release phase...
06 Nov 1995
TL;DR: Using the branch-and-bound algorithm, an optimal schedule of the FMS can be obtained and timed marked graphs are used to analyze the long-term performance of the job-shop systems.
Abstract: In this paper, Petri net models for flexible manufacturing systems (FMS) are constructed. A firing sequence of the Petri net from an initial marking to a final one can be seen as a schedule of the modeled FMS. By using the branch-and-bound algorithm, an optimal schedule of the FMS can be obtained. Timed marked graphs, a special class of timed Petri nets, are then used to analyze the long-term performance of the job-shop systems. For a job shop system, a procedure is proposed to derive the marked graph from the initial Petri net model after the schedule is determined. The branch and bound algorithm and proposed procedure are illustrated through a job-shop system.
TL;DR: A Tabu search technique is employed, as part of the active chain manipulation procedure developed in this paper, to prevent the trap of local optimality.
TL;DR: In this article, the authors evaluated the effects of using a regression-based approach for setting due dates and found that marked improvement in the performance of dispatching rules can occur when the proposed due date setting procedure is used.
Abstract: Many simulation studies have evaluated sequencing rules and due date assignment methods for scheduling job shops. More recently researchers have studied multistage, or assembly, shops. Typically, due dates have been set by using a fixed multiple of the critical path length. This paper evaluates the effects on shop performance due to using a regression-based approach for setting due dates. The findings show that marked improvement in the performance of dispatching rules can occur when the proposed due date setting procedure is used.
TL;DR: A lower bound for the MPM job-shop problem is developed based on a two-job relaxation which can be solved efficiently by using geometric methods.
TL;DR: This paper focuses on the development of an economic approach to selecting an optimal job shop operating policy and shows that due-date dependent dispatch rules outperform due- date independent rules.
TL;DR: The design of a decision support system for capacity planning in clinical laboratories is discussed and modules for supporting decisions at the overall laboratory level and at the job shop level are described.
Abstract: The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.
Posted Content•
TL;DR: The analysis of stationarity requirements within existingproduction control concepts provides guidelines for developing production control concepts for job shops working under dynamic circumstances.
Abstract: In the case of production environments with job shop characteristics, much research has been done on partial control such as priority dispatching. The development of comprehensive control concepts lags behind. However, the principles of workload control (WLC) have been elaborated to more comprehensive production control concepts. WLC concepts buffer the shop floor against external dynamics by creating a pool of unreleased jobs. The use of workload norms should turn the queueing of orders on the shop floor into a stationary process which can be characterised by an equilibrium. This paper compares and discusses the concepts of WLC. Assumptions of stationarity implied in the workload norms are exposed. A subdivision of workload definitions is chosen as a starting-point to trace assumptions of stationarity. The assumptions highlighted relate to the shop floor situation and make demands upon the job release function. An obvious conflict between timing and balancing within the job release function leads to an examination of stationarity requirements on the job pool contents. The analysis of stationarity requirements within existing production control concepts provides guidelines for developing production control concepts for job shops working under dynamic circumstances.
TL;DR: In this paper, the authors present a real-life study of a job shop manufacturing ball screws and suggest an efficient scheduling and due-date setting policy for the shop, which is based on a search algorithm, simulated annealing algorithm, and a combination of simulated AN algorithm and regression analysis.
Abstract: In this article we present a real-life study of a job shop manufacturing ball screws. The aim of the study is to suggest an efficient scheduling and due-date setting policy for the shop. Three different methodologies for setting parameter coefficients for due-date setting in a job shop are proposed. These methodologies are based on a search algorithm, simulated annealing algorithm, and a combination of simulated annealing algorithm and regression analysis. It is found that the combination of a simulated annealing algorithm with regression analysis provides better due-date estimates in minimizing the root mean square of lateness.