Showing papers on "Job shop published in 2014"
TL;DR: In this paper, a multi-objective scheduling method is developed with reducing energy consumption as one of the objectives, which can also be applied across existing legacy systems and does not require large investment.
241 citations
TL;DR: The results show sequence based model and greedy heuristics equipped with redundancy exclusion are effective for the problem of distributed job shop scheduling and the small sized problems are optimally solved.
Abstract: This paper deals with the problem of distributed job shop scheduling in which the classical single-facility job shop is extended to the multi-facility one. The mathematical formulation of the problem is comprehensively discussed. Two different mixed integer linear programming models in form of sequence and position based variables are proposed. Using commercial software of CPLEX, the small sized problems are optimally solved. To solve large sized problems, besides adapting three well-known heuristics, three greedy heuristics are developed. The basic idea behind the developed heuristics is to iteratively insert operations (one at each iteration) into a sequence to build up a complete permutation of operations. The permutation scheme, although having several advantages, suffers from redundancy which is having many different permutations representing the same schedule. The issue is analyzed to recognize the redundant permutation. That improves efficiency of heuristics. Comprehensive experiments are conducted to evaluate the performance of the two models and the six heuristics. The results show sequence based model and greedy heuristics equipped with redundancy exclusion are effective for the problem.
73 citations
TL;DR: A scheduling strategy to determine starting times of surgeries in multiple operating rooms (OR) is presented and is shown to be better than a simulation based scheduling which already outperforms simple scheduling rules in regional hospitals.
58 citations
TL;DR: A local search heuristic, based on an extension of the 1956 graphical method of Akers, is applied to improve the solution of the job-shop scheduling problem and its application within a biased random-key genetic algorithm is presented.
49 citations
TL;DR: A MILP model for an extended version of the Flexible Job Shop Scheduling problem is proposed, which allows the precedences between operations of a job to be given by an arbitrary directed acyclic graph rather than a linear order.
Abstract: A MILP model for an extended version of the Flexible Job Shop Scheduling problem is proposed. The extension allows the precedences between operations of a job to be given by an arbitrary directed acyclic graph rather than a linear order. The goal is the minimization of the makespan. Theoretical and practical advantages of the proposed model are discussed. Numerical experiments show the performance of a commercial exact solver when applied to the proposed model. The new model is also compared with a simple extension of the model described by Ozguven et al. (Appl Math Modell 34:1539–1548, 2010), using instances from the literature and instances inspired by real data from the printing industry.
48 citations
TL;DR: Non-cooperative game theory with complete information is applied to build new scheduling model for flexible job shop scheduling problem subject to machine breakdown and classical problems are employed with random breakdown to prove the feasibility and effectiveness.
Abstract: Flexible job shop scheduling problem subject to machine breakdown is one of the challenging problems in manufacturing field. In this problem, robustness and stability are the two important measures to evaluate the quality of rescheduling. Considering these two objectives cannot be optimised simultaneously and the equilibrium of two objectives has game procedure, non-cooperative game theory with complete information is applied to build new scheduling model. In this game model, the two objectives can be seen as the two sides which take part in the game. Firstly, pre-scheduling without considering machine failure is generated, and then the operations affected by machine failure are obtained according to time at which machine breakdown happens. The decision made by each side should obtain better robust and stable performance. To achieve the optimal objects, Nash Equilibrium (NE) solution for each side is achieved. Considering NE solution may not exist or there are more than one NE solutions, concepts of ideal...
43 citations
TL;DR: In this article, a modified disjunctive graph is used to represent the characteristics and constraints of job shop scheduling problems with transportation constraints and bounded processing times, and a modified shifting bottleneck procedure is coupled with a heuristic for assigning and sequencing transportation tasks iteratively.
Abstract: In this paper, we consider job shop scheduling problems with transportation constraints and bounded processing times We use a modified disjunctive graph to represent the whole characteristics and constraints of such considered problems Compared with classical disjunctive graph, it contains not only processing nodes, but also transportation and storage nodes There are also positive and negative arcs for bounded processing time constraints, transportation times and minimum and maximum allowed storage times before and after each processing task The objective is to minimise makespan A feasible solution for makespan is found, if its associated graph contains no positive cycle A modified shifting bottleneck procedure is used to solve the studied job shop problems which are represented by disjunctive graphs It is coupled with a heuristic for assigning and sequencing transportation tasks iteratively To validate our approach, several types of benchmarks with fixed or bounded processing times are tested, co
40 citations
TL;DR: Two new exact methods to solve an integrated employee-timetable and job-shop-scheduling problem by introducing a decomposition and cut generation approach and a hybridization of a cut generation process with a branch and bound strategy are introduced.
Abstract: We propose two exact methods to solve an integrated employee-timetable and job-shop-scheduling problem. The problem is to find a minimum cost employee-timetable, where employees have different competences and work during shifts, so that the production, that corresponds to a job-shop with resource availability constraints, can be achieved. We introduce two new exact procedures: (1) a decomposition and cut generation approach and (2) a hybridization of a cut generation process with a branch and bound strategy. We also propose initial cuts that strongly improve these methods as well as a standard MIP approach. The computational performances of those methods on benchmark instances are compared to that of other methods from the literature.
39 citations
12 Jul 2014
TL;DR: A genetic programming based hyper-heuristic (GPHH) approach is investigated to develop "less-myopic" DRs for dynamic JSS, showing that in the dynamic ten machine job shop, incorporating features of the state of the wider shop, and the stage of a job's journey through the shop, improves the mean performance, and decreases the standard deviation of performance of the best evolved rules.
Abstract: Job Shop Scheduling (JSS) is a complex real-world problem aiming to optimise a measure of delivery speed or customer satisfaction by determining a schedule for processing jobs on machines. A major disadvantage of using a dispatching rule (DR) approach to solving JSS problems is their lack of a global perspective of the current and potential future state of the shop. We investigate a genetic programming based hyper-heuristic (GPHH) approach to develop "less-myopic" DRs for dynamic JSS. Results show that in the dynamic ten machine job shop, incorporating features of the state of the wider shop, and the stage of a job's journey through the shop, improves the mean performance, and decreases the standard deviation of performance of the best evolved rules.
38 citations
TL;DR: In this article, two heuristics based on two different ways of decomposing the problem were proposed to solve the problem in a three-job job shop with two fully skilled operators.
Abstract: This paper deals with complex job shop scheduling problems. A (typically large) number of elementary tasks has to be carried out, according to precedence constraints defined by a task graph. As typical of production environments such as handicraft production and task processing requires two different resources, i.e. machines and human operators. While for each operation a given machine is specified, there are in general more human operators capable of performing it. The problem is to assign the tasks to the operators, sequence them on each operator and sequence them on each machine so that the overall makespan is minimised. This scheduling problem is NP-hard even if the task graph consists of three chains (three-job job shop), and there are two fully skilled operators. We propose two heuristics for this scheduling problem, based on two different ways of decomposing the problem. An extensive computational experience allows a comparison between the heuristic solutions and the one obtained solving a mixed-in...
36 citations
TL;DR: This paper refine COBACABANA to facilitate its implementation, by reducing the number of cards that have to travel with an order to one per operation and updating the approach based on advances in the Workload Control theory.
TL;DR: Two genetic programming methods are proposed to evolve general due-date assignment models for job shop environments and the experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamicDDAMs with promising reusability.
Abstract: Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models DDAMs is complicated. In this study, two genetic programming GP methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.
TL;DR: This paper studies the distributed and flexible job-shop scheduling problem (DFJSP) which involves the scheduling of jobs (products) in a distributed manufacturing environment, under the assumption that the shop floor of each factory/cell is configured as a flexible job shop.
Abstract: The distributed manufacturing takes place in a multi-factory environment including several factories, which may be geographically distributed in different locations, or in a multi-cell environment including several independent manufacturing cells located in the same plant. Each factory/cell is capable of manufacturing a variety of product types. An important issue in dealing with the production in this decentralized manner is the scheduling of manufacturing operations of products (jobs) in the distributed manufacturing system. In this paper, we study the distributed and flexible job-shop scheduling problem (DFJSP) which involves the scheduling of jobs (products) in a distributed manufacturing environment, under the assumption that the shop floor of each factory/cell is configured as a flexible job shop. A fast heuristic algorithm based on a constructive procedure is developed to obtain good quality schedules very quickly. The algorithm is tested on benchmark instances from the literature in order to evaluate its performance. Computational results show that, despite its simplicity, the proposed heuristic is computationally efficient and promising for practical problems.
TL;DR: In this article, a scheduling problem with multi-level job structures in a flexible job shop environment is studied, where the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates.
Abstract: This study deals with a scheduling problem with multi-level job structures in a flexible job shop environment. This scheduling process arises after the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates. MILP (mixed integer linear programming) model is introduced to mathematically represent the target problem. Owing to the high complexity of the target problem, GA (genetic algorithm) is proposed to solve the problem and additional methods, such as priority rules and local search rules, are applied to improve the performance of GA. Computational examples are shown and the results are discussed in comparison with the results of IBM ILOG CPLEX and IBM ILOG CP Optimizer.
01 Nov 2014
TL;DR: Two integer non-linear programming (INLP) models are proposed and a two-stage heuristic algorithm that combines an improving timetabling method and a local search is proposed to solve the BJS-AGV problem.
Abstract: This paper addresses an extension of Block Job shop Scheduling problem taking AGV.Two integer non-linear programming (INLP) models are proposed.A two-stage heuristic combining improved timetabling and local search is developed.Four principles are proposed to guarantee the feasibility of the search.A set of benchmark tests is conducted to testify the effectiveness of the method. The blocking job shop (BJS) problem is an extension of a job shop problem with no buffer constraints. It means that after a job is completed on the current machine, it remains on that machine until the next machine becomes available. This paper addresses an extension of the BJS problem, which takes into account transferring jobs between different machines using a limited number of automated guided vehicles (AGV), called a BJS-AGV problem. Two integer non-linear programming (INLP) models are proposed. A two-stage heuristic algorithm that combines an improving timetabling method and a local search is proposed to solve the BJS-AGV problem. A neighborhood structure in the local search is proposed based on a disjunctive graph model. According to the characteristics of the BJS-AGV problem, four principles are proposed to guarantee the feasibility of the search neighborhood. Computation results are presented for a set of benchmarking tests, some of which are enlarged by transportation times between different machines. The numerical results show the effectiveness of the proposed two-stage algorithm.
TL;DR: In this paper, the authors focus on overcoming the conflict between order release and dispatching, so load-based order release can be combined with due date-oriented dispatching rules.
Abstract: Workload control (WLC) is a well-established production control concept for job shops that put primary emphasis on load-based order release. Recent advances in load-based order release research have led to an improved delivery performance at reduced shop floor workloads. But although order release is the primary focus of WLC research, it must be coupled with priority dispatching on the shop floor if order progress is to be regulated. Prior simulation research suggests that load-based order release methods should only be coupled with simple dispatching rules because other, more powerful rules can conflict with the functioning of the release method. Yet, recent empirical research suggests that powerful priority dispatching rules – such as due date-oriented dispatching rules – are in fact needed for a high level of delivery performance to be obtained in practice. This paper focuses on overcoming the conflict between order release and dispatching, so load-based order release can be combined with due date-orie...
TL;DR: In this article, the effect of different levels of protective capacity on the performance of state-of-the-art WLC release methods has been investigated in a job shop setting.
Abstract: Workload control (WLC) has been developed as a production planning and control approach for job shop manufacturing. By balancing loads across work centres, WLC anticipates the fact that multiple work centres may become potential bottlenecks in the short term. This approach is generally tested in job shop models that assume equal utilisation levels for all work centres, which will create maximum bottleneck shiftiness. However, job shop practice clearly shows differences in utilisation levels, which means that some work centres can be seen as non-bottlenecks, having protective capacity. This study investigates the effect of different levels of protective capacity on the performance of state-of-the-art WLC release methods. More in detail, it shows how the level of protective capacity interacts with the influence of workload norms at work centres. Despite the fact that WLC has been developed for highly balanced utilisations, results indicate that WLC could also be effective in unbalanced situations. However, ...
TL;DR: In this paper, a multi-product lot-sizing problem for a job shop controlled with a heijunka box is discussed, where demand is considered as a random variable with constant variation which must be absorbed by the manufacturing system, either by increased inventory or by flexi-bility in the production.
Abstract: Here we discuss a multi-product lot-sizing problem for a job shop controlled with a heijunka box. Demand is considered as a random variable with constant variation which must be absorbed somehow by the manufacturing system, either by increased inventory or by flexi- bility in the production. When a heijunka concept (production leveling) is used, fluctuations in customer orders are not transferred directly to the manufacturing system allowing for a smoother production and better production capacity utilization. The problem rather is to determine a tradeoff between the variability in the production line capacity requirement and the inventory level.
TL;DR: In this paper, the authors use a job shop simulation model to examine the performance of continuous release methods from the literature and find that the contradictory results are explained by the different rules applied to sequence jobs in the pool.
Abstract: Order release is a key component of the Workload Control concept. Jobs do not enter the shop floor directly – they are retained in a pre-shop pool and released in time to meet due dates while keeping work-in-process within limits or norms. There are two important groups of release methods: continuous methods, for which the workload falling to a specified level can trigger a release at any moment in time; and, periodic release methods, for which releases take place at fixed intervals. Continuous release methods in general have been shown to outperform periodic release methods. Yet, there is incongruence in the results presented in the literature on the relative performance of the various continuous release methods. We use a job shop simulation model to examine the performance of continuous release methods from the literature and find that the contradictory results are explained by the different rules applied to sequence jobs in the pool – a factor neglected in previous work. Finally, a new breed of continu...
TL;DR: In this paper, a quantitative model to describe the effect of safety time as well as the impact of lateness distribution of the production system on schedule compliance, stock level of finished goods and delivery time is presented.
Abstract: Schedule compliance is one of the main logistic objectives of production systems. In order to achieve high schedule compliance, different control variables of a job shop production system can be adopted. This paper focuses on the relationship between such control variables in make-to-order processes. It provides a quantitative model to describe the effect of safety time as well as the impact of lateness distribution of the production system on schedule compliance, stock level of finished goods and delivery time. Furthermore, the applicability of this model is demonstrated by describing the results of an industry project. In this project, the model was applied to design the supply chain of a metal manufacturer to increase the capability to produce on time.
06 Jul 2014
TL;DR: This work investigates a genetic programming based hyper-heuristic (GPHH) approach to evolving dispatching rules for a two-machine job shop in both static and dynamic environments and shows that relative performance of these methods is dependent on the testing instances.
Abstract: Job Shop Scheduling (JSS) involves determining a schedule for processing jobs on machines to optimise some measure of delivery speed or customer satisfaction. We investigate a genetic programming based hyper-heuristic (GPHH) approach to evolving dispatching rules for a two-machine job shop in both static and dynamic environments. In the static case the proposed GPHH method can represent and discover optimal dispatching rules. In the dynamic case we investigate two representations (using a single rule at both machines and evolving a specialised rule for each machine) and the effect of changing the training problem instances throughout evolution. Results show that relative performance of these methods is dependent on the testing instances.
01 Jan 2014
TL;DR: Assessment of the performance of nine dispatching rules in a stochastic dynamic job shop manufacturing system indicates that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures.
Abstract: 有顺序依赖者安装时间的考虑的随机的动态工作商店安排问题在安排问题的最困难的类之中。这份报纸估计九的表演从 makespan，吝啬的流动时间，最大的流动时间，吝啬的缓慢，最大的缓慢，慢工作的数字，全部的安装和性能测量观点的吝啬的安装时间在如此的商店里派遣规则。生产系统的一个随机的动态工作商店的一个分离事件模拟模型为调查目的被开发。从文学识别的九派遣规则在模拟模型被合并。模拟实验在 3 的紧密因素， 90% 的商店利用百分比和安装预定不到处理乘的到期的日期下面被进行。结果显示最短的安装时间(SIMSET ) 统治在吝啬的流动时间和慢工作措施的数字提供最好的性能。有类似的安装和为 makespan，最大的流动时间，吝啬的缓慢，最大的缓慢，全部的安装和吝啬的安装时间的最好的表演测量的统治提供的修改最早到期的日期(JMEDD ) 的工作。
TL;DR: This paper addresses the classic job shop scheduling problem where sequence dependent setup times are present and develops a tabu search algorithm with a sophisticated neighbourhood structure based on a modified disjunctive graph.
TL;DR: In this paper, a new production planning algorithm in virtual cells is proposed for RMS using an improved genetic algorithm, which can realize the nonstop processing for flow style jobs and schedule job shop jobs in order to fully utilize manufacturing capability among machines in multicells.
Abstract: This paper focuses on the scheduling problem of the reconfiguration manufacturing system (RMS) for execution level, where the final objective is to output a production plan. The practical situation in Chinese factory is analyzed, and the characteristics are summarized into the contradiction between flow and job shop production. In order to handle this problem, a new production planning algorithm in virtual cells is proposed for RMS using an improved genetic algorithm. The advantages of this algorithm have three parts: (1) the virtual cell reconfiguration is formed to assist making production plans through providing relationship among task families and machines from cell formation; (2) The operation buffer algorithm is developed for flow style production in cells, which can realize the nonstop processing for flow style jobs; and (3) The multicell sharing method is proposed to schedule job shop jobs in order to fully utilize manufacturing capability among machines in multicells. Based on the above advantages, an improved genetic algorithm is developed to output scheduling plan. At last, the algorithm is tested in different instances with LINGO and the other genetic algorithm, and then the scheduling solution comparison shows the proposed algorithm can get a better optimum result with the same time using the comparison algorithm.
TL;DR: The GRASPxELS provided in the web service, is a state of the art method which competes with previously published methods and which has the advantage of being available for free, in any languages, everywhere contributing in spreading operational research contribution.
Abstract: The Job-Shop Scheduling Problem (JSSP) is well known for its complexity as an NP-hard disjunctive scheduling problem. The problem addressed in this paper is JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. An efficient GRASPxELS approach is introduced for solving this problem. The efficiency is evaluated using the widely known 40 Laurence's instances which encompass medium and large scale instances. The computational results prove that the proposed method competes with the best published methods in both quality of results and computational time. Recently, Web services have generated great interest in researchers. Such application architecture is based on the client-server model using existing Internet protocols and open standards. It provides new approaches to optimization methods. The proposed GRASPxELS is packaged into a Web Service (WS), i.e., it offers for the research community an open access to our optimization approach. Moreover, the proposed web service can be even included in research future works with a very small programming effort. To favor utilization of the web service and to prove the facility in which the service could be used, we provide an example in Java proving that it is possible to obtain in less than 10min a client application using the different methods exposed by this web service. Such usage extends to classical library inclusion in program with the difference that a method is called in the client side and represents an execution on the server. The Web Service paradigm is a new approach in spreading algorithms and therefore this paper stands at the crossroads of optimization research community and the web service community expectations. The GRASPxELS provided in the web service, is a state of the art method which competes with previously published ones and which has the advantage of being available for free, in any languages, everywhere contributing in spreading operational research contribution.
TL;DR: In this article, a discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose, and nine dispatching rules identified from literature are incorporated in the simulation model.
Abstract: Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.
TL;DR: In this paper, the performance of four of the best-performing release methods from the literature in a job shop with sequence-dependent set-up times by simulation is compared without considering setup requirements at release.
Abstract: Findings from recent implementations of Workload Control (WLC) have called for research to investigate how sequence-dependent set-up times can best be handled within the design of the concept. In response, this study assesses the performance of four of the best-performing release methods from the literature in a job shop with sequence-dependent set-up times by simulation. First, the four methods are compared without considering set-up requirements at release. Second, the methods are refined to consider set-up requirements before being compared against the original methods. A release method that combines continuous and periodic release emerges as the best-performing method. Findings further suggest that considering set-up requirements at release do not have a significant positive effect on performance and may even be counterproductive: conflicting goals between the selection rules employed at release and dispatching may lead to an increase in the percentage of tardy jobs. Future research should consider wh...
18 Aug 2014
TL;DR: The space of semi-active and active fuzzy schedules is formally defined and different schedule-generation schemes (SGSs) are proposed and analysed in this fuzzy framework to study dominance properties of the set of schedules obtained with each SGS.
Abstract: We consider the job shop scheduling problem with fuzzy durations and expected makespan minimisation. We formally define the space of semi-active and active fuzzy schedules and propose and analyse different schedule-generation schemes (SGSs) in this fuzzy framework. In particular, we study dominance properties of the set of schedules obtained with each SGS. Finally, a computational study illustrates the great difference between the spaces of active and the semi-active fuzzy schedules, an analogous behaviour to that of the deterministic job shop.
TL;DR: This paper reports usage of a framework which exploits the diversified global search and the intensified local search capabilities of GA and TS, respectively, and evaluates its suitability by applying it on a set of well-known job shop benchmark problems.
Abstract: It has been well established that to find an optimal or near-optimal solution to job shop scheduling problems (JSSPs), which are NP-hard, one needs to harness different features of many techniques, such as genetic algorithms (GAs) and tabu search (TS). In this paper, we report usage of such a framework which exploits the diversified global search and the intensified local search capabilities of GA and TS, respectively. The system takes its input directly from the process information in contrast to having a problem-specific input format, making it versatile in dealing with different JSSP. This framework has been successfully implemented to solve industrial JSSPs. In this paper, we evaluate its suitability by applying it on a set of well-known job shop benchmark problems. The results have been variable. The system did find optimal solutions for moderately hard benchmark problems (40 out of 43 problems tested). This performance is similar to, and in some cases better than, comparable systems, which also esta...
TL;DR: The Push-Kanban production control concept as discussed by the authors combines robust push scheduling along with a kanban-driven, decentralised inventory control mechanism to create a holistic control approach, integrating all production control tasks.
Abstract: Job-shop production in an individual and small-batch manufacturing environment demands producing simultaneously different products in many customised versions and in small numbers. The associated variability of the time-phased work content leads to a high degree of complexity and turbulence in the manufacturing process of such a production type. Therefore, production control becomes significantly more complicated, and many theories on how to cope fail in the real world. Despite the many technological and conceptual advances in the field of job-shop control over the past few decades, there is still a remarkable lack of practical control approaches for job-shop production. For this reason the Push-Kanban production control concept will be introduced in this article. It combines robust push scheduling along with a kanban-driven, decentralised inventory control mechanism to create a holistic control approach, integrating all production control tasks. Thus, it offers a feasible option for controlling job-shop ...