Tabu search for the job-shop scheduling problem with multi-purpose machines
Hurink, Johann; Jurisch, Bernd; Thole, Monika
1994-01-01
In this paper we study the following generalization of the job-shop scheduling problem. Each operation can be performed by one machine out of a set of machines given for this operation. The processing time does not depend on the machine which has been chosen for processing the operation. This proble
Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines
Directory of Open Access Journals (Sweden)
Eliana Marcela Peña Tibaduiza
2017-01-01
Full Text Available Context: The flow shop hybrid problem with unrelated parallel machines has been less studied in the academia compared to the flow shop hybrid with identical processors. For this reason, there are few reports about the kind of application of this problem in industries. Method: A literature review of the state of the art on flow-shop scheduling problem was conducted by collecting and analyzing academic papers on several scientific databases. For this aim, a search query was constructed using keywords defining the problem and checking the inclusion of unrelated parallel machines in such definition; as a result, 50 papers were finally selected for this study. Results: A classification of the problem according to the characteristics of the production system was performed, also solution methods, constraints and objective functions commonly used are presented. Conclusions: An increasing trend is observed in studies of flow shop with multiple stages, but few are based on industry case-studies.
Two-machine flow shop scheduling integrated with preventive maintenance planning
Wang, Shijin; Liu, Ming
2016-02-01
This paper investigates an integrated optimisation problem of production scheduling and preventive maintenance (PM) in a two-machine flow shop with time to failure of each machine subject to a Weibull probability distribution. The objective is to find the optimal job sequence and the optimal PM decisions before each job such that the expected makespan is minimised. To investigate the value of integrated scheduling solution, computational experiments on small-scale problems with different configurations are conducted with total enumeration method, and the results are compared with those of scheduling without maintenance but with machine degradation, and individual job scheduling combined with independent PM planning. Then, for large-scale problems, four genetic algorithm (GA) based heuristics are proposed. The numerical results with several large problem sizes and different configurations indicate the potential benefits of integrated scheduling solution and the results also show that proposed GA-based heuristics are efficient for the integrated problem.
Cyclic flow shop scheduling problem with two-machine cells
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Bożejko Wojciech
2017-06-01
Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.
Job shop scheduling model for non-identic machine with fixed delivery time to minimize tardiness
Kusuma, K. K.; Maruf, A.
2016-02-01
Scheduling non-identic machines problem with low utilization characteristic and fixed delivery time are frequent in manufacture industry. This paper propose a mathematical model to minimize total tardiness for non-identic machines in job shop environment. This model will be categorized as an integer linier programming model and using branch and bound algorithm as the solver method. We will use fixed delivery time as main constraint and different processing time to process a job. The result of this proposed model shows that the utilization of production machines can be increase with minimal tardiness using fixed delivery time as constraint.
Scheduling of flow shop problems on 3 machines in fuzzy environment with double transport facility
Sathish, Shakeela; Ganesan, K.
2016-06-01
Flow shop scheduling is a decision making problem in production and manufacturing field which has a significant impact on the performance of an organization. When the machines on which jobs are to be processed are placed at different places, the transportation time plays a significant role in production. Further two different transport agents where 1st takes the job from 1st machine to 2nd machine and then returns back to the first machine and the 2nd takes the job from 2nd machine to 3rd machine and then returns back to the 2nd machine are also considered. We propose a method to minimize the total make span; without converting the fuzzy processing time to classical numbers by using a new type of fuzzy arithmetic and a fuzzy ranking method. A numerical example is provided to explain the proposed method.
A bi-criteria M-machine SDST flow shop scheduling using modified ...
African Journals Online (AJOL)
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1*Department of Mechanical Engineering, University Institute of Engineering &Technology, ... Keywords: Flow shop scheduling, Modified Heuristic Genetic algorithm (MHGA), .... and Mirghorbani (2007) developed multi-objective particle swarm optimization for flow shop ..... Designing optimal parameters using design of ...
H. Gong; L. Tang; C.W. Duin
2010-01-01
Motivated by applications in iron and steel industry, we consider a two-stage flow shop scheduling problem where the first machine is a batching machine subject to the blocking constraint and the second machine is a discrete machine with shared setup times. We show that the problem is strongly NP-ha
Gong, H.; Tang, L.; Duin, C.W.
2010-01-01
Motivated by applications in iron and steel industry, we consider a two-stage flow shop scheduling problem where the first machine is a batching machine subject to the blocking constraint and the second machine is a discrete machine with shared setup times. We show that the problem is strongly
HOW GOOD IS A DENSE SHOP SCHEDULE?
Institute of Scientific and Technical Information of China (English)
陈礴; 俞文(鱼此)
2001-01-01
In this paper, we study a class of simple and easy-to-construct shop schedules, known as dense schedules. We present tight bounds on the maximum deviation in makespan of dense flow-shop and job-shop schedules from their optimal ones. For dense open-shop schedules, we do the same for the special case of four machines and thus add a stronger supporting case for proving a standing conjecture.
Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem
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Mohammed Al-Salem
2016-01-01
Full Text Available The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD for a set of jobs when their weights equal 1 (unweighted problem. This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.
Two-agent scheduling in open shops subject to machine availability and eligibility constraints
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Ling-Huey Su
2015-09-01
Full Text Available Purpose: The aims of this article are to develop a new mathematical formulation and a new heuristic for the problem of preemptive two-agent scheduling in open shops subject to machine maintenance and eligibility constraints. Design/methodology: Using the ideas of minimum cost flow network and constraint programming, a heuristic and a network based linear programming are proposed to solve the problem. Findings: Computational experiments show that the heuristic generates a good quality schedule with a deviation of 0.25% on average from the optimum and the network based linear programming model can solve problems up to 110 jobs combined with 10 machines without considering the constraint that each operation can be processed on at most one machine at a time. In order to satisfy this constraint, a time consuming Constraint Programming is proposed. For n = 80 and m = 10, the average execution time for the combined models (linear programming model combined with Constraint programming exceeds two hours. Therefore, the heuristic algorithm we developed is very efficient and is in need. Practical implications: Its practical implication occurs in TFT-LCD and E-paper manufacturing wherein units go through a series of diagnostic tests that do not have to be performed in any specified order. Originality/value: The main contribution of the article is to split the time horizon into many time intervals and use the dispatching rule for each time interval in the heuristic algorithm, and also to combine the minimum cost flow network with the Constraint Programming to solve the problem optimally.
Liou, Cheng-Dar; Hsieh, Yi-Chih; Chen, Yin-Yann
2013-01-01
This article investigates the two-machine flow-shop group scheduling problem (GSP) with sequence-dependent setup and removal times, and job transportation times between machines. The objective is to minimise the total completion time. As known, this problem is an NP-hard problem and generalises the typical two-machine GSPs. In this article, a new encoding scheme based on permutation representation is proposed to transform a random job permutation to a feasible permutation for GSPs. The proposed encoding scheme simultaneously determines both the sequence of jobs in each group and the sequence of groups. By reasonably combining particle swarm optimisation (PSO) and genetic algorithm (GA), we develop a fast and easily implemented hybrid algorithm (HA) for solving the considered problems. The effectiveness and efficiency of the proposed HA are demonstrated and compared with those of standard PSO and GA by numerical results of various tested instances with group numbers up to 20. In addition, three different lower bounds are developed to evaluate the solution quality of the HA. Limited numerical results indicate that the proposed HA is a viable and effective approach for the studied two-machine flow-shop group scheduling problem.
How the Landscape of Random Job Shop Scheduling Instances Depends on the Ratio of Jobs to Machines
Smith, S F; 10.1613/jair.2013
2011-01-01
We characterize the search landscape of random instances of the job shop scheduling problem (JSP). Specifically, we investigate how the expected values of (1) backbone size, (2) distance between near-optimal schedules, and (3) makespan of random schedules vary as a function of the job to machine ratio (N/M). For the limiting cases N/M approaches 0 and N/M approaches infinity we provide analytical results, while for intermediate values of N/M we perform experiments. We prove that as N/M approaches 0, backbone size approaches 100%, while as N/M approaches infinity the backbone vanishes. In the process we show that as N/M approaches 0 (resp. N/M approaches infinity), simple priority rules almost surely generate an optimal schedule, providing theoretical evidence of an "easy-hard-easy" pattern of typical-case instance difficulty in job shop scheduling. We also draw connections between our theoretical results and the "big valley" picture of JSP landscapes.
Directory of Open Access Journals (Sweden)
Yingni Zhai
2014-10-01
Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the
The shop floor scheduling game
Riezebos, Jan; Slomp, Jannes
1995-01-01
The aim of the shop floor scheduling game is getting participants acquainted with: - developing robust planning and scheduling procedures; - accepting orders under uncertainty and competition; - using information from cost accounting in scheduling; - creating an adequate communication structure
Dynamic Scheduling of Flexible Job Shops
Institute of Scientific and Technical Information of China (English)
SHAHID Ikramullah Butt; SUN Hou-fang
2007-01-01
Aim of this research is to minimize makespan in the flexible job shop environment by the use of genetic algorithms and scheduling rules.Software is developed using genetic algorithms and scheduling rules based on certain constraints such as non-preemption of jobs,recirculation,set up times,non-breakdown of machines etc.Purpose of the software is to develop a schedule for flexible job shop environment,which is a special case of job shop scheduling problem.Scheduling algorithm used in the software is verified and tested by using MT10 as benchmark problem,presented in the flexible job shop environment at the end.LEKIN(R) software results are also compared with results of the developed software by the use of MT10 benchmark problem to show that the latter is a practical software and can be used successfully at BIT Training Workshop.
Miller, Rex
2004-01-01
Use the right tool the right wayHere, fully updated to include new machines and electronic/digital controls, is the ultimate guide to basic machine shop equipment and how to use it. Whether you're a professional machinist, an apprentice, a trade student, or a handy homeowner, this fully illustrated volume helps you define tools and use them properly and safely. It's packed with review questions for students, and loaded with answers you need on the job.Mark Richard Miller is a Professor and Chairman of the Industrial Technology Department at Texas A&M University in Kingsville, T
Scheduling job shop - A case study
Abas, M.; Abbas, A.; Khan, W. A.
2016-08-01
The scheduling in job shop is important for efficient utilization of machines in the manufacturing industry. There are number of algorithms available for scheduling of jobs which depend on machines tools, indirect consumables and jobs which are to be processed. In this paper a case study is presented for scheduling of jobs when parts are treated on available machines. Through time and motion study setup time and operation time are measured as total processing time for variety of products having different manufacturing processes. Based on due dates different level of priority are assigned to the jobs and the jobs are scheduled on the basis of priority. In view of the measured processing time, the times for processing of some new jobs are estimated and for efficient utilization of the machines available an algorithm is proposed and validated.
NEW NONSTANDARD JOB SHOP SCHEDULING ALGORITHM
Institute of Scientific and Technical Information of China (English)
XIE Zhiqiang; YE Guangjie; ZHANG Dali; TAN Guangyu
2008-01-01
Considering the complex constraint between operations in nonstandard job shop scheduling problem (NJSSP), critical path of job manufacturing tree is determined according to priority scheduling function constructed. Operations are divided into dependent operations and independent operations with the idea of subsection, and corresponding scheduling strategy is put forward according to operation characteristic in the segment and the complementarities of identical function machines. Forward greedy rule is adopted mainly for dependent operations to make operations arranged in the right position of machine selected, then each operation can be processed as early as possible, and the total processing time of job can be shortened as much as possible. For independent operations optimum scheduling rule is adopted mainly, the inserting position of operations will be determined according to the gap that the processing time of operations is subtracted from idle time of machine, and the operation will be inserted in the position with minimal gap. Experiments show, under the same conditions, the result that operations are scheduled according to the object function constructed, and the scheduling strategy adopted is better than the result that operations are scheduled according to efficiency scheduling algorithm.
FLOW-SHOP SCHEDULING WITH MULTIPLE OPERATIONS AND TIME LAGS
RIEZEBOS, J; GAALMAN, GJC; GUPTA, JND
1995-01-01
A scheduling system is proposed and developed for a special type of flow shop. Ln this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j - 1 has finish
FLOW-SHOP SCHEDULING WITH MULTIPLE OPERATIONS AND TIME LAGS
RIEZEBOS, J; GAALMAN, GJC; GUPTA, JND
A scheduling system is proposed and developed for a special type of flow shop. Ln this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j - 1 has
Directory of Open Access Journals (Sweden)
S. Dousthaghi
2012-08-01
Full Text Available This paper considers an economic lot and delivery scheduling problem (ELDSP in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP approach. In this paper, a mixed-integer nonlinear programming (MINLP model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples.
Directory of Open Access Journals (Sweden)
José Eduardo Márquez-Delgado
2012-09-01
Full Text Available En este trabajo se utiliza la metaheurística nombrada algoritmo genético, para dos variantes típicas de problemas de planificación presentes en un taller de maquinado de piezas: las variantes flujo general y flujo regular, y se ha seleccionado la minimización del tiempo de finalización de todos los trabajos ocamino máximo, como objetivo a optimizar en un plan de trabajo. Este problema es considerado de difícil solución y es típico de la optimización combinatoria. Los resultados demuestran la calidad de las soluciones encontradas en correspondencia con el tiempo de cómputo empleado, al ser comparados conproblemas clásicos reportados por otros autores. La representación propuesta de cada cromosoma genera el universo completo de soluciones factibles, donde es posible encontrar valores óptimos globales de solución y cumple con las restricciones del problema.Palabras claves: algoritmo genético, cromosomas, flujo general, flujo regular, planificación, camino máximo._____________________________________________________________________________AbstractIn this paper we use the metaheuristic named genetic algorithm, for two typical variants of problems of scheduling present in a in a machine shop parts: the variant job shop and flow shop, and the minimization of the time of finalization of all the works has been selected, good known as makespan, as objective tooptimize in a work schedule. This problem is considered to be a difficult solution and is typical in combinatory optimization. The results demonstrate the quality of the solutions found in correspondence with the time of used computation, when being compared with classic problems reported by other authors.The proposed representation of each chromosome generates the complete universe of feasible solutions, where it is possible to find global good values of solution and it fulfills the restrictions of the problem.Key words: genetic algorithm, chromosomes, flow shop, job shop
Three Algorithms for Flexible Flow-shop Scheduling
Directory of Open Access Journals (Sweden)
T. P. Hong
2007-01-01
Full Text Available Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling can reduce material handling costs and time. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Flexible flow shops are thus generalization of simple flow shops. In this paper, we propose three algorithms to solve flexible flow-shop problems of more than two machine centers. The first one extends Sriskandarajah and Sethis method by combining both the LPT and the search-and-prune approaches to get a nearly optimal makespan. It is suitable for a medium-sized number of jobs. The second one is an optimal algorithm, entirely using the search-and-prune technique. It can work only when the job number is small. The third one is similar to the first one, except that it uses Petrovs approach (PT to deal with job sequencing instead of search-and-prune. It can get a polynomial time complexity, thus being more suitable for real applications than the other two. Experiments are also made to compare the three proposed algorithms. A trade-off can thus be achieved between accuracy and time complexity.
Institute of Scientific and Technical Information of China (English)
HE Long-min; SUN Shi-jie; CHENG Ming-bao
2008-01-01
This paper considers a hybrid two-stage flow-shop scheduling problem with m identical parallel machineson one stage and a batch processor on the other stage.The processing time of job Jj on any of m identical parallel machines is aj≡a(j∈N),and the processing time of job Jj is bj(j∈N)on a batch processor M.We take makespan(Cmax)as our minimization objective.In this paper,for the problem of FSMP-BI(m identical parallel machines on the first stage and a batch processor on the second stage),based on the algorithm given by Sung and Choung for the problem of l I rj,BI I Cmax under the constraint of the given processing sequence,we develop an optimal dynamic programming Algorithm H1 for it in max{O(nlogn),O(nB)} time.A max{O(nlogn),O(nB)} time symmetric Algorithm H2 is given then for the problem of BI-FSMP(a batch processor on the first stage and m identical parallel machines on the second stage).
Active Shop Scheduling Of Production Process Based On RFID Technology
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Cuihua Chao
2016-01-01
Full Text Available In industry 4.0 environment, intelligent technology is almost applied to all parts of the manufacturing process, such as process design, job shop scheduling, etc.. This paper presents an efficient approach to job shop scheduling actively by using RFID to collect real-time manufacturing data. Identified the workpiece by RFID which needs to be machined, it can “ask for” the resource actively for the following process. With these active asking-for strategy, a double genetically encoded improved genetic algorithm is proposed for achieving active job shop scheduling solution during the actual manufacturing process. A case was used to evaluate its effectiveness. Meanwhile, , it can effectively and actively carry out job shop scheduling and has much better convergence effect comparing with basic genetic algorithm. And the job shop scheduler in management center can use the proposed algorithm to get the satisfied scheduling result timely by reducing waiting time and making begin time earlier during transmission between manufacturing process, which makes the scheduling result feasible and accurate.
NOISE REDUCTION SCHEDULING METHOD IN A SHOP FLOOR AND ITS CASE STUDY
Institute of Scientific and Technical Information of China (English)
Liu Fei; Cao Huajun; Zhang Hua; Yuan Chuanping
2003-01-01
Noise reduction in a shop floor is one of the important parts of green manufacturing. In a shop floor, machine tools are the main noise sources in a shop floor. A new approach is discovered by investigation that the noise can be obviously reduced in a shop floor by optimizing the scheduling between work pieces and machine tools. Based on the discovery, a new method of noise reduction is proposed. A noise reduction scheduling model in a shop floor is established, and the application of the model is also discussed. A case is studied, which shows that the method and model are practical.
Standardized Curriculum for Machine Tool Operation/Machine Shop.
Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.
Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…
Job shop scheduling problem with late work criterion
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.
OPTIMISATION OF JOB SHOP SCHEDULING USING SHIFTING BOTTLENECK TECHNIQUE
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Katuru Phani Raja Kumar
2013-07-01
Full Text Available In manufacturing system the problem of scheduling machines is a difficult task to reach the due date of the productivity. The Job Shop Scheduling have been solved by different algorithms and methods based on the sequence operation constraints and processing times for small size problems. The JSSP with m machines and n jobs is represented to determine an optimal solution by using the shortest processing time technique and Gantt chart is drawn to visually represent the total makespan. The shifting bottleneck method has been used to reduce the total flow time of the JSSP and arrive at an optimal solution.
Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Tao Ren
2012-01-01
Full Text Available This paper considers the m-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.
EFFICIENT MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR JOB SHOP SCHEDULING
Institute of Scientific and Technical Information of China (English)
Lei Deming; Wu Zhiming
2005-01-01
A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.
A Dynamic Job Shop Scheduling Method Based on Lagrangian Relaxation
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
Due to the complexity of dynamic job shop scheduling in flexible manufacturing s ystem(FMS), many heuristic rules are still used today. A dynamic scheduling appr oach based on Lagrangian relaxation is proposed to improve the quality and guara ntee the real-time capability of dynamic scheduling. The proposed method makes use of the dynamic predictive optimal theory combined with Lagrangian relaxation to obtain a good solution that can be evaluated quantitatively. The Lagrangian multipliers introduced here are capable of describing machine predictive states and system capacity constraints. This approach can evaluate the suboptimality of the scheduling systems. It can also quickly obtain high quality feasible schedu les, thus enabling Lagrangian relaxation to be better used in the dynamic schedu ling of manufacturing system. The efficiency and effectiveness of this method ar e verified by numerical experiments.
A Fast Method for Heuristics in Large-Scale Flow Shop Scheduling
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Fast computation methods are needed for the heuristics of flow shop scheduling problems in practical manufacturing environments. This paper describes a generalized flow shop model, which is an extension of the classical model, in which not all machines are available at time zero. The general completion-time computing method is used to compute completion time of generalized flow shops. The transform classical flow shop to generalized shop (TCG) method is used to transform classical schedules into generalized schedules with less jobs. INSERT and SWAP, extended from job-insertion and pair-wise exchange which are fundamental procedures used in most heuristics for classical flow shops, reduce the CPU time by 1/2 and 1/3, respectively. The CPU time of 14 job-insertion and pair-wise exchange-based heuristics are analyzed with and without the TCG method. The results show that TCG considerably reduces the CPU time.
Job-shop Scheduling Model and Algorithm with Machine Deterioration%设备带有恶化特性的作业车间调度模型与算法
Institute of Scientific and Technical Information of China (English)
黄敏; 付亚平; 王洪峰; 朱兵虎; 王兴伟
2015-01-01
For the job-shop scheduling problem, a job-shop scheduling model with machine deterioration is built in order to minimize makespan, considering that the processing time of jobs is a linearly increasing function of the start time. Then a nested partition method is designed for solving it. In the sampling process, the partheno-genetic algorithm is embedded into the nested partition method in order to ensure the diversity of sampling and quality. Simulation experiments show that the proposed algorithm for solving job-shop scheduling problem with machine deterioration can get higher quality solutions and have a better robustness.%考虑到现实作业车间调度中设备具有恶化特性，针对作业的处理时间是开始时间的线性递增函数的作业车间调度问题，建立了以最小化最迟完成时间为目标的优化模型，进而设计了嵌套分割算法进行求解。该算法在抽样阶段嵌入单亲遗传算法以提高抽样的多样性和质量。实例结果表明，所提出的算法在解决该问题上可以获得较高质量的解，并且具有很好的鲁棒性。
Job shop scheduling problem based on DNA computing
Institute of Scientific and Technical Information of China (English)
Yin Zhixiang; Cui Jianzhong; Yang Yan; Ma Ying
2006-01-01
To solve job shop scheduling problem, a new approach-DNA computing is used in solving job shop scheduling problem. The approach using DNA computing to solve job shop scheduling is divided into three stands. Finally, optimum solutions are obtained by sequencing. A small job shop scheduling problem is solved in DNA computing, and the "operations" of the computation were performed with standard protocols, as ligation, synthesis, electrophoresis etc. This work represents further evidence for the ability of DNA computing to solve NP-complete search problems.
机器柔性度对柔性车间调度影响的研究%Research on impact of flexible machine in Flexible Job-shop Scheduling
Institute of Scientific and Technical Information of China (English)
林仁; 周国华
2015-01-01
In view of the research shortage in the relationship between resource flexibility and scheduling effect, the repre-sentation method of resource flexibility distribution and the measure method of machine flexibility are proposed based on resource-ability matrix, then the model about Flexible Job-shop Scheduling Problem(FJSP)under machine flexible con-straints is established. Improved dual population ant colony algorithm is present to solve the model. Finally, the case proves the effect of flexible degree of machine resources on the scheduling result, and it provides guidance for the construction of flexible manufacturing system.%针对资源柔性与调度效果关系研究匮乏的问题，提出了采用资源－能力矩阵对资源柔性分布进行表示的方法和机器资源柔性程度的度量方法，建立了机器资源柔性约束下的作业车间调度问题模型，采用改进双种群蚁群算法进行求解。案例证明了机器资源柔性程度对调度效果的影响，为构建柔性制造系统提供了指导意见。
Minimizing makespan in a two-stage hybrid flow shop scheduling problem with open shop in one stage
Institute of Scientific and Technical Information of China (English)
DONG Jian-ming; HU Jue-liang; CHEN Yong
2013-01-01
This paper considers a scheduling problem in two-stage hybrid flow shop, where the first stage consists of two machines formed an open shop and the other stage has only one machine. The objective is to minimize the makespan, i.e., the maximum completion time of all jobs. We first show the problem is NP-hard in the strong sense, then we present two heuristics to solve the problem. Computational experiments show that the combined algorithm of the two heuristics performs well on randomly generated problem instances.
Production Machine Shop Employment Competencies. Part Four: The Milling Machine.
Bishart, Gus; Werner, Claire
Competencies for production machine shop are provided for the fourth of four topic areas: the milling machine. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment, will establish…
Integrating Genetic Algorithm, Tabu Search Approach for Job Shop Scheduling
Thamilselvan, R
2009-01-01
This paper presents a new algorithm based on integrating Genetic Algorithms and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of the proposed algorithm is derived from Genetic Algorithms. Most of the scheduling problems require either exponential time or space to generate an optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and it is a NP-complete problem, but it is difficult to find the optimal solution. This paper applies Genetic Algorithms and Tabu Search for Job Shop Scheduling problem and compares the results obtained by each. With the implementation of our approach the JSS problems reaches optimal solution and minimize the makespan.
MODIFIED BOTTLENECK-BASED PROCEDURE FOR LARGE-SCALE FLOW-SHOP SCHEDULING PROBLEMS WITH BOTTLENECK
Institute of Scientific and Technical Information of China (English)
ZUO Yan; GU Hanyu; XI Yugeng
2006-01-01
A new bottleneck-based heuristic for large-scale flow-shop scheduling problems with a bottleneck is proposed, which is simpler but more tailored than the shifting bottleneck (SB)procedure. In this algorithm, a schedule for the bottleneck machine is first constructed optimally and then the non-bottleneck machines are scheduled around the bottleneck schedule by some effective dispatching rules. Computational results show that the modified bottleneck-based procedure can achieve a tradeoff between solution quality and computational time comparing with SB procedure for medium-size problems. Furthermore it can obtain a good solution in quite short time for large-scale scheduling problems.
A Method of Flow-Shop Re-Scheduling Dealing with Variation of Productive Capacity
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Kenzo KURIHARA
2005-02-01
Full Text Available We can make optimum scheduling results using various methods that are proposed by many researchers. However, it is very difficult to process the works on time without delaying the schedule. There are two major causes that disturb the planned optimum schedules; they are (1the variation of productive capacity, and (2the variation of products' quantities themselves. In this paper, we deal with the former variation, or productive capacities, at flow-shop works. When production machines in a shop go out of order at flow-shops, we cannot continue to operate the productions and we have to stop the production line. To the contrary, we can continue to operate the shops even if some workers absent themselves. Of course, in this case, the production capacities become lower, because workers need to move from a machine to another to overcome the shortage of workers and some shops cannot be operated because of the worker shortage. We developed a new re-scheduling method based on Branch-and Bound method. We proposed an equation for calculating the lower bound for our Branch-and Bound method in a practical time. Some evaluation experiments are done using practical data of real flow-shop works. We compared our results with those of another simple scheduling method, and we confirmed the total production time of our result is shorter than that of another method by 4%.
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Mostafa Kazemi
2012-10-01
Full Text Available In this paper, we consider job shop scheduling and machine location problem, simultaneously. Processing, transportation, and setup times are defined as deterministic parameters. The purpose of this paper is to determine machine location and job scheduling such that the make span and transportation cost is minimized. Therefore, the proposed model is a multi-objective problem one, where the first objective function minimizes make span and another minimizes the transportation cost. To solve the multi-objective problem, two methods are evaluated. Considering combination of job shop scheduling problem and machine location problem makes the proposed model more complex than job shop scheduling problem, which is an NP-hard problem. Therefore, to solve the proposed model, genetic algorithm as a meta-heuristic algorithm is implemented. To show the efficiency of the proposed genetic algorithm, 6×6 job shop scheduling problems are considered.
Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
With an aim at the job-shop scheduling problem of multiple resource constraints, this paper presents mixed self-adapting Genetic Algorithm (GA), and establishes a job-shop optimal scheduling model of multiple resource constraints based on the effect of priority scheduling rules in the heuristic algorithm upon the scheduling target. New coding regulations or rules are designed. The sinusoidal function is adopted as the self-adapting factor, thus making cross probability and variable probability automatically change with group adaptability in such a way as to overcome the shortcoming in the heuristic algorithm and common GA, so that the operation efficiency is improved. The results from real example simulation and comparison with other algorithms indicate that the mixed self-adapting GA algorithm can well solve the job-shop optimal scheduling problem under the constraints of various kinds of production resources such as machine-tools and cutting tools.
A PSL Ontology-based Shop Floor Dynamical Scheduler Design
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WANG Wei-da; XU He; PENG Gao-liang; LIU Wen-jian; Khalil Alipour
2008-01-01
Due to the complex,uncertainty and dynamics in the modern manufacturing environment,a flexible and robust shop floor scheduler is essential to achieve the production goals.A design framework of a shop floor dynamical scheduler is presented in this paper.The workflow and function modules of the scheduler are discussed in detail.A multi-step adaptive scheduling strategy and a process specification language,which is an ontology-based representation of process plan,are utilized in the proposed scheduler.The scheduler acquires the dispatching rule from the knowledge base and uses the build in on-line simulator to evaluate the obtained rule.These technologies enable the scheduler to improve its fine-tune ability and effectively transfer process information into other heterogeneous information systems in a shop floor.The effectiveness of the suggested structure will be demonstrated via its application in the scheduling system of a manufacturing enterprise.
JOB SHOP RE- SCHEDULING USING GENETIC ALGORITHM – A CASE STUDY
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P.ChithtraiSelvam
2012-09-01
Full Text Available Scheduling concerns the allocation of limited resources overtime to perform tasks to fulfill certain criterion. One of the most popular models in scheduling theory is that of the job-shop scheduling, as it has earned a reputation for being notoriously difficult to solve. A job-shop scheduling problem comes under the category of combinatorial optimization problems and is very difficult to solve by conventional optimization techniques. Many scheduling problems from manufacturing industries are complex in nature and are to be best known about the difficult combinatorial optimization problems with a finite number of feasible solutions. A machine shop with four numbers of machines and five numbers of jobs and the following assumptions are taken into account and the machines are available at zero time and there are no breakdowns, machine processes one operation at a time and once an operation initiates processing on a given machine the machine stops only when the operation is over and the processing times are deterministic. In this present work, a rescheduling is done for the existing jobshop in a small scale industry and this problem is solved using the non-traditional optimization technique like Genetic Algorithms. Their performances are depicted graphically to exhibit how they have converged to the optimal solution.
A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
Gonçalves, José Fernando; Mendes, J. J. M.; Resende, Maurício G. C.
2005-01-01
This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set o...
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Behnam Barzegar
2012-01-01
Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.
Institute of Scientific and Technical Information of China (English)
刘佳; 刘林
2012-01-01
In the circumstance of multi machine Job_Shop scheduling, restricting to order-dependent setup-time and taking an overall consideration of the two factors-completion time and earliness/tardiness penalties ,this research proposes a hybrid genetic al- gorithm based on sequential coding of jobs on machines and interleaved mode in genes and integrates variable neighborhood search （VNS）and cluster analysis ,making the Pareto solution set more effective in quality and distribution.%分析并讨论了带调整时间即换模具时间，综合考虑工件完工时间、不同交货期窗口下的提前／拖期惩罚、并行机环境下的多目标Job—Shop调度问题，提出了一种基于不同工件工序排序的染色体编码方式，利用稳步遗传算法求解，并融合变邻域搜索和依角度聚类的方法，使得求得的Pareto解集在质量和分布上均有较好的效果。仿真实验表明了此种算法的可行性和有效性。
An Iterative Layered Tabu Search Algorithm for Complex Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
LIUMin; DONGMingyu; WUCheng
2005-01-01
In this paper, aiming at the complex characteristics that there exist two interrelated decision processes: job-assignment decision and job-sequencing decision in the complex job shop scheduling problem with parallel machines and technical constraints, we propose an Iterative layered tabu search algorithm (ILTSA), which combines the iterative and layered mechanism with tabu search algorithm. In ILTSA, we define the notation of the optimization layer including the job-assignment optimization layer and the job-sequencing optimization layer which correspond to the above two interrelated decision processes respectively. On the basis, we use the corresponding tabu search algorithms in different optimization layers and switch iteratively the above two tabu search algorithms between the two optimization layers to improve the performance of the scheduling algorithm effectively. In the above two TS algorithms, the measuring functions are the objective of the whole scheduling problem. At last, we make numerical computations for different scale scheduling problems of minimizing the makespan and minimizing the total number of tardy jobs respectively, and numerical computational results show that ILTSA is very efficient and suitable for solving larger scale job shop scheduling problem with parallel machines and technical constraints. Also, we apply successfully ILTSA to a practical complex job shop scheduling problem with parallel machines and technical constraints in one of the largest cotton colored weaving enterprises in China.
Mathematical Model and Hybrid Scatter Search for Cost Driven Job-shop Scheduling Problem
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Bai Jie
2011-07-01
Full Text Available Job-shop scheduling problem (JSP is one of the most well-known machine scheduling problems and one of the strongly NP-hard combinatorial optimization problems. Cost optimization is an attractive and critical research and development area for both academic and industrial societies. This paper presents a cost driven model of the job-shop scheduling problem in which the solutions are driven by business inputs, such as the cost of the product transitions, revenue loss due to the machine idle time and earliness/tardiness penalty. And then, a new hybrid scatter search algorithm is proposed to solve the cost driven job-shop scheduling problem by introducing the simulated annealing (SA into the improvement method of scatter search (SS. In order to illustrate the effectiveness of the hybrid method, some test problems are generated, and the performance of the proposed method is compared with other evolutionary algorithms such as genetic algorithm and simulated annealing. The experimental simulation tests show that the hybrid method is quite effective at solving the cost driven job-shop scheduling problem.
Multiagent scheduling method with earliness and tardiness objectives in flexible job shops.
Wu, Zuobao; Weng, Michael X
2005-04-01
Flexible job-shop scheduling problems are an important extension of the classical job-shop scheduling problems and present additional complexity. Such problems are mainly due to the existence of a considerable amount of overlapping capacities with modern machines. Classical scheduling methods are generally incapable of addressing such capacity overlapping. We propose a multiagent scheduling method with job earliness and tardiness objectives in a flexible job-shop environment. The earliness and tardiness objectives are consistent with the just-in-time production philosophy which has attracted significant attention in both industry and academic community. A new job-routing and sequencing mechanism is proposed. In this mechanism, two kinds of jobs are defined to distinguish jobs with one operation left from jobs with more than one operation left. Different criteria are proposed to route these two kinds of jobs. Job sequencing enables to hold a job that may be completed too early. Two heuristic algorithms for job sequencing are developed to deal with these two kinds of jobs. The computational experiments show that the proposed multiagent scheduling method significantly outperforms the existing scheduling methods in the literature. In addition, the proposed method is quite fast. In fact, the simulation time to find a complete schedule with over 2000 jobs on ten machines is less than 1.5 min.
Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.
This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for machine tool operation/machine shop I and II. Presented first are a…
Institute of Scientific and Technical Information of China (English)
李俊芳; 李铁克; 屈国强
2011-01-01
分析并行机Job-Shop调度问题的特点并建立其约束满足优化模型,结合约束满足与变邻域搜索技术设计了一个求解该问题的混合优化算法.该算法采用变量排序方法和值排序方法选择变量并赋值,利用回溯和约束传播消解资源冲突,生成初始可行调度,然后应用局部搜索技术增强收敛性,并通过结合问题特点设计的邻域结构的多样性提高求解质量.数据实验表明,提出的算法与其他两种算法相比,具有一定的可行性和有效性.%Analyzed the Job-Shop scheduling problem with parallel machines and established its constraint satisfaction optimization model. Proposed a hybrid optimization algorithm combined with constraint satisfaction and variable neighborhood search technique. In the algorithm, chosen a variable and assigned by variable ordering and value ordering method. Resolved resource conflicts using backtracking and obtained constraint propagation technology until a feasible schedule. Then the feasible schedule acted as an initial solution of the variable neighborhood search algorithm. Enhanced the convergence through local search technology and improved the quality of solution through the diversity of the designed neighborhood structures according to the characteristics of the problem. The feasibility and validity of the proposed hybrid method is demonstrated by the data experiment compared with the other two algorithms.
Production Machine Shop Employment Competencies. Part One: Practices and Principles.
Bishart, Gus; Werner, Claire
Competencies for production machine shop are provided for the first of four topic areas: principles and practice of machine shop. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment,…
Impact of Personnel Flexibility on Job Shop Scheduling
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Ren Lin
2016-01-01
Full Text Available Considering the lack of the research on the relationship between HR flexibility and scheduling effect, a resource-competency matrix-based method was proposed in order to reveal the quantitative relationship between them. Meanwhile, a job shop scheduling model with HR flexibility was established and the improved genetic algorithm was used to solve the model. A case analysis demonstrated significant impact of HR flexibility on the scheduling effect, which provided valuable guidance for building flexible manufacturing systems.
A Modified Biogeography-Based Optimization for the Flexible Job Shop Scheduling Problem
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Yuzhen Yang
2015-01-01
Full Text Available The flexible job shop scheduling problem (FJSSP is a practical extension of classical job shop scheduling problem that is known to be NP-hard. In this paper, an effective modified biogeography-based optimization (MBBO algorithm with machine-based shifting is proposed to solve FJSSP with makespan minimization. The MBBO attaches great importance to the balance between exploration and exploitation. At the initialization stage, different strategies which correspond to two-vector representation are proposed to generate the initial habitats. At global phase, different migration and mutation operators are properly designed. At local phase, a machine-based shifting decoding strategy and a local search based on insertion to the habitat with best makespan are introduced to enhance the exploitation ability. A series of experiments on two well-known benchmark instances are performed. The comparisons between MBBO and other famous algorithms as well as BBO variants prove the effectiveness and efficiency of MBBO in solving FJSSP.
Heuristics methods for the flow shop scheduling problem with separated setup times
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Marcelo Seido Nagano
2012-06-01
Full Text Available This paper deals with the permutation flow shop scheduling problem with separated machine setup times. As a result of an investigation on the problem characteristics, four heuristics methods are proposed with procedures of the construction sequencing solution by an analogy with the asymmetric traveling salesman problem with the objective of minimizing makespan. Experimental results show that one of the new heuristics methods proposed provide high quality solutions in comparisons with the evaluated methods considered in the literature.
Study on disruption management scheduling problem of flow shop under supply chain environment
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Bo Hong Guang
2016-01-01
Full Text Available This paper presents a disruption scheduling model for an environment of proportional two-machine no-wait flow shop. To achieve the objects of minimization of weighted sum of makespan and minimization of weighted sum of tardiness, we introduce a revised PSO algorithm which is designed with a neighborhood search structure. According to the experiment, the effectivity of the method proposed is proven.
A COMBINATORIAL PROPERTY OF PALLET-CONSTRAINED TWO MACHINE FLOW SHOP PROBLEM IN MINIMIZING MAKESPAN
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HOU Sixiang; Han Hoogeveen; Petra Schuurman
2002-01-01
We consider the problem of scheduling n jobs in a pallet-constrained flowshop so as to minimize the makespan. In such a flow shop environment, each job needs apallet the entire time, from the start of its first operation until the completion of the lastoperation, and the number of pallets in the shop at any given time is limited by a positiveinteger K ≤ n. Generally speaking, the optimal schedules may be passing schedules. In thispaper, we present a combinatorial property which shows that for two machines, K(K ≥ 3)pallets, there exists a no-passing schedule which is an optimal schedule for n ≤ 2K - 1 and2K - 1 is tight.
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M. Saravanan
2014-03-01
Full Text Available A Hybrid flow shop scheduling is characterized ‘n’ jobs ‘m’ machines with ‘M’ stages by unidirectional flow of work with a variety of jobs being processed sequentially in a single-pass manner. The paper addresses the multi-stage hybrid flow shop scheduling problems with missing operations. It occurs in many practical situations such as stainless steel manufacturing company. The essential complexity of the problem necessitates the application of meta-heuristics to solve hybrid flow shop scheduling. The proposed Simulated Annealing algorithm (SA compared with Particle Swarm Optimization (PSO with the objective of minimization of makespan. It is show that the SA algorithm is efficient in finding out good quality solutions for the hybrid flow shop problems with missing operations.
Flow-shop scheduling problem under uncertainties: Review and trends
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Eliana María González-Neira
2017-03-01
Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.
Machine scheduling with resource dependent processing times
Grigoriev, A.; Sviridenko, M.; Uetz, Marc Jochen
We consider machine scheduling on unrelated parallel machines with the objective to minimize the schedule makespan. We assume that, in addition to its machine dependence, the processing time of any job is dependent on the usage of a discrete renewable resource, e.g. workers. A given amount of that
APPLYING PARTICLE SWARM OPTIMIZATION TO JOB-SHOP SCHEDULING PROBLEM
Institute of Scientific and Technical Information of China (English)
Xia Weijun; Wu Zhiming; Zhang Wei; Yang Genke
2004-01-01
A new heuristic algorithm is proposed for the problem of finding the minimum makespan in the job-shop scheduling problem. The new algorithm is based on the principles of particle swarm optimization (PSO). PSO employs a collaborative population-based search, which is inspired by the social behavior of bird flocking. It combines local search (by self experience) and global search (by neighboring experience), possessing high search efficiency. Simulated annealing (SA) employs certain probability to avoid becoming trapped in a local optimum and the search process can be controlled by the cooling schedule. By reasonably combining these two different search algorithms, a general, fast and easily implemented hybrid optimization algorithm, named HPSO, is developed. The effectiveness and efficiency of the proposed PSO-based algorithm are demonstrated by applying it to some benchmark job-shop scheduling problems and comparing results with other algorithms in literature. Comparing results indicate that PSO-based algorithm is a viable and effective approach for the job-shop scheduling problem.
An improved Genetic Algorithm of Bi-level Coding for Flexible Job Shop Scheduling Problems
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Ye Li
2014-07-01
Full Text Available The current study presents an improved genetic algorithm(GA for the flexible job shop scheduling problem (FJSP. The coding is divided into working sequence level and machine level and two effective crossover operators and mutation operators are designed for the generation and reduce the disruptive effects of genetic operators. The algorithm is tested on instances of 10 working sequences and 10 machines. Computational results show that the proposed GA was successfully and efficiently applied to the FJSP. The results were compared with other approaches, such as traditional GA and GA with neural network. Compared to traditional genetic algorithm, the proposed approach yields significant improvement in solution quality.
MULTICRITERIA HYBRID FLOW SHOP SCHEDULING PROBLEM: LITERATURE REVIEW, ANALYSIS, AND FUTURE RESEARCH
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Marcia de Fatima Morais
2014-12-01
Full Text Available This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future research on this topic, including the following: (i use uniform and dedicated parallel machines, (ii use exact and metaheuristics approaches, (iv develop lower and uppers bounds, relations of dominance and different search strategies to improve the computational time of the exact methods, (v develop other types of metaheuristic, (vi work with anticipatory setups, and (vii add constraints faced by the production systems itself.
Flow shop scheduling algorithm to optimize warehouse activities
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P. Centobelli
2016-01-01
Full Text Available Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.
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Thamilselvan Rakkiannan
2012-01-01
Full Text Available Problem statement: The Job Shop Scheduling Problem (JSSP is observed as one of the most difficult NP-hard, combinatorial problem. The problem consists of determining the most efficient schedule for jobs that are processed on several machines. Approach: In this study Genetic Algorithm (GA is integrated with the parallel version of Simulated Annealing Algorithm (SA is applied to the job shop scheduling problem. The proposed algorithm is implemented in a distributed environment using Remote Method Invocation concept. The new genetic operator and a parallel simulated annealing algorithm are developed for solving job shop scheduling. Results: The implementation is done successfully to examine the convergence and effectiveness of the proposed hybrid algorithm. The JSS problems tested with very well-known benchmark problems, which are considered to measure the quality of proposed system. Conclusion/Recommendations: The empirical results show that the proposed genetic algorithm with simulated annealing is quite successful to achieve better solution than the individual genetic or simulated annealing algorithm."
Institute of Scientific and Technical Information of China (English)
HE Yan; LIU Fei; CAO Hua-jun; LI Cong-bo
2005-01-01
The issue of reducing energy consumption for the job-shop scheduling problem in machining systems is addressed, whose dual objectives are to minimize both the energy consumption and the makespan. First, the biobjective model for the job-shop scheduling problem is proposed. The objective function value of the model represents synthesized optimization of energy consumption and makespan. Then, a heuristic algorithm is developed to locate the optimal or near optimal solutions of the model based on the Tabu search mechanism. Finally, the experimental case is presented to demonstrate the effectiveness of the proposed model and the algorithm.
Study on multi-objective flexible job-shop scheduling problem considering energy consumption
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Zengqiang Jiang
2014-06-01
Full Text Available Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II based on blood variation for above scheduling model.Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model.Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption.Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.
A hybrid algorithm for flexible job-shop scheduling problem with setup times
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Ameni Azzouz
2017-01-01
Full Text Available Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper addresses the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a hybrid algorithm based on genetic algorithm (GA and variable neighbourhood search (VNS to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our algorithm against the available ones in terms of solution quality.
Application of Tabu Search Algorithm in Job Shop Scheduling
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Betrianis Betrianis
2010-10-01
Full Text Available Tabu Search is one of local search methods which is used to solve the combinatorial optimization problem. This method aimed is to make the searching process of the best solution in a complex combinatorial optimization problem(np hard, ex : job shop scheduling problem, became more effective, in a less computational time but with no guarantee to optimum solution.In this paper, tabu search is used to solve the job shop scheduling problem consists of 3 (three cases, which is ordering package of September, October and November with objective of minimizing makespan (Cmax. For each ordering package, there is a combination for initial solution and tabu list length. These result then compared with 4 (four other methods using basic dispatching rules such as Shortest Processing Time (SPT, Earliest Due Date (EDD, Most Work Remaining (MWKR dan First Come First Served (FCFS. Scheduling used Tabu Search Algorithm is sensitive for variables changes and gives makespan shorter than scheduling used by other four methods.
Flow Shop Scheduling using Differential Evolution of CRM
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Zuzana Čičková
2010-12-01
Full Text Available The article is focused on the application of differential evolution for solving flow shop problem that belongs to the class of scheduling problems. The scheduling problems arise in diverse areas such as manufacturing systems, production planning, computer design, logistics etc.. Only in very special cases there exist exact polynomial algorithms to reach optimal solution. In most of the other cases, its computational complexity is NP-hard and it seems to be desirable to employ some heuristics to solve it. Nowadays, the use of some methods that are based on metaheuristics is a popular way. One of them is a differential evolution, which belongs to the class of evolutionary techniques. The application of evolutionary algorithms to NP-hard problems generally requires a special modification of these algorithms; therefore the main object of the work is to adapt a canonical version of differential evolution for solving flow shop problem. The effectiveness of the proposed approach is compared with other evolutionary techniques known from the already published results. The available instance of flow shop Car and Rec are used for comparison.
Simultaneous scheduling of machines and mobile robots
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa
2013-01-01
This paper deals with the problem of simultaneously scheduling machines and a number of autonomous mobile robots in a flexible manufacturing system (FMS). Besides capability of transporting materials between machines, the considered mobile robots are different from other material handling devices...... in terms of their advanced ability to perform tasks at machines by using their manipulation arms. The mobile robots thus have to be scheduled in relation to scheduling of machines so as to increase the efficiency of the overall system. The performance criterion is to minimize time required to complete all...
Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.
2016-08-01
In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.
Critical Machine Based Scheduling -A Review
Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.
2017-03-01
This article aims to identify the natural occurrence of the critical machines in scheduling. The exciting scheduling in the real time manufacturing environment is focused on considering equal weight-age of all the machines, but very few researchers were considered the real time constraint(s) like processor/ machine/ workstation availability, etc.,. This article explores the gap between the theory and practices by identifying the critical machine in scheduling and helps the researcher to find the suitable problem in their case study environment. Through the literature survey, it is evident that, in scheduling the occurrence of the critical machine is in nature. The critical machine is found in various names and gives a various range of weight-age based on the particular manufacturing environment and it plays a vital role in scheduling which includes one or more circumstances of occurrence in the production environment. Very few researchers were reported that in manufacturing environment, the critical machine occurrence is in nature, but most of the researchers were focused to optimize the manufacturing environment by only reducing the cycle time. In real-time manufacturing environment, the scheduling of critical machine(s) was keenly monitored and some weight-age was considered.
Paksi, A. B. N.; Ma'ruf, A.
2016-02-01
In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.
Analysis of dispatching rules application on scheduling problem in flexible-flow shop production
Directory of Open Access Journals (Sweden)
Rakićević Zoran M.
2014-01-01
Full Text Available In this paper we analyzed a group of simple heuristic methods, which are used for solving the scheduling problem in manufacturing and services. The analysis was performed on the scheduling problem in a flexible-flow shop production, which is known by the English term - Flexible-Flow Shop (FFS. The task is to determine the schedule of processing multiple products on multiple machines, where all the products have the same sequence of processing and for each process there are multiple machines available. For this FFS problem we present the corresponding mathematical model of mixed integer programming. Among potential methods for solving the set task, we consider simple heuristics because the original scheduling problem is NP-hard and finding the exact optimal solution would require unacceptably long computing time. Heuristic methods are based on priority rules that are performed based on the relations of importance between products and their processing time on individual machines. Heuristic methods are widely used for solving practical problems, which was the motivation for the analysis performed in this paper. The aim of the analysis is to identify those priority rules, from a set of considered, which provide a good solution to a hypothetical scheduling problem example, where the evaluation of solution is performed using different criteria functions. The analysis that is presented in the paper was obtained by using the computer program LEKIN. The main results of the analysis indicated that priority rules give different solutions to the problem of FFS and that each of these solutions is a significantly good result in terms of some of the considered criteria functions.
A Genetic Algorithm Approach for Solving a Flexible Job ShopScheduling Problem
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Sayedmohammadreza Vaghefinezhad
2012-05-01
Full Text Available Flexible job shop scheduling has been noticed as an effective manufacturing system to cope with rapid development in todays competitive environment. Flexible job shop scheduling problem (FJSSP is known as a NP-hard in the field of the optimization problem. Assuming the dynamic state of the real world, make these problems more and more complicated. Most studies in the field of FJSSP have only focused on minimizing the total makespan. In this paper, a mathematical model for FJSSP has been developed. The objective function is maximizing the total profit while meeting some constraints. Considering time-varying raw material and selling price and dissimilar demand for each period, are attempts that have been done to decrease gaps between reality and the model. A manufacturer that produces various parts of gas valves has been used as a case study. The scheduling problem for multi part, multi period, and multi operation with parallel machines has been solved by genetic algorithm (GA. The best obtained answer determines the economic amount of production by different machines that belong to predefined operations for each part to satisfy customer demand in each period.
Parallel Branch-and-Bound Methods for the Job Shop Scheduling
DEFF Research Database (Denmark)
Clausen, Jens; Perregaard, Michael
1998-01-01
Job-shop scheduling (JSS) problems are among the more difficult to solve in the class of NP-complete problems. The only successful approach has been branch-and-bound based algorithms, but such algorithms depend heavily on good bound functions. Much work has been done to identify such functions...... for the JSS problem, but with limited success. Even with recent methods, it is still not possible to solve problems substantially larger than 10 machines and 10 jobs. In the current study, we focus on parallel methods for solving JSS problems. We implement two different parallel branch-and-bound algorithms...
Optimal Research and Numerical Simulation for Scheduling No-Wait Flow Shop in Steel Production
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Huawei Yuan
2013-01-01
Full Text Available This paper considers the m-machine flow shop scheduling problem with the no-wait constraint to minimize total completion time which is the typical model in steel production. First, the asymptotic optimality of the Shortest Processing Time (SPT first rule is proven for this problem. To further evaluate the performance of the algorithm, a new lower bound with performance guarantee is designed. At the end of the paper, numerical simulations show the effectiveness of the proposed algorithm and lower bound.
Parallel Machine Scheduling with Special Jobs
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper considers parallel machine scheduling with special jobs. Normal jobs can be processed on any of the parallel machines, while the special jobs can only be processed on one machine. The problem is analyzed for various manufacturing conditions and service requirements. The off-line scheduling problem is transformed into a classical parallel machine scheduling problem. The on-line scheduling uses the FCFS (first come, first served), SWSC (special window for special customers), and FFFS (first fit, first served) algorithms to satisfy the various requirements. Furthermore, this paper proves that FCFS has a competitive ratio of m, where m is the number of parallel machines, and this bound is asymptotically tight, SWSC has a competitive ratio of 2 and FFFS has a competitive ratio of , and these bounds are tight.
Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems
Institute of Scientific and Technical Information of China (English)
Jin-hui Yang; Liang Sun; Heow Pueh Lee; Yun Qian; Yan-chun Liang
2008-01-01
A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki's neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.
Hybrid Multi-Objective Particle Swarm Optimization for Flexible Job Shop Scheduling Problem
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S. V. Kamble
2015-03-01
Full Text Available Hybrid algorithm based on Particle Swarm Optimization (PSO and Simulated annealing (SA is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hybrid algorithm combines the high global search efficiency of PSO with the powerful ability to avoid being trapped in local minimum of SA. A hybrid multi-objective PSO (MPSO and SA algorithm is proposed to identify an approximation of the pareto front for Flexible job shop scheduling (FJSSP. Pareto front and crowding distance is used for identify the fitness of particle. MPSO is significant to global search and SA used to local search. The proposed MPSO algorithm is experimentally applied on two benchmark data set. The result shows that the proposed algorithm is better in term quality of non-dominated solution compared to the other algorithms in the literature.
Directory of Open Access Journals (Sweden)
MUSSA I. MGWATU
2013-08-01
Full Text Available Numerical control (NC machines in a job shop may not be cost and time effective if the assignment of cutting operations and optimisation of machining parameters are overlooked. In order to justify better utilisation and higher productivity of invested NC machine tools, it is necessary to determine the optimum machining parameters and realize effective assignment of cutting operations on machines. This paper presents two mathematical models for optimising machining parameters and effectively allocating turning operations on NC lathe machines in a job shop manufacturing system. The models are developed as non-linear programming problems and solved using a commercial LINGO software package. The results show that the decisions of machining optimisation and operation allocation on NC lathe machines can be simultaneously made while minimising both production cost and cycle time. In addition, the results indicate that production cost and cycle time can be minimised while significantly reducing or totally eliminating idle times among machines.
Performance comparison of some evolutionary algorithms on job shop scheduling problems
Mishra, S. K.; Rao, C. S. P.
2016-09-01
Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.
Production Machine Shop Employment Competencies. Part Three: The Engine Lathe.
Bishart, Gus; Werner, Claire
Competencies for production machine shop are provided for the third of four topic areas: the engine lathe. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment, will establish…
Assignment Book in Print Reading for Machine Shop.
Texas A and M Univ., College Station. Vocational Instructional Services.
This student assignment book is designed for use in a course on print reading as applied to the machine shop course. Introductory materials include a student progress record, a list of references, and a pretest. For each of eight lessons, information sheets with one or more assignment sheets and a test are provided. The lessons cover the role of…
Job-shop Scheduling with Multi-objectives Based on Genetic Algorithms
Institute of Scientific and Technical Information of China (English)
周亚勤; 李蓓智; 陈革
2003-01-01
The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special class of NP-hard problems. Most of the algorithms used to optimize this class of problems have an exponential time; that is, the computation time increases exponentially with problem size. In scheduling study, makespan is often considered as the main objective. In this paper, makespan, the due date request of the key jobs, the availability of the key machine, the average wait-time of the jobs, and the similarities between the jobs and so on are taken into accotmt based on the application of mechanical engineering. The job shop scheduling problem with multi-objectives is analyzed and studied by using genetic algorithms based on the mechanics of genetics and natural selection. In this research, the tactics of the coding and decoding and the design of the genetic operators, along with the description of the mathematic model of the multi-objective functions,are presented. Finally an illu-strative example is given to testify the validity of this algorithm.
Overlap Algorithms in Flexible Job-shop Scheduling
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Celia Gutierrez
2014-06-01
Full Text Available The flexible Job-shop Scheduling Problem (fJSP considers the execution of jobs by a set of candidate resources while satisfying time and technological constraints. This work, that follows the hierarchical architecture, is based on an algorithm where each objective (resource allocation, start-time assignment is solved by a genetic algorithm (GA that optimizes a particular fitness function, and enhances the results by the execution of a set of heuristics that evaluate and repair each scheduling constraint on each operation. The aim of this work is to analyze the impact of some algorithmic features of the overlap constraint heuristics, in order to achieve the objectives at a highest degree. To demonstrate the efficiency of this approach, experimentation has been performed and compared with similar cases, tuning the GA parameters correctly.
Scheduling Algorithm to Optimize Jobs in Shop Floor
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T. Hemamalini
2010-01-01
Full Text Available Problem statement: The ratio scheduling algorithm to solve the allocation of jobs in the shop floor was proposed. The problem was to find an optimal schedule so as to minimize the maximum completion time, the sum of distinct earliness and tardiness penalties from a given common due date d. Approach: The objective of the proposed algorithm was to reduce the early penalty and the late penalty and to increase the overall profit of the organization. The proposed method was discussed with different possible instances. Results: The test results showed that the algorithm was robust and simple and can be applied for any job size problem. Conclusion: The proposed algorithm gave encouraging result for the bench mark instances when the due date is less than half of the total processing time.
Extended precedence preservative crossover for job shop scheduling problems
Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd
2013-04-01
Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A modified bottleneck-based (MB) heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested,which is simpler but more tailored than the shifting bottleneck (SB) procedure.In this algorithm,the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules.Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems.Furthermore,it can obtain a good solution in a short time for large-scale job-shop scheduling problems.
Directory of Open Access Journals (Sweden)
Salazar-Hornig E.
2013-01-01
Full Text Available A genetic algorithm for the parallel shop with identical machines scheduling problem with sequence dependent setup times and makespan (Cmáx minimization is presented. The genetic algorithm is compared with other heuristic methods using a randomly generated test problem set. A local improvement procedure in the evolutionary process of the genetic algorithm is introduced, which significantly improves its performance.
The integration of process planning and shop floor scheduling in small batch part manufacturing
Zijm, Willem H.M.; Kals, H.J.J.
1995-01-01
In this paper we explore possibilities to cut manufacturing leadtimes and to improve delivery performance in a small batch part manufacturing shop by integrating process planning and shop floor scheduling. Using a set of initial process plans (one for each order in the shop), we exploit a resource
Scheduling identical jobs on uniform parallel machines
M. Dessouky (Mohamed); B. Lageweg (Ben); J.K. Lenstra; S.L. van de Velde (Steef)
1990-01-01
textabstractWe address the problem of scheduling n identical jobs on m uniform parallel machines to optimize scheduling criteria that are nondecreasing in the job completion times. It is well known that this can be formulated as a linear assignment problem, and subsequently solved in O(n3) time. We
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Qianwang Deng
2017-01-01
Full Text Available Flexible job-shop scheduling problem (FJSP is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II for multiobjective FJSP (MO-FJSP with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N, in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed.
Deng, Qianwang; Gong, Guiliang; Gong, Xuran; Zhang, Like; Liu, Wei; Ren, Qinghua
2017-01-01
Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N, in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed.
Machine Shop. Module 6: Milling. Instructor's Guide.
Walden, Charles H.
This document consists of materials for a 12-unit course on the following topics: (1) introduction to milling; (2) structure and accessories; (3) safety and maintenance; (4) cutting-tool variables; (5) basic set-up activities; (6) squaring a workpiece; (7) hole-making operations; (8) form milling; (9) machining keyways; (10) milling angular…
Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements
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Kalinowski Krzysztof
2017-01-01
Full Text Available The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.. Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.
Directory of Open Access Journals (Sweden)
Lei Wang
2017-01-01
Full Text Available In real-world manufacturing systems, production scheduling systems are often implemented under random or dynamic events like machine failure, unexpected processing times, stochastic arrival of the urgent orders, cancellation of the orders, and so on. These dynamic events will lead the initial scheduling scheme to be nonoptimal and/or infeasible. Hence, appropriate dynamic rescheduling approaches are needed to overcome the dynamic events. In this paper, we propose a dynamic rescheduling method based on variable interval rescheduling strategy (VIRS to deal with the dynamic flexible job shop scheduling problem considering machine failure, urgent job arrival, and job damage as disruptions. On the other hand, an improved genetic algorithm (GA is proposed for minimizing makespan. In our improved GA, a mix of random initialization population by combining initialization machine and initialization operation with random initialization is designed for generating high-quality initial population. In addition, the elitist strategy (ES and improved population diversity strategy (IPDS are used to avoid falling into the local optimal solution. Experimental results for static and several dynamic events in the FJSP show that our method is feasible and effective.
Simultaneous scheduling of machines and mobile robots
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa
2013-01-01
This paper deals with the problem of simultaneously scheduling machines and a number of autonomous mobile robots in a flexible manufacturing system (FMS). Besides capability of transporting materials between machines, the considered mobile robots are different from other material handling devices...... in terms of their advanced ability to perform tasks at machines by using their manipulation arms. The mobile robots thus have to be scheduled in relation to scheduling of machines so as to increase the efficiency of the overall system. The performance criterion is to minimize time required to complete all...... tasks or makespan. A heuristic based on genetic algorithm is developed to find the best solution for the problem. A numerical example is investigated to demonstrate results of the proposed approach. The implementation of the proposed approach in a multi-agent system is also generally described....
Directory of Open Access Journals (Sweden)
Souad Mekni
2014-11-01
Full Text Available In this paper, a modified invasive weed optimization (IWO algorithm is presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs with the criteria to minimize the maximum completion time (makespan, the total workload of machines and the workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour of weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solve continuous optimization problems that’s why the heuristic rule the Smallest Position Value (SPV is used to convert the continuous position values to the discrete job sequences. The computational experiments show that the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it is able to find the optimal and best-known solutions on the instances studied.
A heuristic algorithm for scheduling in a flow shop environment to minimize makespan
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Arun Gupta
2015-04-01
Full Text Available Scheduling ‘n’ jobs on ‘m’ machines in a flow shop is NP- hard problem and places itself at prominent place in the area of production scheduling. The essence of any scheduling algorithm is to minimize the makespan in a flowshop environment. In this paper an attempt has been made to develop a heuristic algorithm, based on the reduced weightage of ma-chines at each stage to generate different combination of ‘m-1’ sequences. The proposed heuristic has been tested on several benchmark problems of Taillard (1993 [Taillard, E. (1993. Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285.]. The performance of the proposed heuristic is compared with three well-known heuristics, namely Palmer’s heuristic, Campbell’s CDS heuristic, and Dannenbring’s rapid access heuristic. Results are evaluated with the best-known upper-bound solutions and found better than the above three.
Performance analysis of active schedules in identical parallel machine
Institute of Scientific and Technical Information of China (English)
Changjun WANG; Yugeng XI
2007-01-01
Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs' dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.
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Yahong Zheng
2014-05-01
Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.
A Hybrid Bacterial Foraging Algorithm For Solving Job Shop Scheduling Problems
Narendhar, S.; T Amudha
2012-01-01
Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by proposed Hybrid Bacterial Foraging Optimization algorithms are much better when compared with the solution...
Optimizing a multi-objectives flow shop scheduling problem by a novel genetic algorithm
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R. Tavakkoli-Moghaddam
2013-06-01
Full Text Available Flow-shop problems, as a typical manufacturing challenge, have become an interesting area of research. The primary concern is that the solution space is huge and, therefore, the set of feasible solutions cannot be enumerated one by one. In this paper, we present an efficient solution strategy based on a genetic algorithm (GA to minimize the makespan, total waiting time and total tardiness in a flow shop consisting of n jobs and m machines. The primary objective is to minimize the job waiting time before performing the related operations. This is a major concern for some industries such as food and chemical for planning and production scheduling. In these industries, there is a probability of the decay and deterioration of the products prior to accomplishment of operations in workstation, due to the increase in the waiting time. We develop a model for a flowshop scheduling problem, which uses the planner-specified weights for handling a multi-objective optimization problem. These weights represent the priority of planning objectives given by managers. The results of the proposed GA and classic GA are analyzed by the analysis of variance (ANOVA method and the results are discussed.
Scheduling and Subcontracting under Parallel Machines
Institute of Scientific and Technical Information of China (English)
CHEN Rong-jun; TANG Guo-chun
2012-01-01
In this paper,we study a model on joint decisions of scheduling and subcontracting,in which jobs(orders) can be either processed by parallel machines at the manufacturer in-house or subcontracted to a subcontractor.The manufacturer needs to determine which jobs should be produced in-house and which jobs should be subcontracted.Furthermore,it needs to determine a production schedule for jobs to be produced in-house.We discuss five classical scheduling objectives as production costs.For each problem with different objective functions,we give optimality conditions and propose dynamic programming algorithms.
An Improved Shuffled Frog-Leaping Algorithm for Flexible Job Shop Scheduling Problem
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Kong Lu
2015-02-01
Full Text Available The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the proposed algorithm has a powerful search capability in solving the flexible job shop scheduling problem compared with other heuristic algorithms, such as the genetic algorithm, tabu search and ant colony optimization. Moreover, the results also show that the improved strategies could improve the performance of the algorithm effectively.
Directory of Open Access Journals (Sweden)
Seyyed Mohammad Hassan Hosseini
2016-05-01
Full Text Available Scheduling problem for the hybrid flow shop scheduling problem (HFSP followed by an assembly stage considering aging effects additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at the same time. The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan. A mathematical modeling is presented and its validation is shown by solving an example in small scale. Since this problem has been proved strongly NP-hard, in order to solve the problem in medium and large scale, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms.
Scheduling Unrelated Machines of Few Different Types
Bonifaci, Vincenzo
2012-01-01
A very well-known machine model in scheduling allows the machines to be unrelated, modelling jobs that might have different characteristics on each machine. Due to its generality, many optimization problems of this form are very difficult to tackle and typically APX-hard. However, in many applications the number of different types of machines, such as processor cores, GPUs, etc. is very limited. In this paper, we address this point and study the assignment of jobs to unrelated machines in the case that each machine belongs to one of a fixed number of types and the machines of each type are identical. We present polynomial time approximation schemes (PTASs) for minimizing the makespan for multidimensional jobs with a fixed number of dimensions and for minimizing the L_p-norm. In particular, our results subsume and generalize the existing PTASs for a constant number of unrelated machines and for an arbitrary number of identical machines for these problems. We employ a number of techniques which go beyond the pr...
Design and fabrication of metal briquette machine for shop floor
Pramod, R.; Kumar, G. B. Veeresh; Prashanth B., N.
2017-07-01
Efforts have to be taken to ensure efficient waste management system in shop floors, with minimum utilization of space and energy when it comes to disposing metal chips formed during machining processes. The salvaging of junk metallic chips and the us e of scrap are important for the economic production of a steelworks. For this purpose, we have fabricated a metal chip compaction machine, which can compact the metal chips into small briquettes. The project started with the survey of chips formed in shop floors and the practices involved in waste management. Study was done on the requirements for a better compaction. The heating chamber was designed taking into consideration the temperature required for an easy compaction of the metal chips. The power source for compaction and the pneumatic design for mechanism was done following the appropriate calculations regarding the air pressure provided and thrust required. The processes were tested under different conditions and found effective. The fabrication of the machine has been explained in detail and the results have been discussed.
Emergency local searching approach for job shop scheduling
Zhao, Ning; Chen, Siyu; Du, Yanhua
2013-09-01
Existing methods of local search mostly focus on how to reach optimal solution. However, in some emergency situations, search time is the hard constraint for job shop scheduling problem while optimal solution is not necessary. In this situation, the existing method of local search is not fast enough. This paper presents an emergency local search(ELS) approach which can reach feasible and nearly optimal solution in limited search time. The ELS approach is desirable for the aforementioned emergency situations where search time is limited and a nearly optimal solution is sufficient, which consists of three phases. Firstly, in order to reach a feasible and nearly optimal solution, infeasible solutions are repaired and a repair technique named group repair is proposed. Secondly, in order to save time, the amount of local search moves need to be reduced and this is achieved by a quickly search method named critical path search(CPS). Finally, CPS sometimes stops at a solution far from the optimal one. In order to jump out the search dilemma of CPS, a jump technique based on critical part is used to improve CPS. Furthermore, the schedule system based on ELS has been developed and experiments based on this system completed on the computer of Intel Pentium(R) 2.93 GHz. The experimental result shows that the optimal solutions of small scale instances are reached in 2 s, and the nearly optimal solutions of large scale instances are reached in 4 s. The proposed ELS approach can stably reach nearly optimal solutions with manageable search time, and can be applied on some emergency situations.
Local Search Algorithm with Hybrid Neighborhood and Its Application to Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
黄文奇; 曾立平
2004-01-01
A new local search method with hybrid neighborhood for Job shop scheduling problem is developed. The proposed hybrid neighborhood is not only efficient in local search, but also can help overcome entrapments while search procedure get trapped at local optima and carry the search to areas of the feasible set with better prospect. New strategies used for breaking out of entrapments are presented and they are helpful for the procedure to improve local optima. A performance comparison of the proposed method with some best-performing algorithms on all 10-job, 10-machine benchmark problems and the other two problems generated by Fisher and Thompson ( ie. , FT6 and FT20) is made. The experiment results show the better optimal performance of the proposed algorithm.
A NEW APPROACH TO JOB SHOP-SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
Ramezanali Mahdavinejad
2007-03-01
Full Text Available In this paper, single-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan i.e. total completion time , in which a simultanous presence of various kinds of ferons is allowed. The process of finding the best solution will be improved by using the suitable hybrid of priority dispatching rules. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. By solving some problems as samples (i.e. Fisher's & Thomson's problems, this algorithm is compared with the others. The results show that when the size of the problem becomes larger the deviation from lower limit increases, but its rate decreases with the size of the problems, so that it reaches to its limit.
No-Wait Flexible Flow Shop Scheduling with Due Windows
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Rong-Hwa Huang
2015-01-01
Full Text Available To improve capacity and reduce processing time, the flow shop with multiprocessors (FSMP system is commonly used in glass, steel, and semiconductor production. No-wait FSMP is a modern production system that responds to periods when zero work is required in process production. The production process must be continuous and uninterrupted. Setup time must also be considered. Just-in-time (JIT production is very popular in industry, and timely delivery is important to customer satisfaction. Therefore, it is essential to consider the time window constraint, which is also very complex. This study focuses on a no-wait FSMP problem with time window constraint. An improved ant colony optimization (ACO, known as ant colony optimization with flexible update (ACOFU, is developed to solve the problem. The results demonstrate that ACOFU is more effective and robust than ACO when applied to small-scale problems. ACOFU has superior solution capacity and robustness when applied to large-scale problems. Therefore, this study concludes that the proposed algorithm ACOFU performs excellently when applied to the scheduling problem discussed in this study.
Parallel machine scheduling with a common server
Energy Technology Data Exchange (ETDEWEB)
Hall, N.; Sriskandarajah, C.; Potts, C.
1994-12-31
This paper considers the nonpreemptive scheduling of a given set of jobs on several identical, parallel machines. Each job must be processed on one of the machines. Prior to processing, a job must be loaded (setup) by a single server onto the relevant machine. The server may be a human operator, a robot, or a piece of specialized equipment. We study a number of classical scheduling objectives in this environment, including makespan, maximum lateness, the sum of completion times, the number of late jobs, and total tardiness, as well as weighted versions of some of these. The number of machines may be constant or arbitrary. Setup times may be unit, equal, or arbitrary. Processing times may be unit or arbitrary. For each problem considered, we attempt to provide either an efficient algorithm, or a proof that such an algorithm is unlikely to exist. Our results provide a mapping of the computational complexity of these problems. Included in these results are generalizations of the classical algorithms of Moore, Lawler and Moore and Lawler. In addition, we describe two heuristics for makespan scheduling in this environment, and provide an exact analysis of their worst-case performance.
Linear Time Algorithms for Parallel Machine Scheduling
Institute of Scientific and Technical Information of China (English)
Zhi Yi TAN; Yong HE
2007-01-01
This paper addresses linear time algorithms for parallel machine scheduling problems. We introduce a kind of threshold algorithms and discuss their main features. Three linear time threshold algorithm classes DT, PT and DTm are studied thoroughly. For all classes, we study their best possible algorithms among each class. We also present their application to several scheduling problems.The new algorithms are better than classical algorithms in time complexity and/or worst-case ratio.Computer-aided proof technique is used in the proof of main results, which greatly simplifies the proof and decreases case by case analysis.
A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time
Institute of Scientific and Technical Information of China (English)
NIU Qun; GU Xing-sheng
2008-01-01
Since in most practical cases the processing time of scheduling is not deterministic,flow shop scheduling model with fuzzy processing time is established.It is assumed that the processing times of jobs on the machines are described by triangular fuzzy sets.In order to find a sequence that minimizes the mean makespan and the spread of the makespan,Lee and Li fuzzy ranking method is adopted and modified to solve the problem.Particle swarm optimization (PSO) is a population-based stochyastic appmxilmtion aigorithm that has been applied to a wide range of problems,but there is little reported in respect of application to scheduling problems because of its unsuitability for them.In the paper,PSO is redefined and modified by introducing genetic operations such as crossover and mutation to update the particles,which is called GPSO and successfully employed to solve the formulated problem.A series of benchmarks with fuzzy processing time are used to verify GPSO.Extensive experiments show the feasibility and effectiveness of the proposed method.
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Hong-an Yang
2014-01-01
Full Text Available We focus on solving Stochastic Job Shop Scheduling Problem (SJSSP with random processing time to minimize the expected sum of earliness and tardiness costs of all jobs. To further enhance the efficiency of the simulation optimization technique of embedding Evolutionary Strategy in Ordinal Optimization (ESOO which is based on Monte Carlo simulation, we embed Optimal Computing Budget Allocation (OCBA technique into the exploration stage of ESOO to optimize the performance evaluation process by controlling the allocation of simulation times. However, while pursuing a good set of schedules, “super individuals,” which can absorb most of the given computation while others hardly get any simulation budget, may emerge according to the allocating equation of OCBA. Consequently, the schedules cannot be evaluated exactly, and thus the probability of correct selection (PCS tends to be low. Therefore, we modify OCBA to balance the computation allocation: (1 set a threshold of simulation times to detect “super individuals” and (2 follow an exclusion mechanism to marginalize them. Finally, the proposed approach is applied to an SJSSP comprising 8 jobs on 8 machines with random processing time in truncated normal, uniform, and exponential distributions, respectively. The results demonstrate that our method outperforms the ESOO method by achieving better solutions.
Integrating Preventive Maintenance Planning and Production Scheduling under Reentrant Job Shop
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Ruiqiu Li
2017-01-01
Full Text Available This paper focuses on a preventive maintenance plan and production scheduling problem under reentrant Job Shop in semiconductor production. Previous researches discussed production scheduling and preventive maintenance plan independently, especially on reentrant Job Shop. Due to reentrancy, reentrant Job Shop scheduling is more complex than the standard Job Shop which belongs to NP-hard problems. Reentrancy is a typical characteristic of semiconductor production. What is more, the equipment of semiconductor production is very expensive. Equipment failure will affect the normal production plan. It is necessary to maintain it regularly. So, we establish an integrated and optimal mathematical model. In this paper, we use the hybrid particle swarm optimization algorithm to solve the problem for it is highly nonlinear and discrete. The proposed model is evaluated through some simple simulation experiments and the results show that the model works better than the independent decision-making model in terms of minimizing maximum completion time.
一种基于强化学习的作业车间动态调度方法%A Reinforcement Learning-based Approach to Dynamic Job-shop Scheduling
Institute of Scientific and Technical Information of China (English)
魏英姿; 赵明扬
2005-01-01
Production scheduling is critical to manufacturing system. Dispatching rules are usually applied dynamically to schedule the job in a dynamic job-shop. Existing scheduling approaches seldom address machine selection in the scheduling process. Composite rules, considering both machine selection andjob selection, are proposed in this paper. The dynamic system is trained to enhance its learning and adaptive capability by a reinforcement learning (RL) algorithm. We define the conception of pressure to describe the system feature. Designing a reward function should be guided by the scheduling goal to accurately record the learning progress. Competitive results with the RL-based approach show that it can be used as real-time scheduling technology.
Semi-Online Scheduling with Machine Cost
Institute of Scientific and Technical Information of China (English)
何勇; 蔡圣义
2002-01-01
For most scheduling problems the set of machines is fixed initially and remainsunchanged for the duration of the problem. Recently Imreh and Nogaproposed to add theconcept of machine cost to scheduling problems and considered the so-called List Model problem.An online algorithm with a competitive ratio 1.618 was given while the lower bound is 4/3. Inthis paper, two different semi-online versions of this problem are studied. In the first case, it isassumed that the processing time of the largest job is known a priori. A semi-online algorithmis presented with the competitive ratio at most 1.5309 while the lower bound is 4/3. In thesecond case, it is assumed that the total processing time of all jobs is known in advance. Asemi-online algorithm is presented with the competitive ratio at most 1.414 while the lowerbound is 1.161. It is shown that the additional partial available information about the jobsleads to the possibility of constructing a schedule with a smaller competitive ratio than that ofonline algorithms.
Factors Affecting the Behavior of Engineering Students toward Safety Practices in the Machine Shop
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Jessie Kristian M. Neria
2015-08-01
Full Text Available This study aimed to determine the factors that affect the behavior of engineering student toward safety practices in the machine shop. Descriptive type of research was utilized in the study. Results showed that most of the engineering students clearly understand the signage shown in the machine shop. Students are aware that they should not leave the machines unattended. Most of the engineering students handle and use the machine properly. The respondents have an average extent of safety practices in the machine shop which means that they are applying safety practices in their every activity in machine shop. There is strong relationship between the safety practices and the factors affecting behavior in terms of signage, reminder of teacher and rules and regulation.
Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng
2016-01-01
Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.
MULTIOBJECTIVE FLEXIBLE JOB SHOP SCHEDULING USING A MODIFIED INVASIVE WEED OPTIMIZATION
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Souad Mekni
2015-02-01
Full Text Available Recently, many studies are carried out with inspirations from ecological phenomena for developing optimization techniques. The new algorithm that is motivated by a common phenomenon in agriculture is colonization of invasive weeds. In this paper, a modified invasive weed optimization (IWO algorithm is presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs with the criteria to minimize the maximum completion time (makespan, the total workload of machines and the workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour of weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solve continuous optimization problems that’s why the heuristic rule the Smallest Position Value (SPV is used to convert the continuous position values to the discrete job sequences. The computational experiments show that the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it is able to find the optimal and best-known solutions on the instances studied.
Bicriteria Scheduling on Single Machine with Outsourcing
Institute of Scientific and Technical Information of China (English)
CHEN Rong-jun; QIN Li-zhen; TANG Guo-chun
2015-01-01
Scheduling with outsourcing is studied in this paper. It is assumed that both manufacturer and subcontractor have a single machine to process n jobs. The manufacturer needs to determine simultaneously a set of outsourced jobs and the schedule of the jobs in-house such that two criterias, i.e., outsourcing cost and production cost, are minimized. The production cost is measured by the number of tardy jobs or the total tardiness of jobs in-house, and the outsourcing cost is proportional to the total processing time of jobs outsourced. Two kinds of problems with different criterias are considered. We analyze the computational complexity and provide pseudo-polynomial time optimization algorithms for the NP-hard version of the problems.
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Chen Ming
2017-01-01
Full Text Available To solve the Flexible Job-shop Scheduling Problem (FJSP with different varieties and small batches, a modified meta-heuristic algorithm based on Genetic Algorithm (GA is proposed in which gene encoding is divided into process encoding and machine encoding, and according to the encoding mode, the machine gene fragment is connected with the process gene fragment and can be changed with the alteration of process genes. In order to get the global optimal solutions, the crossover and mutation operation of the process gene fragment and machine gene fragment are carried out respectively. In the initialization operation, the machines with shorter manufacturing time are more likely to be chosen to accelerate the convergence speed and then the tournament selection strategy is applied due to the minimum optimization objective. Meanwhile, a judgment condition of the crossover point quantity is introduced to speed up the population evolution and as an important interaction bridge between the current machine and alternative machines in the incidence matrix, a novel mutation operation of machine genes is proposed to achieve the replacement of manufacturing machines. The benchmark test shows the correctness of proposed algorithm and the case simulation proves the proposed algorithm has better performance compared with existing algorithms.
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Hamed Piroozfard
2016-01-01
Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.
Single machine stochastic JIT scheduling problem subject to machine breakdowns
Institute of Scientific and Technical Information of China (English)
2008-01-01
In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat.The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date.For preemptive-resume,we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem,and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions.For preemptive-repeat,the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed.We replace the ESSD problem by the SSDE problem.We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.
Single machine stochastic JIT scheduling problem subject to machine breakdowns
Institute of Scientific and Technical Information of China (English)
TANG HengYong; ZHAO ChuanLi; CHENG CongDian
2008-01-01
In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat. The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date. For preemptive-resume, we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times. And a dynamic programming algorithm with the pseudopolynomial time complexity is, given. We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem, and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions. For preemptive-repeat, the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed. We replace the ESSD problem by the SSDE problem. We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times. And a dynamic programming algorithm with the pseudopolynomial time complexity is given. A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.
Directory of Open Access Journals (Sweden)
Song Huang
2016-01-01
Full Text Available The fuzzy processing time occasionally exists in job shop scheduling problem of flexible manufacturing system. To deal with fuzzy processing time, fuzzy flexible job shop model was established in several papers and has attracted numerous researchers’ attention recently. In our research, an improved version of discrete particle swarm optimization (IDPSO is designed to solve flexible job shop scheduling problem with fuzzy processing time (FJSPF. In IDPSO, heuristic initial methods based on triangular fuzzy number are developed, and a combination of six initial methods is applied to initialize machine assignment and random method is used to initialize operation sequence. Then, some simple and effective discrete operators are employed to update particle’s position and generate new particles. In order to guide the particles effectively, we extend global best position to a set with several global best positions. Finally, experiments are designed to investigate the impact of four parameters in IDPSO by Taguchi method, and IDPSO is tested on five instances and compared with some state-of-the-art algorithms. The experimental results show that the proposed algorithm can obtain better solutions for FJSPF and is more competitive than the compared algorithms.
Duality-based algorithms for scheduling unrelated parallel machines
S.L. van de Velde (Steef)
1993-01-01
textabstractWe consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an a
Model of Production Planning and Scheduling in Shop Floor Based on Collaboration and Competition
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The planning and scheduling in real shop floor is actually achieved by coordination betweendifferent persons. in this process, cooperation is mainstream, but competition also exists, for example.,the competition between different groups, operators with the same skill, etc. In multi-agent based shopfloor management and control system, this competition and cooperation relation must be embodied. Thegeneral process of shop floor production planning and scheduling is studied, and a colored Petri-net modelfor the competition and cooperation process of three main agents in such system to achieve shop floor pro-duction planning and scheduling is presented. The evaluating method of bids in bidding process that espe-cially embodies the competition relationship is also presented. This colored Petri-net model gives a clear il-lustration of this complex coordination process to system designers, effectively promotes the cooperativedevelopment.
Tang, Dunbing; Dai, Min
2015-09-01
The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.
Institute of Scientific and Technical Information of China (English)
CHEN Yong; LIN Feilong; WANG Xiao; TANG Kefeng
2006-01-01
In this paper, the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent, process agent, testing agent, transition agent, production information agent, scheduling agent, process agent and stock agent. The scheduling agent has three subagents: manager agent (MA), resource agent (RA) and part agent (PA). MA, PA and RA are communicating equally that guarantees agility of the whole MAS system. The part tasks pass between MA, RA and PA as an integer, which can guarantee the consistency of the data. We use a detailed example about shop logistics scheduling in a semiconductor company to explain the principle. In this example, we use two scheduling strategies:FCFS and SPT. The result data indicates that the average flow time and lingering ratio are changed using different strategy. It is proves that the multi-agent scheduling is useful.
Santa Claus Schedules Jobs on Unrelated Machines
Svensson, Ola
2010-01-01
One of the classic results in scheduling theory is the 2-approximation algorithm by Lenstra, Shmoys, and Tardos for the problem of scheduling jobs to minimize makespan on unrelated machines, i.e., job j requires time p_{ij} if processed on machine i. More than two decades after its introduction it is still the algorithm of choice even in the restricted model where processing times are of the form p_{ij} in {p_j, \\infty}. This problem, also known as the restricted assignment problem, is NP-hard to approximate within a factor less than 1.5 which is also the best known lower bound for the general version. Our main result is a polynomial time algorithm that estimates the optimal makespan of the restricted assignment problem within a factor 33/17 + \\epsilon \\approx 1.9412 + \\epsilon, where \\epsilon > 0 is an arbitrary small constant. The result is obtained by upper bounding the integrality gap of a certain strong linear program, known as configuration LP, that was previously successfully used for the related Santa...
Solving Job-Shop Scheduling Problems by Genetic Algorithms Based on Building Block Hypothesis
Institute of Scientific and Technical Information of China (English)
CHENG Rong; CHEN You-ping; LI Zhi-gang
2006-01-01
In this paper, we propose a new genetic algorithm for job-shop scheduling problems(JSP). The proposed method uses the operation-based representation, based on schema theorem and building block hypothesis, a new crossover is proposed: By selecting short, low order highly fit schemas to genetic operator, the crossover can exchange meaningful ordering information of parents effectively and can search the global optimization. Simulation results on MT benchmark problem coded by C + + show that our genetic operators are very powerful and suitable to job-shop scheduling problems and our method outperforms the previous GA-based approaches.
A Dynamic Job Shop Scheduling Method Based on Ant Colony Coordination System
Institute of Scientific and Technical Information of China (English)
ZHU Qiong; WU Li-hui; ZHANG Jie
2009-01-01
Due to the stubborn nature of dynamic job shop scheduling problem, a novel ant colony coordination mechanism is proposed in this paper to search for an optimal schedule in dynamic environment. In ant colony coordination mechanism, the dynamic .job shop is composed of several autonomous ants. These ants coordinate with each other by simulating the ant foraging behavior of spreading pheromone on the trails, by which they can make information available globally, and further more guide ants make optimal decisions. The proposed mechanism is tested by several instances and the results confirm the validity of it.
A new genetic algorithm for flexible job-shop scheduling problems
Energy Technology Data Exchange (ETDEWEB)
Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia [University of Batna, Batna (Algeria)
2015-03-15
Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.
Multi-agent Optimization Design for Multi-resource Job Shop Scheduling Problems
Xue, Fan; Fan, Wei
As a practical generalization of the job shop scheduling problem, multi-resource job shop scheduling problem (MRJSSP) is discussed in this paper. In this problem, operations may be processed by a type of resources and jobs have individual deadlines. How to design and optimize this problem with DSAFO, a novel multi-agent algorithm, is introduced in detail by a case study, including problem analysis, agent role specification, and parameter selection. Experimental results show the effectiveness and efficiency of designing and optimizing MRJSSPs with multi-agent.
Machine Shop Practice, 13-2. Military Curriculum Materials for Vocational and Technical Education.
Army Ordnance Center and School, Aberdeen Proving Ground, MD.
This military-developed text consists of self-instructional materials dealing with the basic tools and equipment used in metalworking shops. Covered in the individual lessons are the following topics: materials and processes; shop mathematics; blueprint reading and sketching; handtools, measuring instruments, and basic metalworking machines;…
Energy Technology Data Exchange (ETDEWEB)
Hoogeveen, J.A.; Van de Velde, S.L.
1994-12-31
We address the problem of scheduling n jobs in a flow shop environment that consists of a batching machine with capacity c and a standard machine with capacity 1 such that total completion time is minimized. We formulate this problem as a pidgin integer programming problem by using the concept of position dependent completion times; to this formulation we apply Lagrangian relaxation to obtain a strong lower bound. We show that this lower bound dominates the bound that was obtained by Ahmadi et al. by applying Lagrangian relaxation to an ordinary formulation of this problem.
Flow-Shop Scheduling Models with Parameters Represented by Rough Variables
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
In reality, processing times are often imprecise and this imprecision is critical for the scheduling procedure. This research deals with flow-shop scheduling in rough environment. In this type of scheduling problem, we employ the rough sets to represent the job parameters. The job processing times are assumed to be rough variables, and the problem is to minimize the makespan. Three novel types of rough scheduling models are presented. A rough simulation-based genetic algorithm is designed to solve these models and its effectiveness is well illustrated by numerical experiments.
Look-Ahead Techniques for Micro-Opportunistic Job Shop Scheduling
1991-03-01
throughout all these years; My advisor, Mark Fox , for his guidance, enthusiasm and unfailing support; The other members of my thesis committee, Tom Mitchell...about the same time, the ISIS factory scheduling system developed by Mark Fox and his team first demonstrated the potential of AI modeling and...Katia Sycara, Steve Roth, and Mark Fox . LOOK-AHEAD TECHNIQUES FOR MICRO-OPPORTUNISTIC JOB SHOP SCHEDULING 155 Appendix A Counting the Number of
DEFF Research Database (Denmark)
Mathiesen, Frants; Arvedsen, Karsten
2014-01-01
Shopping behandles som fænomen og begivenhed og som konkret undervisningstilgang til Visuel Kultur......Shopping behandles som fænomen og begivenhed og som konkret undervisningstilgang til Visuel Kultur...
Institute of Scientific and Technical Information of China (English)
张宏远; 席裕庚; 谷寒雨
2005-01-01
There are many flow shop problems of throughput (denoted by FSPT) with constraints of due date in real production planning and scheduling. In this paper, a decomposition and coordination algorithm is proposed based on the analysis of FSPT and under the support of TOC (theory of constraint). A flow shop is at first decomposed into two subsystems named PULL and PUSH by means of bottleneck. Then the subsystem is decomposed into single machine scheduling problems,so the original NP-HARD problem can be transferred into a serial of single machine optimization problems finally. This method reduces the computational complexity, and has been used in a real project successfully.
An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem
Directory of Open Access Journals (Sweden)
Jianhui Mou
2014-01-01
Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.
Directory of Open Access Journals (Sweden)
Lu Lin
2009-10-01
Full Text Available Estimation of Distribution Algorithm (EDA is a new kinds of colony evolution algorithm, through counting excellent information of individuals of the present colony EDA construct probability distribution model, then sample the model produces newt generation. To solve the NP-Hard question as EDA searching optimum network structure a new Maximum Entropy Distribution Algorithm (MEEDA is provided. The algorithm takes Jaynes principle as the basis, makes use of the maximum entropy of random variables to estimate the minimum bias probability distribution of random variables, and then regard it as the evolution model of the algorithm, which produces the optimal/near optimal solution. Then this paper presents a rough programming model for job shop scheduling under uncertain information problem. The method overcomes the defects of traditional methods which need pre-set authorized characteristics or amount described attributes, designs multi-objective optimization mechanism and expands the application space of a rough set in the issue of job shop scheduling under uncertain information environment. Due to the complexity of the proposed model, traditional algorithms have low capability in producing a feasible solution. We use MEEDA in order to enable a definition of a solution within a reasonable amount of time. We assume that machine flexibility in processing operations to decrease the complexity of the proposed model. Muth and Thompson’s benchmark problems tests are used to verify and validate the proposed rough programming model and its algorithm. The computational results obtained by MEEDA are compared with GA. The compared results prove the effectiveness of MEEDA in the job shop scheduling problem under uncertain information environment.
ON-LINE PREEMPTIVE SCHEDULING ON UNIFORM MACHINES
Institute of Scientific and Technical Information of China (English)
ZHANG Yuzhong; WANG Shouyang; Bo Chen; ZHANG Shuxia
2001-01-01
We address the problem of preemptively schedule on-line jobs on arbitrary muniformly related machines with the objective of minimizing the schedule length. We provide the first on-line algorithm for this general problem, and show that the algorithm being the speeds of the m machines.
Proactive Algorithms for Job Shop Scheduling with Probabilistic Durations
Beck, J C; 10.1613/jair.2080
2011-01-01
Most classical scheduling formulations assume a fixed and known duration for each activity. In this paper, we weaken this assumption, requiring instead that each duration can be represented by an independent random variable with a known mean and variance. The best solutions are ones which have a high probability of achieving a good makespan. We first create a theoretical framework, formally showing how Monte Carlo simulation can be combined with deterministic scheduling algorithms to solve this problem. We propose an associated deterministic scheduling problem whose solution is proved, under certain conditions, to be a lower bound for the probabilistic problem. We then propose and investigate a number of techniques for solving such problems based on combinations of Monte Carlo simulation, solutions to the associated deterministic problem, and either constraint programming or tabu search. Our empirical results demonstrate that a combination of the use of the associated deterministic problem and Monte Carlo sim...
An evolutionary approach for solving the job shop scheduling problem in a service industry
Directory of Open Access Journals (Sweden)
Milad Yousefi
2015-03-01
Full Text Available In this paper, an evolutionary-based approach based on the discrete particle swarm optimization (DPSO algorithm is developed for finding the optimum schedule of a registration problem in a university. Minimizing the makespan, which is the total length of the schedule, in a real-world case study is considered as the target function. Since the selected case study has the characteristics of job shop scheduling problem (JSSP, it is categorized as a NP-hard problem which makes it difficult to be solved by conventional mathematical approaches in relatively short computation time.
Adaptive scheduling of batch servers in flow shops
van der Zee, D.J.
2002-01-01
Batch servicing is a common way of benefiting from economies of scale in manufacturing operations. Good examples of production systems that allow for batch processing are ovens found in the aircraft industry and in semiconductor manufacturing. In this paper we study the issue of dynamic scheduling o
Huang, Rong-Hwa; Yang, Chang-Lin; Hsu, Chun-Ting
2015-12-01
Flow shop production system - compared to other economically important production systems - is popular in real manufacturing environments. This study focuses on the flow shop with multiprocessor scheduling problem (FSMP), and develops an improved particle swarm optimisation heuristic to solve it. Additionally, this study designs an integer programming model to perform effectiveness and robustness testing on the proposed heuristic. Experimental results demonstrate a 10% to 50% improvement in the effectiveness of the proposed heuristic in small-scale problem tests, and a 10% to 40% improvement in the robustness of the heuristic in large-scale problem tests, indicating extremely satisfactory performance.
Directory of Open Access Journals (Sweden)
Hadi Mokhtari
2015-11-01
Full Text Available In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexible job shop scheduling with controllable processing times (FJCPT, is formulated as an integer non-linear programming (INLP model and then it is converted into an integer linear programming (ILP model. Due to NP-hardness of FJCPT, conventional analytic optimization methods are not efficient. Hence, in order to solve the problem, a Scatter Search (SS, as an efficient metaheuristic method, is developed. To show the effectiveness of the proposed method, numerical experiments are conducted. The efficiency of the proposed algorithm is compared with that of a genetic algorithm (GA available in the literature for solving FJSP problem. The results showed that the proposed SS provide better solutions than the existing GA.
Lauritzen, Louis Dee
2014-01-01
Machine shop students face the daunting task of learning the operation of complex three-dimensional machine tools, and welding students must develop specific motor skills in addition to understanding the complexity of material types and characteristics. The use of consumer technology by the Millennial generation of vocational students, the…
Lauritzen, Louis Dee
2014-01-01
Machine shop students face the daunting task of learning the operation of complex three-dimensional machine tools, and welding students must develop specific motor skills in addition to understanding the complexity of material types and characteristics. The use of consumer technology by the Millennial generation of vocational students, the…
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
Flexible job-shop scheduling based on genetic algorithm and simulation validation
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Zhou Erming
2017-01-01
Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.
Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems
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Noor Hasnah Moin
2015-01-01
Full Text Available The job shop scheduling problem (JSSP is one of the well-known hard combinatorial scheduling problems. This paper proposes a hybrid genetic algorithm with multiparents crossover for JSSP. The multiparents crossover operator known as extended precedence preservative crossover (EPPX is able to recombine more than two parents to generate a single new offspring distinguished from common crossover operators that recombine only two parents. This algorithm also embeds a schedule generation procedure to generate full-active schedule that satisfies precedence constraints in order to reduce the search space. Once a schedule is obtained, a neighborhood search is applied to exploit the search space for better solutions and to enhance the GA. This hybrid genetic algorithm is simulated on a set of benchmarks from the literatures and the results are compared with other approaches to ensure the sustainability of this algorithm in solving JSSP. The results suggest that the implementation of multiparents crossover produces competitive results.
Arakawa, Masahiro; Fuyuki, Masahiko; Inoue, Ichiro
Aiming at the elimination of tardy jobs in a job shop production schedule, an optimization-oriented simulation-based scheduling (OSBS) method incorporating capacity adjustment function is proposed. In order to determine the pertinent additional capacities and to control job allocations simultaneously the proposed method incorporates the parameter-space search improvement (PSSI) method into the scheduling procedure. In previous papers, we have introduced four parameters; two of them are used to control the upper limit to the additional capacity and the balance of the capacity distribution among machines, while the others are used to control the job allocation procedure. We found that a ‘direct' optimization procedure which uses the enumeration method produces a best solution with practical significance, but it takes too much computation time for practical use. In this paper, we propose a new method which adopts a pattern search method in the schedule generation procedure to obtain an approximate optimal solution. It is found that the computation time becomes short enough for a practical use. Moreover, the extension of the parameter domain yields an approximate optimal solution which is better than the best solution obtained by the ‘direct' optimization.
Queuing Network Analysis on Hybrid Flow Shop Scheduling
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Fuqing Zhao
2012-11-01
Full Text Available In this study, we consider a queuing model extension for a production system composed of several parallel machines and the same number of transporters. To obtain the minimum waiting time of the jobs in the queue, we present an exact solution for the proposed queuing model. The solution integrates M/M/C system with M/M/1 system. We obtain explicit expressions for its steady-state behavior under M/M/C and M/M/1 assumptions. Further, in order to illustrate the usefulness of the proposed methods, numerical examples are solved. On the basis of the results of these examples, some important conclusions are drawn.
工件加工时间退化且可拒的带优势关系流水作业问题的动态规划算法%Scheduling deteriorating jobs with rejection on dominant machines
Institute of Scientific and Technical Information of China (English)
程予绍; 孙世杰
2008-01-01
The permutation flow shop scheduling problems with deteriorating jobs and rejection on dominant machines were studied. The objectives are to minimize the makespan of scheduled jobs plus the total rejection penalty and the total completion time of scheduled jobs plus the total rejection penalty. For each objective, polynomial time algorithms based on dynamic programming were presented.
Associating Memory Through Case-Based Immune Mechanisms for Dynamic Job-Shop Scheduling
Institute of Scientific and Technical Information of China (English)
尹文君; 刘民; 吴澄
2004-01-01
Knowledge plays an active role in job-shop scheduling,especially in dynamic environments.A novel case-based immune framework was developed for static and dynamic job-shop problems,using the associative memory and knowledge reuse from case-based reasoning (CBR) and immune response mechanisms.A 2-level similarity index which combines both job routing and problem solution characteristics based on DNA matching ideas was defined for both the CBR and immune algorithms.A CBR-embedded immune algorithms (CBR-IAs) framework was then developed focusing on case retrieval and adaptation methods.In static environments,the CBR-IAs have excellent population diversity and fast convergence which are necessary for dynamic problems with jobs arriving and leaving continually.The results with dynamic scheduling problems further confirm the CBR-IAs effectiveness as a problem solving method with knowledge reuse.
Algorithm Based on Taboo Search and Shifting Bottleneck for Job Shop Scheduling
Institute of Scientific and Technical Information of China (English)
Wen-Qi Huang; Zhi Huang
2004-01-01
In this paper, a computational effective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. It is based on taboo search procedure and on the shifting bottleneck procedure used to jump out of the trap of the taboo search procedure. A key point of the algorithm is that in the taboo search procedure two taboo lists are used to forbid two kinds of reversals of arcs, which is a new and effective way in taboo search methods for job shop scheduling. Computational experiments on a set of benchmark problem instances show that, in several cases, the approach, in reasonable time, yields better solutions than the other heuristic procedures discussed in the literature.
Bai, Danyu
2015-08-01
This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.
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A. Baskar
2016-04-01
Full Text Available Permutation flow shop scheduling problems have been an interesting area of research for over six decades. Out of the several parameters, minimization of makespan has been studied much over the years. The problems are widely regarded as NP-Complete if the number of machines is more than three. As the computation time grows exponentially with respect to the problem size, heuristics and meta-heuristics have been proposed by many authors that give reasonably accurate and acceptable results. The NEH algorithm proposed in 1983 is still considered as one of the best simple, constructive heuristics for the minimization of makespan. This paper analyses the powerful job insertion technique used by NEH algorithm and proposes seven new variants, the complexity level remains same. 120 numbers of problem instances proposed by Taillard have been used for the purpose of validating the algorithms. Out of the seven, three produce better results than the original NEH algorithm.
CONWIP card setting in a flow-shop system with a batch production machine
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Marcello Braglia
2011-01-01
Full Text Available This paper presents an analytical technique to determine the optimum number of cards to control material release in a CONWIP system. The work focuses on the card setting problem for a flow-shop system characterised by the presence of a batch processing machine (e.g. a kiln for long heat treatment. To control production, two different static approaches are developed: the first one is used when the bottleneck coincides with the batch processing machine and the second one is proposed when the bottleneck is another machine of the flow shop. In both contexts, by means of the appropriate model, one can optimize the performance of the flow-shop by maximizing the throughput and keeping the work in process at a minimum level. Numerical examples are also included in the paper to confirm the validity of the models and to demonstrate their practical utility.
A Heuristic for Two-Stage No-Wait Hybrid Flowshop Scheduling with a Single Machine in Either Stage
Institute of Scientific and Technical Information of China (English)
刘志新; 谢金星; 李建国; 董杰方
2003-01-01
This paper studies the hybrid flow-shop scheduling problem with no-wait restrictions. The production process consists of two machine centers, one has a single machine and the other has more than one parallel machine. A greedy heuristic named least deviation algorithm is designed and its worst case performance is analyzed. Computational results are also given to show the algorithm's average performance compared with some other algorithms. The least deviation algorithm outperforms the others in most cases tested here, and it is of low computational complexity and is easy to carry out,thus it is of favorable application value.
Reactive Scheduling Presentation for an Open Shop problem focused on job\\\\\\'s due dates
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hadi naseri
2016-02-01
Full Text Available scheduling consists of assignment resources in order to perform a set of tasks in a given time horizon, that optimizes the usage of available resources. Most of researches in open shop district (area have stationary and certain status, means the situation that all data are certain and won't change in time horizon. Whereas real world scheduling problems are rarely stationary and certain. Reactive programming is a researching district that considers and peruses each changes and uncertain assumptions in real world scheduling problems, so in this paper, first we express a mixed integer programming model to produce initial scheduling for open shop problem, in continue we will generalize the presented model to it's equivalent reactive programming with due date's changing. Finally we will express an algorithm due to necessity for revise the primal scheduling. This algorithm and whole models have been implemented and ran in AIMMS software environment and the computational results have been reported.
Yamana, Takashi; Iima, Hitoshi; Sannomiya, Nobuo
Although there have been many studies on parallel machine scheduling problems, the number of machines operated is fixed in these studies. It is desirable to generate a schedule with fewer machines operated from the viewpoint of the operation cost of machines. In this paper, we cope with a problem of minimizing the number of parallel machines subject to the constraint that the total tardiness is not greater than the value given in advance. For this problem, we introduce a local search method in which the number of machines operated is changed efficiently and appropriately in a short time as well as reducing the total tardiness.
Online algorithms for scheduling with machine activation cost on two uniform machines
Institute of Scientific and Technical Information of China (English)
HAN Shu-guang; JIANG Yi-wei; HU Jue-liang
2007-01-01
In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Machines need to be activated before starting to process, and each machine activated incurs a fixed machine activation cost. No machines are initially activated,and when a job is revealed, the algorithm has the option to activate new machines. The objective is to minimize the sum of the makespan and the machine activation cost. We design optimal online algorithms with competitive ratio of (2s+1)/(s+1) for every s≥1.
Optimasi Multi-objective Menggunakan NSGA-II Dalam Penjadwalan Mesin Produksi Flow Shop
2016-01-01
Scheduling is an activity to allocate limited resources to finish the jobs. Scheduling process arise if there are limitations on available resources that requiring utilization the available resources efficiently. Generally, the purpose of production scheduling is to optimize specific dimensions or objects. Flow shop scheduling is a type of production scheduling where each job will go through each machine with an uniform sequence. Optimization of the flow shop production machine scheduling rel...
Unrelated Machine Scheduling with Stochastic Processing Times
Skutella, Martin; Sviridenko, Maxim; Uetz, Marc
2016-01-01
Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the processing times of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated
Unrelated Machine Scheduling with Stochastic Processing Times
Skutella, Martin; Sviridenko, Maxim; Uetz, Marc Jochen
Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the processing times of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated
Production Machine Shop Employment Competencies. Part Two: Saws, Drills, and Grinders.
Bishart, Gus; Werner, Claire
Competencies for production machine shop are provided for the second of four topic areas: saws, drills, and grinders. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment, will…
Directory of Open Access Journals (Sweden)
M. Frutos
2013-01-01
Full Text Available Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.
Machine Shop. Module 8: CNC (Computerized Numerical Control). Instructor's Guide.
Crosswhite, Dwight
This document consists of materials for a five-unit course on the following topics: (1) safety guidelines; (2) coordinates and dimensions; (3) numerical control math; (4) programming for numerical control machines; and (5) setting and operating the numerical control machine. The instructor's guide begins with a list of competencies covered in the…
Machine Shop. Module 8: CNC (Computerized Numerical Control). Instructor's Guide.
Crosswhite, Dwight
This document consists of materials for a five-unit course on the following topics: (1) safety guidelines; (2) coordinates and dimensions; (3) numerical control math; (4) programming for numerical control machines; and (5) setting and operating the numerical control machine. The instructor's guide begins with a list of competencies covered in the…
SOLVING FLEXIBLE JOB SHOP SCHEDULING PROBLEM BY GENETIC ALGORITHM%用遗传算法求解柔性作业车间调度问题
Institute of Scientific and Technical Information of China (English)
乔兵; 孙志峻; 朱剑英
2001-01-01
古典作业车间调度问题已经被研究了几十年并证明为NP-hard问题。柔性作业车间调度是古典作业车间调度问题的扩展，它允许工序由一个机床集合中的任意一台加工，调度的目的是将工序分配给各机床，并对各机床上的工序进行排序以使完成所有工序的时间最小化。本文采用遗传算法进行柔性作业车间调度研究，针对柔性作业车间问题提出了一种新颖直观的基因编码方法，从而取消了运用遗传算法求解作业车间问题时为使基因合法化而进行的基因修复过程，仿真结果表明用该遗传算法解决柔性作业车间调度问题是有效的。%The job shop scheduling problem has been studied for decades and known as an NP-hard problem. The flexible job shop scheduling problem is a generalization of the classical job scheduling problem that allows an operation to be processed on one machine out of a set of machines. The problem is to assign each operation to a machine and find a sequence for the operations on the machine in order that the maximal completion time of all operations is minimized. A genetic algorithm is used to solve the flexible job shop scheduling problem. A novel gene coding method aiming at job shop problem is introduced which is intuitive and does not need repairing process to validate the gene. Computer simulations are carried out and the results show the effectiveness of the proposed algorithm.
An Efficient Estimation of Distribution Algorithm for Job Shop Scheduling Problem
He, Xiao-Juan; Zeng, Jian-Chao; Xue, Song-Dong; Wang, Li-Fang
An estimation of distribution algorithm with probability model based on permutation information of neighboring operations for job shop scheduling problem was proposed. The probability model was given using frequency information of pair-wise operations neighboring. Then the structure of optimal individual was marked and the operations of optimal individual were partitioned to some independent sub-blocks. To avoid repeating search in same area and improve search speed, each sub-block was taken as a whole to be adjusted. Also, stochastic adjustment to the operations within each sub-block was introduced to enhance the local search ability. The experimental results show that the proposed algorithm is more robust and efficient.
A Grafted Genetic Algorithm for the Job-Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
LI Xiang-jun; WANG Shu-zhen; XU Guo-hua
2004-01-01
The standard genetic algorithm has limitations of a low convergence rate and premature convergence in solving the job-shop scheduling problem.To overcome these limitations,this paper presents a new improved hybrid genetic algorithm on the basis of the idea of graft in botany.Through the introduction of a grafted population and crossover probability matrix,this algorithm accelerates the convergence rate greatly and also increases the ability to fight premature convergence.Finally,the approach is tested on a set of standard instances taken from the literature and compared with other approaches.The computation results validate the effectiveness of the proposed algorithm.
Improvements for multi-objective flow shop scheduling by Pareto Iterated Local Search
Geiger, Martin Josef
2009-01-01
The article describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow shop scheduling problems under multiple objectives and compared to other local search approaches. While the obtained results are encouraging in terms of their quality, another positive attribute of the approach is its simplicity as it does require the setting of only very few parameters.
Noori-Darvish, Samaneh; Tavakkoli-Moghaddam, Reza
2012-10-01
We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEA-II. Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the traditional NSGA-II.
Category 1 Project Machine Shop Improvements. Phase 3 Proposal. Revision A
1984-10-26
Controller (Water/2500 F) Grieve Convection Oven 18" x 17" x 13" 1 1980 Good Advantage Engineering Hopper Loader 1 1980 Good Arburg Hopper Dryer 1 1977...Good Nova-Tech Twin Bed Dessicant Dryer 1 1980 Good Figure 1-17. MOLD SHOP LAYOUT AND EQUIPMENT LISTING 1J 22 -Ir, Figure 1-18. MOLD SHOr 23 I II I I I...adjacent to the Machine Shop. This work cell brings the Sweco Tumbling Mill and most of the manual grinders and belt sanders into one area. Currently
Approximation algorithms for scheduling unrelated parallel machines with release dates
Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.
2017-01-01
In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.
An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times
Directory of Open Access Journals (Sweden)
Rui Zhang
2011-09-01
Full Text Available Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the stochastic job shop scheduling problem (SJSSP has not received sufficient attention. In this paper, we propose an artificial bee colony (ABC algorithm for SJSSP with the objective of minimizing the maximum lateness (which is an index of service quality. First, we propose a performance estimate for preliminary screening of the candidate solutions. Then, the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation (through Monte Carlo simulation process. Finally, the computational results on different-scale test problems validate the effectiveness and efficiency of the proposed approach.
Models and Strategies for Variants of the Job Shop Scheduling Problem
Grimes, Diarmuid
2011-01-01
Recently, a variety of constraint programming and Boolean satisfiability approaches to scheduling problems have been introduced. They have in common the use of relatively simple propagation mechanisms and an adaptive way to focus on the most constrained part of the problem. In some cases, these methods compare favorably to more classical constraint programming methods relying on propagation algorithms for global unary or cumulative resource constraints and dedicated search heuristics. In particular, we described an approach that combines restarting, with a generic adaptive heuristic and solution guided branching on a simple model based on a decomposition of disjunctive constraints. In this paper, we introduce an adaptation of this technique for an important subclass of job shop scheduling problems (JSPs), where the objective function involves minimization of earliness/tardiness costs. We further show that our technique can be improved by adding domain specific information for one variant of the JSP (involving...
Directory of Open Access Journals (Sweden)
Jinwei Gu
2015-01-01
Full Text Available A mutualism quantum genetic algorithm (MQGA is proposed for an integrated supply chain scheduling with the materials pickup, flow shop scheduling, and the finished products delivery. The objective is to minimize the makespan, that is, the arrival time of the last finished product to the customer. In MQGA, a new symbiosis strategy named mutualism is proposed to adjust the size of each population dynamically by regarding the mutual influence relation of the two subpopulations. A hybrid Q-bit coding method and a local speeding-up method are designed to increase the diversity of genes, and a checking routine is carried out to ensure the feasibility of each solution; that is, the total physical space of each delivery batch could not exceed the capacity of the vehicle. Compared with the modified genetic algorithm (MGA and the quantum-inspired genetic algorithm (QGA, the effectiveness and efficiency of the MQGA are validated by numerical experiments.
Directory of Open Access Journals (Sweden)
J. S. Sadaghiani
2014-04-01
Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.
Institute of Scientific and Technical Information of China (English)
张素君; 顾幸生
2015-01-01
An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers (IBFSP) in order to minimize the maximum completion time (i.e makespan). The effective combination of the insertion and swap operator is applied to producing neighborhood individual at the employed bee phase. The tournament selection is adopted to avoid falling into local optima, while, the optimized insert operator embeds in onlooker bee phase for further searching the neighborhood solution to enhance the local search ability of algorithm. The tournament selection with size 2 is again applied and a better selected solution will be performed destruction and construction of iterated greedy (IG) algorithm, and then the result replaces the worse one. Simulation results show that our algorithm has a better performance compared with the HDDE and CHS which were proposed recently. It provides the better known solutions for the makespan criterion to flow shop scheduling problem with limited buffers for the Car benchmark by Carlier and Rec benchmark by Reeves. The convergence curves show that the algorithm not only has faster convergence speed but also has better convergence value.
Directory of Open Access Journals (Sweden)
A. Khodadadi
2014-04-01
Full Text Available In most manufacturing and distribution systems, semi-finished jobs are transferred from one processing facility to another by transporters such as automated guided vehicles and conveyors and finished jobs are delivered to customers or warehouses by vehicles such as trucks. Most machine scheduling models assume either that there are a finite number of transporters for delivering jobs or that jobs are delivered instantaneously from one location to another without transportation time involved. In this study we study a new simple heuristic algorithm for a ‘3-machine, n-job’ flow shop scheduling problem in which transportation time and break down times of machines are considered. A heuristic approach method to find optimal and near optimal sequence minimizing the total elapsed time.
柔性作业车间调度的多Agent协商策略%Negotiation Strategies for Multi-Agent Flexible Job-shop Scheduling
Institute of Scientific and Technical Information of China (English)
任海英; 商晓坤
2011-01-01
柔性作业车间调度问题是经典作业车间调度问题的扩展.为此,提出一种新的基于招投标的多Agent协商调度策略,并研究各Agent协商时的价格函数.系统主要由工件Agent和机器Agent组成,工件Agent通过招投标的方式,选择合适的机器完成加工任务,机器Agent按照市场机制通过自由竞争获得工件的加工权,根据基于规则的调度策略处理工件.用Java设计仿真实验程序,并通过实验验证所提价格协商函数的有效性.%The Flexible Job-shop Scheduling Problem(FJSP) is a generalization of the classical Job-shop Scheduling Problem(JSP).In this paper, a multi-Agent negotiation and scheduling strategy based on biding is proposed.This study focuses on bid calculation.The system contains part Agent and machine Agent.Through biding part Agent selects the appropriate machine and machine Agent selects the appropriate part by competing with others based on market mechanism to maximize its income and use dispatching rules to schedule the parts.The system is implemented in Java and the proposed algorithm is tested on a standard instance taken from the literature and compared with other approaches.Experimental results show the effectiveness of the negotiation function.
A hybrid quantum-inspired genetic algorithm for multiobjective flow shop scheduling.
Li, Bin-Bin; Wang, Ling
2007-06-01
This paper proposes a hybrid quantum-inspired genetic algorithm (HQGA) for the multiobjective flow shop scheduling problem (FSSP), which is a typical NP-hard combinatorial optimization problem with strong engineering backgrounds. On the one hand, a quantum-inspired GA (QGA) based on Q-bit representation is applied for exploration in the discrete 0-1 hyperspace by using the updating operator of quantum gate and genetic operators of Q-bit. Moreover, random-key representation is used to convert the Q-bit representation to job permutation for evaluating the objective values of the schedule solution. On the other hand, permutation-based GA (PGA) is applied for both performing exploration in permutation-based scheduling space and stressing exploitation for good schedule solutions. To evaluate solutions in multiobjective sense, a randomly weighted linear-sum function is used in QGA, and a nondominated sorting technique including classification of Pareto fronts and fitness assignment is applied in PGA with regard to both proximity and diversity of solutions. To maintain the diversity of the population, two trimming techniques for population are proposed. The proposed HQGA is tested based on some multiobjective FSSPs. Simulation results and comparisons based on several performance metrics demonstrate the effectiveness of the proposed HQGA.
Games and mechanism design in machine scheduling - an introduction
Heydenreich, Birgit; Müller, Rudolf; Uetz, Marc Jochen
We survey different models, techniques, and some recent results to tackle machine scheduling problems within a distributed setting. In traditional optimization, a central authority is asked to solve a (computationally hard) optimization problem. In contrast, in distributed settings there are several
Prediction based proactive thermal virtual machine scheduling in green clouds.
Kinger, Supriya; Kumar, Rajesh; Sharma, Anju
2014-01-01
Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.
Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds
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Supriya Kinger
2014-01-01
Full Text Available Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.
The Distributed Assembly Parallel Machine Scheduling Problem with eligibility constraints.
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Sara Hatami
2015-01-01
Full Text Available In this paper we jointly consider realistic scheduling extensions: First we study the distributed unrelated parallel machines problems by which there is a set of identical factories with parallel machines in a production stage. Jobs have to be assigned to factories and to machines. Additionally, there is an assembly stage with a single assembly machine. Finished jobs at the manufacturing stage are assembled into final products in this second assembly stage. These two joint features are referred to as the distributed assembly parallel machine scheduling problem or DAPMSP. The objective is to minimize the makespan in the assembly stage. Due to technological constraints, machines cannot be left empty and some jobs might be processed on certain factories only. We propose a mathematical model and two high performing heuristics. The model is tested with two state-of-the-art solvers and, together with the heuristics, 2220 instances are solved in a comprehensive computational experiments. Results show that the proposed model is able to solve moderately-sized instances and one of the heuristics is fast, giving close to optimal solutions in less than half a second in the worst case.
含局部流水的柔性作业车间调度研究%Research of flexible job shop scheduling with flow process line
Institute of Scientific and Technical Information of China (English)
陆汉东; 何卫平
2012-01-01
针对含有局部流水生产的柔性作业车间生产调度问题,首先在柔性作业车间调度问题的基础上建立调度模型,然后提出一种基于模拟退火法的调度算法,同时对加工路径和加工顺序进行优化,并实现最小化完工时间的调度目标.最后通过实例进行仿真,结果表明了算法的可行性和有效性.%Aiming at solving the problem of flexible job shop scheduling with flow process line, a mathematic model has been established firstly based on flexible job shop scheduling. Then a scheduling algorithm based on simulated annealing method has been presented to realize the minimum time for the work, which both optimizes the assignment of machine and the sequence of operations. Finally, the simulation of the practical example proves the feasibility and efficiency of the algorithm.
Automatic programming via iterated local search for dynamic job shop scheduling.
Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen
2015-01-01
Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.
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Jianfei Ye
2015-01-01
Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.
Optimal Rules for Single Machine Scheduling with Stochastic Breakdowns
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Jinwei Gu
2014-01-01
Full Text Available This paper studies the problem of scheduling a set of jobs on a single machine subject to stochastic breakdowns, where jobs have to be restarted if preemptions occur because of breakdowns. The breakdown process of the machine is independent of the jobs processed on the machine. The processing times required to complete the jobs are constants if no breakdown occurs. The machine uptimes are independently and identically distributed (i.i.d. and are subject to a uniform distribution. It is proved that the Longest Processing Time first (LPT rule minimizes the expected makespan. For the large-scale problem, it is also showed that the Shortest Processing Time first (SPT rule is optimal to minimize the expected total completion times of all jobs.
A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems
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Jian Xiong
2012-01-01
Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.
Three hybridization models based on local search scheme for job shop scheduling problem
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
Solution-Guided Multi-Point Constructive Search for Job Shop Scheduling
Beck, J C
2011-01-01
Solution-Guided Multi-Point Constructive Search (SGMPCS) is a novel constructive search technique that performs a series of resource-limited tree searches where each search begins either from an empty solution (as in randomized restart) or from a solution that has been encountered during the search. A small number of these "elite solutions is maintained during the search. We introduce the technique and perform three sets of experiments on the job shop scheduling problem. First, a systematic, fully crossed study of SGMPCS is carried out to evaluate the performance impact of various parameter settings. Second, we inquire into the diversity of the elite solution set, showing, contrary to expectations, that a less diverse set leads to stronger performance. Finally, we compare the best parameter setting of SGMPCS from the first two experiments to chronological backtracking, limited discrepancy search, randomized restart, and a sophisticated tabu search algorithm on a set of well-known benchmark problems. Results d...
A New Local Search Algorithm for the Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
HuangWen-qi; YinAi-hua
2003-01-01
In this paper, the job shop scheduling problem concerned with minimizing make-span is discussed, and a new local search algorithm is proposed for it. This local search method is based on an improved shifting bottleneck procedure and Tabu Search technique. This new local search is different from the previous Tabu Search (TS) proposed by other authors, which is because the improved shifting bottleneck procedure is a new technology that is provided by us for the problem, and two remarkable strategies--intensification and diversification of TS are modified. To demonstrate the performance, our algorithm has been tested on many common problem instances (benchmarks) with various sizes and levels of hardness and compared with other algorithms, especially the latest TS in the literatures.Computational experiments show that this algorithm is effective and efficient.
A New Local Search Algorithm for the Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
Huang Wen-qi; Yin Ai-hua
2003-01-01
In this paper, the job shop scheduling problem concerned with minimizing make-span is discussed, and a new local search algorithm is proposed for it. This local search method is based on an improved shifting bottleneck procedure and Tabu Search technique. This new local search is different from the previous Tabu Search (TS) proposed by other authors, which is because the improved shifting bottleneck procedure is a new technology that is provided by us for the problem, and two remarkable strategies--intensification and diversification of TS are modified. To demonstrate the performance, our algorithm has been tested on many common problem instances (benchmarks)with various sizes and levels of hardness and compared with other algorithms, especially the latest TS in the literatures.Computational experiments show that this algorithm is effective and efficient.
Wang, Chun; Ji, Zhicheng; Wang, Yan
2017-07-01
In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.
Liu, Weibo; Jin, Yan; Price, Mark
2016-10-01
A new heuristic based on the Nawaz-Enscore-Ham algorithm is proposed in this article for solving a permutation flow-shop scheduling problem. A new priority rule is proposed by accounting for the average, mean absolute deviation, skewness and kurtosis, in order to fully describe the distribution style of processing times. A new tie-breaking rule is also introduced for achieving effective job insertion with the objective of minimizing both makespan and machine idle time. Statistical tests illustrate better solution quality of the proposed algorithm compared to existing benchmark heuristics.
Optimum Production Control and Workforce Scheduling of Machining Project
Lan, Tian-Syung; Lo, Chih-Yao; Hou, Cheng-I.
Through the proposed model in this study, the production control with the consideration of workforce scheduling for advanced manufacturing systems becomes realistically and concretely solvable. This study not only meditates the concept of balancing machine productivity and human ability into the objective, but also implements Calculus of Variations to optimize the profit for a deterministic production quantity. In addition, the optimum solutions of dynamic productivity control and workforce scheduling are comprehensively provided. Moreover, the decision criteria for selecting the optimum solution and the sensitivity analysis of the critical variables are fully discussed. This study definitely contributes the applicable strategy to control the productivity and workforce in manufacturing and provides the valuable tool to conclusively optimize the profit of a machining project for operations research in today`s manufacturing industry with profound insight.
Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints
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Cuixia Miao
2015-01-01
Full Text Available We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme for the two-machine problem. Furthermore, we extended the dynamic programming algorithm to the total weighted completion time minimization problem.
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Ricardo Ferrari Pacheco
1999-04-01
Full Text Available Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados em métodos de busca estendida. Por meio dessa classificação obteve-se um painel amplo dos modelos existentes, evidenciando as diferentes abordagens do problema e suas soluções, com o objetivo de proporcionar uma orientação preliminar na escolha do modelo de job shop scheduling mais adequado.This paper proposes a hierarchical model classification used in the job shop scheduling problem, including those that provide an optimal solution and the more recent ones based on heuristics, called extended search methods. A panel with the existing models is obtained by this classification, and solutions and approach differences are highlighted with the aim of a preliminary orientation on the choice of a more adequate job shop scheduling model.
ON-LINE SCHEDULING WITH REJECTION ON IDENTICAL PARALLEL MACHINES
Institute of Scientific and Technical Information of China (English)
Cuixia MIAO; Yuzhong ZHANG
2006-01-01
In this paper, we consider the on-line scheduling of unit time jobs with rejection on m identical parallel machines. The objective is to minimize the total completion time of the accepted jobs plus the total penalty of the rejected jobs. We give an on-line algorithm for the problem with competitive ratio 1/2(2 + √3) ≈ 1.86602.
Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds
Supriya Kinger; Rajesh Kumar; Anju Sharma
2014-01-01
Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a crit...
Single-Machine Scheduling with Accelerating Learning Effects
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T. C. E. Cheng
2013-01-01
Full Text Available Scheduling with learning effects has been widely studied. However, there are situations where the learning effect might accelerate. In this paper, we propose a new model where the learning effect accelerates as time goes by. We derive the optimal solutions for the single-machine problems to minimize the makespan, total completion time, total weighted completion time, maximum lateness, maximum tardiness, and total tardiness.
Algorithms for single machine scheduling with availability constraints
Institute of Scientific and Technical Information of China (English)
LI Bo; SHI Bing-xin; SHEN Bin; LIU Ji-cheng
2005-01-01
It is a NP-hard problem to schedule a list of nonresumable jobs to the available intervals of an availability-constrained single machine to minimize the scheduling length. This paper transformed this scheduling problem into a variant of the variable-sized bin packing problem, put forward eight bin packing algorithms adapted from the classic one-dimensional bin packing problem and investigated their performances from both of the worst-case and the average-case scenarios. Analytical results show that the worst-case performance ratios of the algorithms are not less than 2. Experimental results for average cases show that the Best Fit and the Best Fit Decreasing algorithm outperform any others for independent and precedence-constrained jobs respectively.
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Sunxin Wang
2014-01-01
Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.
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Renata Melo e Silva de Oliveira
2015-03-01
Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests. With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs. The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2014-09-01
In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.
A hybrid flow shop model for an ice cream production scheduling problem
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Imma Ribas Vila
2009-07-01
Full Text Available Normal 0 21 false false false ES X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Taula normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} In this paper we address the scheduling problem that comes from an ice cream manufacturing company. This production system can be modelled as a three stage nowait hybrid flow shop with batch dependent setup costs. To contribute reducing the gap between theory and practice we have considered the real constraints and the criteria used by planners. The problem considered has been formulated as a mixed integer programming. Further, two competitive heuristic procedures have been developed and one of them will be proposed to schedule in the ice cream factory.
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XIONG He-gen; LI Jian-jun; OUYANG Hong-qun; XIAO Xiang-zhi
2004-01-01
In a one-of-a-kind and order-oriented production corporation, job shop scheduling plays an important role in the production planning system and production process control. Since resource selection in job shop scheduling directly influences the qualities and due dates of products and production cost, it is indispensable to take resource selection into account during job shop scheduling. By analyzing the relative characteristics of resources, an approach of fuzzy decision is proposed for resource selection. Finally, issues in the application of the approach are discussed.
On the Configuration-LP for Scheduling on Unrelated Machines
Verschae, José
2010-01-01
One of the most important open problems in machine scheduling is the problem of scheduling a set of jobs on unrelated machines to minimize the makespan. The best known approximation algorithm for this problem guarantees an approximation factor of 2. It is known to be NP-hard to approximate with a better ratio than 3/2. Closing this gap has been open for over 20 years. The best known approximation factors are achieved by LP-based algorithms. The strongest known linear program formulation for the problem is the configuration-LP. We show that the configuration-LP has an integrality gap of 2 even for the special case of unrelated graph balancing, where each job can be assigned to at most two machines. In particular, our result implies that a large family of cuts does not help to diminish the integrality gap of the canonical assignment-LP. Also, we present cases of the problem which can be approximated with a better factor than 2. They constitute valuable insights for constructing an NP-hardness reduction which im...
Real time scheduling model for flexible job-shop environment%以多Agent系统为架构的实时调度模型
Institute of Scientific and Technical Information of China (English)
赵良辉; 王天擎; 陶雪萍
2012-01-01
A real time scheduling model for Flexible Job-Shop Scheduling Problem(FJSP) is designed; in the model jobs and machines are capsulated as agents, the negotiations between Job Agents (Jas) and Machine Agents(Mas) form the real time schedule. The model bases on Contract-Net-Protocol (CNP) along with a virtue-currency-scheme, which can give jobs that have closer due dates higher priority on winning machines to process their operations, consequently optimizes the schedule resolution while holding its real time ability. In additional, an urgent-job-insertion algorithm is introduced in, to dealing with schedules of "urgent jobs" smoothly, without disturbing other jobs' schedules too much. Compared to other known schedule models, the one in this paper has its unique edge in real-time responding, scheduling quality and customer satisfaction degree.%构建了一个适用于柔性作业车间(FJSP)调度的实时模型,将车间加工设备和作业封装为Agent,通过Agent之间的招投标实现实时调度.采用了虚拟货币机制来构造实时调度模型,该机制可使交货期紧张的作业拥有更高的优先级选择加工机器,使调度方案在满足实时性的同时得到优化；模型还引入急件插入机制,在处理紧急任务时可在尽量减少对其他任务干扰的前提下顺利实现对紧急任务的调度.与其他同类调度模型相比,提出的模型在实时性、调度质量上和用户满意度上都拥有其独特优势.
Institute of Scientific and Technical Information of China (English)
邓冠龙; 徐震浩; 顾幸生
2012-01-01
A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.
A hybrid algorithm for unrelated parallel machines scheduling
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Mohsen Shafiei Nikabadi
2016-09-01
Full Text Available In this paper, a new hybrid algorithm based on multi-objective genetic algorithm (MOGA using simulated annealing (SA is proposed for scheduling unrelated parallel machines with sequence-dependent setup times, varying due dates, ready times and precedence relations among jobs. Our objective is to minimize makespan (Maximum completion time of all machines, number of tardy jobs, total tardiness and total earliness at the same time which can be more advantageous in real environment than considering each of objectives separately. For obtaining an optimal solution, hybrid algorithm based on MOGA and SA has been proposed in order to gain both good global and local search abilities. Simulation results and four well-known multi-objective performance metrics, indicate that the proposed hybrid algorithm outperforms the genetic algorithm (GA and SA in terms of each objective and significantly in minimizing the total cost of the weighted function.
Online Scheduling on a Single Machine with Grouped Processing Times
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Qijia Liu
2015-01-01
Full Text Available We consider the online scheduling problem on a single machine with the assumption that all jobs have their processing times in [p,(1+αp], where p>0 and α=(5-1/2. All jobs arrive over time, and each job and its processing time become known at its arrival time. The jobs should be first processed on a single machine and then delivered by a vehicle to some customer. When the capacity of the vehicle is infinite, we provide an online algorithm with the best competitive ratio of (5+1/2. When the capacity of the vehicle is finite, that is, the vehicle can deliver at most c jobs at a time, we provide another best possible online algorithm with the competitive ratio of (5+1/2.
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Min Dai
2013-01-01
Full Text Available A flexible flow-shop scheduling (FFS with nonidentical parallel machines for minimizing the maximum completion time or makespan is a well-known combinational problem. Since the problem is known to be strongly NP-hard, optimization can either be the subject of optimization approaches or be implemented for some approximated cases. In this paper, an improved genetic-simulated annealing algorithm (IGAA, which combines genetic algorithm (GA based on an encoding matrix with simulated annealing algorithm (SAA based on a hormone modulation mechanism, is proposed to achieve the optimal or near-optimal solution. The novel hybrid algorithm tries to overcome the local optimum and further to explore the solution space. To evaluate the performance of IGAA, computational experiments are conducted and compared with results generated by different algorithms. Experimental results clearly demonstrate that the improved metaheuristic algorithm performs considerably well in terms of solution quality, and it outperforms several other algorithms.
Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem
Luo, Yabo; Waden, Yongo P.
2017-06-01
Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.
Parallel genetic algorithms with migration for the hybrid flow shop scheduling problem
Directory of Open Access Journals (Sweden)
K. Belkadi
2006-01-01
Full Text Available This paper addresses scheduling problems in hybrid flow shop-like systems with a migration parallel genetic algorithm (PGA_MIG. This parallel genetic algorithm model allows genetic diversity by the application of selection and reproduction mechanisms nearer to nature. The space structure of the population is modified by dividing it into disjoined subpopulations. From time to time, individuals are exchanged between the different subpopulations (migration. Influence of parameters and dedicated strategies are studied. These parameters are the number of independent subpopulations, the interconnection topology between subpopulations, the choice/replacement strategy of the migrant individuals, and the migration frequency. A comparison between the sequential and parallel version of genetic algorithm (GA is provided. This comparison relates to the quality of the solution and the execution time of the two versions. The efficiency of the parallel model highly depends on the parameters and especially on the migration frequency. In the same way this parallel model gives a significant improvement of computational time if it is implemented on a parallel architecture which offers an acceptable number of processors (as many processors as subpopulations.
Johan Soewanda; Tanti Octavia; Iwan Halim Sahputra
2007-01-01
This paper discusses the application of Robust Hybrid Genetic Algorithm to solve a flow-shop scheduling problem. The proposed algorithm attempted to reach minimum makespan. PT. FSCM Manufacturing Indonesia Plant 4's case was used as a test case to evaluate the performance of the proposed algorithm. The proposed algorithm was compared to Ant Colony, Genetic-Tabu, Hybrid Genetic Algorithm, and the company's algorithm. We found that Robust Hybrid Genetic produces statistically better result than...
Hybrid genetic algorithm for minimizing non productive machining ...
African Journals Online (AJOL)
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A Bi-criteria M-Machine SDST Flow Shop Scheduling using Modified Heuristic Genetic ... He has more than 35 research papers in international/national journals and ... supply chain management, inventory management, machine learning, etc.
Shaper and Milling Machine Operation, Machine Shop Work 2: 9555.04.
Dade County Public Schools, Miami, FL.
The course outline has been prepared to assist the student in learning the basic skills and safety for shaper and milling operations. The course presents the various types of machines, work holding devices, cutting tools and feeds and speeds, and instruction designed to enable the student to obtain the manipulative skills and related knowledge…
Directory of Open Access Journals (Sweden)
Rui Zhang
2012-01-01
Full Text Available Most existing research on the job shop scheduling problem has been focused on the minimization of makespan (i.e., the completion time of the last job. However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. Several dispatching rules are adopted in the Giffler-Thompson algorithm for constructing active schedules. It is noticeable that the rule selections for scheduling consecutive operations are not mutually independent but actually interrelated. Under such circumstances, a probabilistic model-building genetic algorithm (PMBGA is proposed to optimize the sequence of selected rules. First, we use Bayesian networks to model the distribution characteristics of high-quality solutions in the population. Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. The superiority of the proposed approach is verified by extensive computational experiments and comparisons.
Semi on-line scheduling for maximizing the minimum machine completion time on three uniform machines
Institute of Scientific and Technical Information of China (English)
LUO Run-zi; SUN Shi-jie
2005-01-01
The paper investigates a semi on-line scheduling problem wherein the largest processing time of jobs done by three uniform machines M1, M2, M3 is known in advance. A speed si (s1=1, s2=r, s3=s, 1≤r≤s) is associated with machine Mi. Our goal is to maximize Cmin-the minimum workload of the three machines. We present a min3 algorithm and prove its competitive ratio is max {r+ 1,(3s+r+ 1)/(1 +r+s)}, with the lower bound being at least max {2,r}. We also claim the competitive ratio of min3 algorithn cannot be improved and is the best possible for 1≤s≤2, r=1.
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Omar Danilo Castrillón
2010-08-01
Full Text Available The objective of the present work is to diminish the total process time (Makespan and to increase the machine process time, by diminishing the idle time in a job-shop environment. Through the design of a hyper-heuristic based on an ant colony and genetic algorithms. This work is developed in two phases: in the first phase, a hyper-heuristic identification and definition is carried out for sequencing processes in job shop environments. In the second phase, the system effectiveness in the traditional production programming is shown. In the investigation project, an enterprise from the metal mechanic sector was chosen, where by means of a combination of an ant colony and genetic algorithms, the optimal route for an order is scheduled, achieving the optimization or suboptimization of its respective total process time in an upper percentage of 95%.El objetivo del presente trabajo es disminuir el tiempo de proceso (Makespan e incrementar el tiempo de trabajo de las maquinas, diminuyendo el tiempo de ocio en ambientes de Job Shop, a través del diseño de una Hiper-heurística basada en colonia de hormigas y algoritmos genéticos. Este trabajo se desarrolla en dos etapas: en la primera se realiza la definición e identificación de una Hiper-heurística para la secuenciación de procesos en ambientes Job shop. En la segunda etapa, es mostrada la efectividad del sistema en la programación de la producción. En el proyecto de investigación, se seleccionó una empresa del sector metalmecánico, donde por medio de una combinación de colonia de hormigas y algoritmos genéticos, se programa la ruta óptima para un pedido, logrando la optimización o suboptimización de su respectivo tiempo total de proceso en un porcentaje superior al 95%.
JIT single machine scheduling problem with periodic preventive maintenance
Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani
2016-03-01
This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms.
Directory of Open Access Journals (Sweden)
Hui Du
2016-01-01
Full Text Available To produce the final product, parts need to be fabricated in the process stages and thereafter several parts are joined under the assembly operations based on the predefined bill of materials. But assembly relationship between the assembly parts and components has not been considered in general job shop scheduling problem model. The aim of this research is to find the schedule which minimizes completion time of Assembly Job Shop Scheduling Problem (AJSSP. Since the complexity of AJSSP is NP-hard, a hybrid particle swarm optimization (HPSO algorithm integrated PSO with Artificial Immune is proposed and developed to solve AJSSP. The selection strategy based on antibody density makes the particles of HPSO maintain the diversity during the iterative process, thus overcoming the defect of premature convergence. Then HPSO algorithm is applied into a case study development from classical FT06. Finally, the effect of key parameters on the proposed algorithm is analyzed and discussed regarding how to select the parameters. The experiment result confirmed its practice and effectiveness.
An analysis of iterated local search for job-shop scheduling.
Energy Technology Data Exchange (ETDEWEB)
Whitley, L. Darrell (Colorado State University, Fort Collins, CO); Howe, Adele E. (Colorado State University, Fort Collins, CO); Watson, Jean-Paul (Colorado State University, Fort Collins, CO)
2003-08-01
Iterated local search, or ILS, is among the most straightforward meta-heuristics for local search. ILS employs both small-step and large-step move operators. Search proceeds via iterative modifications to a single solution, in distinct alternating phases. In the first phase, local neighborhood search (typically greedy descent) is used in conjunction with the small-step operator to transform solutions into local optima. In the second phase, the large-step operator is applied to generate perturbations to the local optima obtained in the first phase. Ideally, when local neighborhood search is applied to the resulting solution, search will terminate at a different local optimum, i.e., the large-step perturbations should be sufficiently large to enable escape from the attractor basins of local optima. ILS has proven capable of delivering excellent performance on numerous N P-Hard optimization problems. [LMS03]. However, despite its implicity, very little is known about why ILS can be so effective, and under what conditions. The goal of this paper is to advance the state-of-the-art in the analysis of meta-heuristics, by providing answers to this research question. They focus on characterizing both the relationship between the structure of the underlying search space and ILS performance, and the dynamic behavior of ILS. The analysis proceeds in the context of the job-shop scheduling problem (JSP) [Tai94]. They begin by demonstrating that the attractor basins of local optima in the JSP are surprisingly weak, and can be escaped with high probaiblity by accepting a short random sequence of less-fit neighbors. this result is used to develop a new ILS algorithms for the JSP, I-JAR, whose performance is competitive with tabu search on difficult benchmark instances. They conclude by developing a very accurate behavioral model of I-JAR, which yields significant insights into the dynamics of search. The analysis is based on a set of 100 random 10 x 10 problem instances, in
Directory of Open Access Journals (Sweden)
Johan Soewanda
2007-01-01
Full Text Available This paper discusses the application of Robust Hybrid Genetic Algorithm to solve a flow-shop scheduling problem. The proposed algorithm attempted to reach minimum makespan. PT. FSCM Manufacturing Indonesia Plant 4's case was used as a test case to evaluate the performance of the proposed algorithm. The proposed algorithm was compared to Ant Colony, Genetic-Tabu, Hybrid Genetic Algorithm, and the company's algorithm. We found that Robust Hybrid Genetic produces statistically better result than the company's, but the same as Ant Colony, Genetic-Tabu, and Hybrid Genetic. In addition, Robust Hybrid Genetic Algorithm required less computational time than Hybrid Genetic Algorithm
Lahimer, Asma; Haouari, Mohamed
2011-01-01
This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The problem even in its simplest form is NP-hard in the strong sense. The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems. We propose a new approach based on limited discrepancy search to solve the problem. Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature. Computational results show that the developed approach is efficient in particular for large-size problems.
Directory of Open Access Journals (Sweden)
Tao Ren
2014-01-01
Full Text Available We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.
Energy Technology Data Exchange (ETDEWEB)
Whitley, L. Darrell (Colorado State University, Fort Collins, CO); Watson, Jean-Paul; Howe, Adele E. (Colorado State University, Fort Collins, CO)
2005-06-01
Over the last decade and a half, tabu search algorithms for machine scheduling have gained a near-mythical reputation by consistently equaling or establishing state-of-the-art performance levels on a range of academic and real-world problems. Yet, despite these successes, remarkably little research has been devoted to developing an understanding of why tabu search is so effective on this problem class. In this paper, we report results that provide significant progress in this direction. We consider Nowicki and Smutnicki's i-TSAB tabu search algorithm, which represents the current state-of-the-art for the makespan-minimization form of the classical jobshop scheduling problem. Via a series of controlled experiments, we identify those components of i-TSAB that enable it to achieve state-of-the-art performance levels. In doing so, we expose a number of misconceptions regarding the behavior and/or benefits of tabu search and other local search metaheuristics for the job-shop problem. Our results also serve to focus future research, by identifying those specific directions that are most likely to yield further improvements in performance.
Senthiil, P. V.; Selladurai, V.; Rajesh, R.
This study introduces a new approach for decentralized scheduling in a parallel machine environment based on the ant colonies optimization algorithm. The algorithm extends the use of the traveling salesman problem for scheduling in one single machine, to a multiple machine problem. The results are presented using simple and illustrative examples and show that the algorithm is able to optimize the different scheduling problems. Using the same parameters, the completion time of the tasks is minimized and the processing time of the parallel machines is balanced.
An Adaptive Algorithm for Dynamic Priority Based Virtual Machine Scheduling in Cloud
Directory of Open Access Journals (Sweden)
Subramanian S
2012-11-01
Full Text Available Cloud computing, a relatively new technology, has been gaining immense popularity over the last few years. The number of cloud users has been growing exponentially and apparently scheduling of virtual machines in the cloud becomes an important issue to analyze. This paper throws light on the various scheduling algorithms present for scheduling virtual machines and also proposes a new algorithm that combines the advantages of all the existing algorithms and overcomes their disadvantages.
Institute of Scientific and Technical Information of China (English)
赵诗奎; 方水良; 顾新建
2013-01-01
为了提高柔性作业车间调度求解遗传算法(GA-Ⅰ)的初始种群质量,提出一种基于短用时和设备均衡策略的机器链优化初始方法.运用均匀设计原理对每道工序的具有最短加工时间的可选机器进行均匀组合,形成机器分配链优化遗传算法(GA-Ⅱ)的初始群体；采用均匀设计法构造不同权值,形成机器总负荷和机器负荷方差的不同加权组合以构造机器链优化的适应度函数；通过GA-Ⅱ计算产生定量优化的机器分配链群体.将上述机器分配链优化群体作为柔性作业车间调度问题遗传算法(GA-Ⅰ)的机器链初始群体,并利用混合方式的交叉与变异在工件和工序级尺度上进行遗传操作,实现了FJSP的高效求解算法.通过典型算例验证了该方法的可行性和有效性.%A novel initialization method for machine chains was proposed based on short time and workloads balancing strategies to improve the quality of initial population for the flexible job shop scheduling genetic algorithm(GA-Ⅰ).The uniform design principle was applied to combine alternative machines with the shortest processing time for each operation uniformly,and the initial population of machine chains optimization genetic algorithm(GA-Ⅱ) was constructed.Different weights were designed based on uniform design method,and the machine chains optimization fitness function with different weighted-combinations of total machine load and its variance was constituted.The optimized machine distribution chains were selected as the machine chains initial population for flexible job shop scheduling problem genetic algorithm (GA-Ⅰ).Hybrid cross and mutation were operated on job and operation levels,thus an efficient algorithm for flexible job shop scheduling problem was achieved.Finally,the feasibility and validity of the proposed method was demonstrated with typical examples.
柔性作业车间调度问题的一种启发式算法%Heuristic algorithm for flexible Job-Shop scheduling
Institute of Scientific and Technical Information of China (English)
苏子林; 车忠志; 苑金梁
2011-01-01
为了研究多目标柔性作业车间调度问题,基于甘特图和搭积木经验进行了分析,提出了一种组合优先规则和基于此优先规则的启发式算法.组合优先规则面向完工时间、关键机床负荷和总负荷三个指标,改变规则中各数据项的比例可调整三个指标所占的比例;算法采用随机方式调整三个指标的比例,并微调最优解对应的比例.能随机产生多个高质量调度解.算法对比测试表明,该算法求解质量高、运行速度快且稳定,可直接用于在其他调度算法中产生初始解或者用于动态调度.%To study multi-objective flexible Job-Shop scheduling problem, this paper analyzed it based on Gantt graph and experience from building block, presented a composite priority rule and heuristic algorithm based on this priority rule.This composite priority rule was for three scheduling targets including makespan, critical machine workload and total workload, changing the ratio of data items in the rule could adjust the ratio of the three scheduling targets.The algorithm randomly adjusted the ratio of this three scheduling targets, and slightly adjusted the ratio corresponding to the best solution, could randomly generate many excellent scheduling solutions.The algorithm' s comparison and test show that the result of this algorithm is more excellent, the algorithm runs rapidly and steadily, and can directly be used in generating initial solution in other scheduling algorithms or dynamic scheduling.
柔性作业车间调度分析及其启发式算法%Flexible job-shop scheduling analysis and its heuristic algorithm
Institute of Scientific and Technical Information of China (English)
苏子林; 苑金梁; 陈炜; 邱景炜
2012-01-01
针对多目标柔性作业车间调度问题,基于甘特图和搭积木经验进行了分析,提出了一种组合优先规则和基于此优先规则的启发式算法.组合优先规则面向完工时间、关键机床负荷和总负荷三个指标,改变规则中各数据项的比例可调整三个指标所占的比例.算法采用随机方式调整三个指标的比例,并微调最优解对应的比例,能随机产生多个高质量调度解.对比测试表明,算法求解质量更高,运行速度快,稳定,可直接用于在其他调度算法中产生初始解,或者用于动态调度.%The multi-objective flexible job-shop scheduling problem is analyzed based on Gantt graph and experience from building block, a composite priority rule and heuristic algorithm based on this priority rule are presented. This composite priority rule is for three scheduling targets including makespan, critical machine workload and total workload, changing the ratio of data items in the rule can adjust the ratio of the three scheduling targets. This heuristic algorithm randomly adjusts the ratio of this three scheduling targets, and slightly adjusts the ratio corresponding to the best solution, can randomly generate many excellent scheduling solutions. The algorithm' s comparison and test show that the result of this algorithm is more excellent. The algorithm runs rapidly and steadily, and can directly be used in generating initial solution in other scheduling algorithms or used in dynamic scheduling.
Institute of Scientific and Technical Information of China (English)
信宁宁; 黄宗南
2013-01-01
Reasonable job scheduling program can improve the utilization of the processing machine.The immune genetic algorithm is used to solve the flexible job-shop scheduling problem while it is more difficult.At the side of vaccine technology,according to the process timetable of the work piece,selecting the machine that processes the same process of same work piece with the shortest processing time as vaccine is proposed and vaccinate the machine code of the individual for the corresponding workpiece.Finally,an example is tested,the result shows that the method used can obtain better scheduling program and reduce machine idle time.%合理的作业调度方案能提高加工机器的利用率.针对柔性作业车间调度求解难度更大的特点,采用免疫遗传算法求解.在疫苗技术方面,提出依据工件工序加工时间表,选择同工件同工序加工时间最短的机器作为疫苗,对相应工件个体机器码接种.最后对测试案例求解,结果表明所采取的方法能够求得更好的调度方案,减少机器空闲时间.
Rolling optimization algorithm based on collision window for single machine scheduling problem
Institute of Scientific and Technical Information of China (English)
Wang Changjun; Xi Yugeng
2005-01-01
Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.
Axani, Spencer N; Kirby, Conor
2016-01-01
This paper describes an undergraduate-level physics project that incorporates various aspects of machine- and electronics-shop technical development. The desktop muon detector is a self-contained apparatus that employs plastic scintillator as a detection medium and a silicon photomultiplier for light collection. These detectors can be used in conjunction with the provided software to make interesting physics measurements. The total cost of each counter is approximately $100.
Institute of Scientific and Technical Information of China (English)
陈耀军; 姚锡凡
2009-01-01
A flexible job shop scheduling system based on multi agents and genetic algorithm is established to overcome job shop automation and optimization problems. The system is made of a management agent,a scheduling agent and machine agents,where the static scheduling is realized by genetic algorithm,while the dynamic scheduling is realized by these coordinative agents. An order is evaluated by the management agent first,and then passed to the scheduling agent with corresponding information as soon as the order is accepted. The order is optimized and decomposed by the scheduling agent with object oriented genetic algorithm,and the result is passed down to the machine agents. The machine agents act according to the information passed down by the scheduling agent，and eliminate the uncertainties in machining process by changing the order dynamically. Illustration examples show that the established system is practical,efficient and advanced.%为解决柔性车间调度自动化及优化问题,建立了基于多Agent及遗传算法的柔性车间调度系统.系统是一个由管理Agent,调度Agent及多个加工单元Agent组成,系统中通过遗传算法实现静态优化调度,而通过Agent之间的协作现实动态调度.加工任务到来时,先经管理Agent评估,接受后打包相应信息传递给调度Agent;调度Agent调用其面向对象遗传算法对任务进行优化分解并传递给各加工单元Agent;加工单元Agent根据调度Agent下达的任务进行加工,同时通过相互协调动态调整加工任务,以消除加工过程中出现的不确定性.示例运行表明所建立的系统可行,并兼有实用性,先进性和有效性.
Winston, Courtney P; Sallis, James F; Swartz, Michael D; Hoelscher, Deanna M; Peskin, Melissa F
2013-08-01
According to ecological models, the physical environment plays a major role in determining individual health behaviors. As such, researchers have started targeting the consumer nutrition environment of large-scale foodservice operations when implementing obesity-prevention programs. In 2010, the American Hospital Association released a call-to-action encouraging health care facilities to join in this movement and improve their facilities' consumer nutrition environments. The Hospital Nutrition Environment Scan (HNES) for Cafeterias, Vending Machines, and Gift Shops was developed in 2011, and the present study evaluated the inter-rater reliability of this instrument. Two trained raters visited 39 hospitals in southern California and completed the HNES. Percent agreement, kappa statistics, and intraclass correlation coefficients were calculated. Percent agreement between raters ranged from 74.4% to 100% and kappa statistics ranged from 0.458 to 1.0. The intraclass correlation coefficient for the overall nutrition composite scores was 0.961. Given these results, the HNES demonstrated acceptable reliability metrics and can now be disseminated to assess the current state of hospital consumer nutrition environments.
Ordinal scheduling problem and its asymptotically optimal algorithms on parallel machine system
Institute of Scientific and Technical Information of China (English)
TAN Zhiyi; HE Yong
2004-01-01
Focusing on the ordinal scheduling problem on a parallel machine system, we discuss the background of ordinal scheduling and the motivation of ordinal algorithms. In addition, for the ordinal scheduling problem on identical parallel machines with the objective to maximize the minimum machine load, we then give two asymptotically optimal algorithm classes which have worst-case ratios very close to the upper bound of the problem for any given m. These results greatly improve the results proposed by He Yong and Tan Zhiyi in 2002.
Institute of Scientific and Technical Information of China (English)
王小蓉; 李蓓智; 周亚勤; 杨建国; 施烁
2015-01-01
为更有效地求解柔性作业车间调度问题，提出一种混合遗传算法（蚁群-遗传算法）。在分层法的基础上，首先采用蚁群算法解决工艺路线选择问题，再通过遗传算法解决传统的作业车间调度问题。在混合遗传算法求解过程中，不断地在前期优化中获取调度知识，用于指导后期的优化过程。通过标准案例测试，验证了混合遗传算法对于解决柔性作业车间调度问题的有效性。%To solve flexible job-shop scheduling problem effectively ,a hybrid genetic algorithm ( ant colony algorithm-genetic algo-rithm) was proposed .Hierarchical approaches was used ,at first ant colony algorithm was applied to solve tackle machine assign-ment,and job-shop scheduling problem was solved by genetic algorithm .In the solution process,scheduling knowledge was learn-ed from previous optimization process and then adopted to guide the subsequent optimization process .Through the standard case experiment ,effectiveness of hybrid genetic algorithm to solve the complex flexible job-shop scheduling problem is feasible .
Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines
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Guang-Qian Zhang
2014-01-01
Full Text Available m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting time, the total machine load, the total absolute differences in completion (waiting times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem.
Institute of Scientific and Technical Information of China (English)
HOU Fu-jun; WU Qi-zong
2007-01-01
A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided.For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers.Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated.Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints.The genetic algorithm is utilized to find the best solutions in a short period of time.An illustrative numerical example is also given.Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.
An improved heuristic for one-machine scheduling with delays constraints
Institute of Scientific and Technical Information of China (English)
杜东雷; 韩继业; 陈礴
1997-01-01
An improved heuristic is proposed for one-machine scheduling problem with delay constraints,thus an open problem raised by Wikum et al.is solved.The heuristic solves the corresponding unit-execution-time problem optimally.
Online Scheduling with Delivery Time on a Bounded Parallel Batch Machine with Limited Restart
National Research Council Canada - National Science Library
Liu, Hailing; Wan, Long; Yan, Zhigang; Yuan, Jinjiang
2015-01-01
We consider the online (over time) scheduling of equal length jobs on a bounded parallel batch machine with batch capacity b to minimize the time by which all jobs have been delivered with limited restart...
1993-09-01
refinement of DISASTERTm. We can expect that the management of the constraints in USAF operations will contribute to future success in executing our global...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations ...Assignment Rules," Journal of Operations Management , 5: 27-39 (November 1984). Reynolds, Daniel E., Professor, Air Force Institute of Technology
The single-machine scheduling problems with deteriorating jobs and learning effect
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimization and maximum lateness minimization corresponding to the first and second special cases of our model under some agreeable conditions. However,corresponding to the third special case of our model, we show that the optimal schedules may be different from those of the classical version for the above objective functions.
A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem
2010-01-01
A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific p...
An effective co-evolutionary quantum genetic algorithm for the no-wait flow shop scheduling problem
Directory of Open Access Journals (Sweden)
Guanlong Deng
2015-12-01
Full Text Available This article proposes a competitive co-evolutionary quantum genetic algorithm for the no-wait flow shop scheduling problem with the criterion to minimize makespan, which is a renowned NP-hard combinatorial optimization problem. An innovative coding and decoding mechanism is proposed. The mechanism uses square matrix to represent the quantum individual and adapts the quantum rotation gate to update the quantum individual. In the algorithm framework, the store-with-diversity is proposed to maintain the diversity of the population. Moreover, a competitive co-evolution strategy is introduced to enhance the evolutionary pressure and accelerate the convergence. The store-with-diversity and competitive co-evolution are designed to keep a balance between exploration and exploitation. Simulations based on a benchmark set and comparisons with several existing algorithms demonstrate the effectiveness and robustness of the proposed algorithm.
List scheduling in a parallel machine environment with precedence constraints and setup times
Hurink, J.L.; Knust, S.
2000-01-01
We present complexity results which have influence on the strength of list scheduling in a parallel machine environment where additionally precedence constraints and sequence-dependent setup times are given and the makespan has to be minimized. We show that contrary to various other scheduling probl
List scheduling in a parallel machine environment with precedence constraints and setup times
Hurink, Johann; Knust, Sigrid
2001-01-01
We present complexity results which have influence on the strength of list scheduling in a parallel machine environment where additionally precedence constraints and sequence-dependent setup times are given and the makespan has to be minimized. We show that contrary to various other scheduling probl
A Class of Single Machine Scheduling Problems with Variable Processing Time
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, single machine scheduling problems with variableprocessing time are raised. The criterions of the problem considered are minimizing scheduling length of all jobs, flow time and number of tardy jobs and so on. The complexity of the problem is determined.
一种求解柔性作业车间调度问题的改进 DRSGA%Improved DRSGA for flexible job shop scheduling
Institute of Scientific and Technical Information of China (English)
赵小强; 何浩
2016-01-01
为了解决柔性作业车间调度问题中权重难以确定导致调度效率低的问题，该文提出了1种改进的动态随机搜索遗传算法（ DRSGA）。用功效系数法将所有工件完成时间和机器的总负载转化为单一的最小化目标。基于工序和机器分配2种交叉操作，采用1种双层染色体编码方案进行编码。采用1种可变影响空间评价方法，在保证非劣解均匀分布的同时维护了种群多样性。采用动态随机搜索（ DRS）和擂台赛法则调整关键路径中工序的排序，得到最优调度方案。将改进DRSGA与向量评估遗传算法、改进遗传算法和混合遗传算法运行结果进行比较，仿真实验结果表明，改进DRSGA求最优解所用平均时间比3种对比算法缩短了41～257 s。%To solve the problems of flexible job shop scheduling that it is difficult to determine the weight and the scheduling efficiency is poor ,an improved dynamic random search genetic algorithm ( DRSGA) is proposed here .All minimized job completing time and total machine loading are translated into single minimized objective by the efficiency coefficient method .A double-layer chromosome encoding scheme is adopted based on sequence crossover and machine allocation crossover .A variable influence space evaluation method is used to guarantee the uniform distribution of non-inferior solutions , and the diversity of population is maintained .A dynamic random search ( DRS) method and contest rules are employed to adjust key process orders and obtain the optimal scheduling scheme .The improved DRSGA is compared with the vector evaluated genetic algorithm (VEGA),the improved genetic algorithm (IMGA) and the hybrid genetic algorithm (HGA).The simulation results indicate that the average time of the optimal solution of the improved DRSGA is shorter than the other three algorithms for 41~257 s.
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韩帮军; 潘军; 范秀敏; 马登哲
2004-01-01
The recursion relation of preventive maintenance (PM) cycle is built up concerning the concept of effective age and age setback factor proposed in this paper, which illustrates the dynamic relationship between failure rate and preventive maintenance activity. And the nonlinear optimal PM policy model satisfying the reliability constraints in finite time horizon following Weibull distribution is proposed. The model built in this paper avoids the shortcoming of steady analytical PM model in infinite time horizon and can be used to aid scheduling the maintenance plan and providing decision supporting for job shop scheduling.
一种基于最小二乘支持向量机JSP调度算法%An Algorithm Based on Least Squares Support Vector Machine for Job-shop Problem
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李文超; 杨宏兵
2011-01-01
作为生产调度里面一类典型问题,Job-shop问题的求解是属于NP完全的,对于大规模Job-shop 问题的有效算法至今仍未找到.在有向图模型基础上,提出通过约束引导方式获取可行调度.提出使用最小二乘支持向量机对样本学习实现可互换工序对准确选取,以此提高调度方案质量.将求解过程中特殊算例补充到样本库进行后续训练以提高算法性能.数值仿真结果表明所提算法对于大规模Job-shop问题求解存在较好效果.%As a kind of typical problem in production scheduling, the solving of Job-shop problem belongs to NP complete and the valid algorithm hasn' t been found until now for large scale Job-shop problems. The feasible scheduling can be obtained by adding guided constraint on the basis of directed graph. A method based on least squares support vector machine is constructed to choose accurately the interchangeable operations by learning small samples to obtain the better scheduling. The performance of the algorithm presented can be improved by replenishing special problems during running as supplementary samples for the following training. The results of simulation show that the algorithm performed well for Job-shop problem.
A case study on Machine scheduling and sequencing using Meta heuristics
Directory of Open Access Journals (Sweden)
Sarfaraz ahmad
2016-01-01
Full Text Available Modern manufacturing systems are constantly increasing in complexity and become more agile in nature such system has become more crucial to check feasibility of machine scheduling and sequencing because effective scheduling and sequencing can yield increase in productivity due to maximum utilization of available resources but when number of machine increases traditional scheduling methods e.g. Johnson‟s ,rule is becomes in effective Due to the limitations involved in exhaustive enumeration, for such problems meta-heuristics has become greater choice for solving NP hard problems because of their multi solution and strong neighbourhood search capability in a reasonable time.
Modeling and Analysis of Single Machine Scheduling Based on Noncooperative Game Theory
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WANGChang-Jun; XIYu-Geng
2005-01-01
Considering the independent optimization requirement for each demander of modern manufacture, we explore the application of noncooperative game in production scheduling research,and model scheduling problem as competition of machine resources among a group of selfish jobs.Each job has its own performance objective. For the single machine, multi-jobs and non-preemptive scheduling problem, a noncooperative game model is established. Based on the model, many problems about Nash equilibrium solution, such as the existence, quantity, properties of solution space,performance of solution and algorithm are discussed. The results are tested by numerical example.
量子进化算法在柔性作业车间调度问题中的应用%Quantum Evolutionary Algorithm for Flexible Job-Shop Scheduling Problems
Institute of Scientific and Technical Information of China (English)
张建明; 顾幸生
2012-01-01
In this paper, a quantum evolutionary algorithm is proposed for flexible job-shop scheduling problems with the objective to minimize the makespan. Aiming at the features of the flexible job-shop scheduling problems, both the working-procedures-based encoding method and the machine-based decoding method are proposed. Moreover, dynamic rotation angle and jumping gens operator are utilized in the proposed algorithm. Finally, simulation results are provided to demonstrate the effectiveness and the applicability of the proposed algorithm.%针对柔性作业车间调度完工时间最小化问题，提出了一种基于量子计算的量子进化算法。根据柔性作业车间调度问题的特点，设计出基于工序编码和基于机器编码的量子编码及解码方法。引入动态旋转角策略和跳跃基因算子，并通过实例验证了算法的有效性。
Semi-Online Algorithms for Scheduling with Machine Cost
Institute of Scientific and Technical Information of China (English)
Yi-Wei Jiang; Yong He
2006-01-01
In this paper, we consider the following semi-online List Model problem with known total size. We are given a sequence of independent jobs with positive sizes, which must be assigned to be processed on machines. No machines are initially provided, and when a job is revealed the algorithm has the option to purchase new machines. By normalizing all job sizes and machine cost, we assume that the cost of purchasing one machine is 1. We further know the total size of all jobs in advance. The objective is to minimize the sum of the makespan and the number of machines to be purchased. Both non-preemptive and preemptive versions are considered. For the non-preemptive version, we present a new lower bound 6/5 which improves the known lower bound 1.161. For the preemptive version, we present an optimal semi-online algorithm with a competitive ratio of 1 in the case that the total size is not greater than 4, and an algorithm with a competitive ratio of 5/4 otherwise, while a lower bound 1.0957 is also presented for general case.
Afzalirad, Mojtaba; Rezaeian, Javad
2016-04-01
This study involves an unrelated parallel machine scheduling problem in which sequence-dependent set-up times, different release dates, machine eligibility and precedence constraints are considered to minimize total late works. A new mixed-integer programming model is presented and two efficient hybrid meta-heuristics, genetic algorithm and ant colony optimization, combined with the acceptance strategy of the simulated annealing algorithm (Metropolis acceptance rule), are proposed to solve this problem. Manifestly, the precedence constraints greatly increase the complexity of the scheduling problem to generate feasible solutions, especially in a parallel machine environment. In this research, a new corrective algorithm is proposed to obtain the feasibility in all stages of the algorithms. The performance of the proposed algorithms is evaluated in numerical examples. The results indicate that the suggested hybrid ant colony optimization statistically outperformed the proposed hybrid genetic algorithm in solving large-size test problems.
Institute of Scientific and Technical Information of China (English)
侯晓莉; 刘永; 江来臻; 高新勤
2015-01-01
In flexible job-shop scheduling with single piece and small batch production mode, the optimized objective is to reduce production costs, improve production efficiency and avoid bottleneck. This paper investigates an optimization model of Flexible Job-shop Scheduling Problems(FJSP), which aims at a comprehensive objective combined with mini-mized makespan, machine total load and single maximum load. It designs a unidimensional-encoded Particle Swarm Opti-mization(PSO)taking probability as continuous particle component. Combined with completion-time-earliest heuristic rules, these components are discretized by probability interval to solve operation sequence scheduling and machine tools selecting. After comparing and analyzing different sizes of examples, the proposed algorithm is found a distinct advantage in solving large scale problems.%以单件小批量生产方式为主的柔性车间调度中，快速得到满足低生产成本、高生产效率，避免瓶颈发生的调度方案，是调度优化算法的设计目标。就此建立了以制造期、机床总负荷和单机最大负荷为综合目标的柔性车间调度问题（Flexible Job-shop Scheduling Problems，FJSP）优化模型；设计了一种以概率值为分量的一维粒子群优化算法，通过概率区间划分将连续粒子分量离散化，结合完工时间最早启发式规则，实现工序的排序与加工机床的选取。通过不同规模算例的比较，分析结果表明该方法在求解较大规模问题时具有一定的优势。
Applying TOC Heuristics to Job Scheduling in a Hybrid Flexible Flow Shop
Directory of Open Access Journals (Sweden)
Jaime Antero Arango-Marín
2014-01-01
Full Text Available Este artículo presenta una aplicación de la heurística para la mezcla de productos de la Teoría de Restricciones, a la planificación de tareas en un Flow Shop híbrido flexible. La heurística general se adapta para el caso de máquinas paralelas no relacionadas y el algoritmo se implementa como una herramienta de programación detallada de trabajos, basada en el principio de la Teoría de Restricciones de subordinar toda la programación al recurso cuello de botella. La adaptación de la metodología a un contexto híbrido flexible, donde hay paralelismo en la etapa cuello de botella y su aplicación en una planta textil contribuye a asignar la capacidad con base en el margen de contribución. El resultado es una programación de trabajos viable enfocada en la utilidad unitaria. Aunque los resultados no alcanzan el óptimo global para este tipo de problemas, sí representan una alternativa de programación de trabajos rápida y eficaz en los contextos estudiados.
Supply Chain Scheduling with Open-shop Problem%自由作业环境下的供应链排序问题
Institute of Scientific and Technical Information of China (English)
陈荣军; 唐国春
2009-01-01
In this paper, we study an integrated scheduling model of production and dis-tribution operations. In this model, a set of jobs (i.e., customer orders) are first processed in the processing facility of open-shop machine and then delivered to the manufacturers di-rectly without intermediate inventory. The problem is to find a joint schedule of production and distribution such that an objective function that takes into account both production cost and distribution cost is optimized, where production cost is measured by the maximum delivery time and the distribution cost of a delivery shipment consists of a fixed charge and a variable cost proportional to the total distance of the route taken by the shipment. For the problem under this integrated scheduling model, we use dynamic programming to provide a heuristic algorithm with worst-case performance analysis. Finally some special cases are also introduced.%本文研究自由作业环境下的供应链排序问题,研究供应链的上游如何安排工件在自由作业机器上加工,把加工完毕的工件分批发送给下游,使得生产排序费用和发送费用总和最少.这里,生产排序费用是用工件送到时间的函数来表示;发送费用是由发送的固定费用和与运输路径有关的变化费用所组成.本文研究以工件最大送到时间为生产排序费用的自由作业供应链排序问题,在指出问题的NP困难性后,用动态规划算法构造多项式时间近似算法,并分析算法的性能比.本文最后还对特殊情形进行了讨论.
Institute of Scientific and Technical Information of China (English)
陈义保; 姚建初; 钟毅芳
2002-01-01
Identical parallel machine scheduling problem for minimizing the makespan is a very important productionscheduling problem. When its scale is large, many difficulties will arise in the course of solving identical parallel machinescheduling problem. Ant system based optimization algorithm (ASBOA) has shown great advantages in solving thecombinatorial optimization problem in view of its characteristics of high efficiency and suitability for practical applications.In this paper, an ASBOA for minimizing the makespan in identical machine scheduling problem is presented. Twodifferent scale numerical examples demonstrate that the ASBOA proposed is efficient and fit for large-scale identicalparallel machine scheduling problem for minimizing the makespan, the quality of its solution has advantages over heuristicprocedure and simulated annealing method, as well as genetic algorithm.
Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks
Directory of Open Access Journals (Sweden)
Ronald Díaz-Cazaña
2014-01-01
Full Text Available El análisis simultáneo de la programación de la producción y la s tareas de mantenimiento preventivo atrae especial atención en los investigadores debido a su gran complejidad y por ende la neces idad de encontrar métodos eficientes para resolver este tipo de problema combinatorio. Este artículo presenta un enfoque heurístico para resolver dicha problemática en plantas tipo job-shop . El método de solución incluye un modelo de programación lineal inspirado en el proble ma del Agente Vendedor, donde el tiempo de iniciación es consid erado como métrica de distancia. El método persigue obtener una secue ncia de las órdenes de producción y tareas de mantenimiento pre ventivo que reduzcan el tiempo ocioso y los retrasos simultáneamente, c umpliendo con el programa de mantenimiento. Luego de encontrar la solución óptima para cada máquina, un factor de corrección ( CF es determinado como la nueva medida de distancia. El factor CF considera la estructura inicial de solución, la utilización de las máquin as y las prioridades en los productos. De esta forma, la soluci ón final es alcanzada solucionando el modelo de programación lineal usando los valores de distancia actualizados. Finalmente, la heurístic a propuesta es aplicada en un caso de estudio real de la Industria Cubana. Los resultados experimentales indicaron una reducción significa tiva del tiempo ocioso para la compañía objeto de estudio.
Single-Machine Group Scheduling Problems with Deterioration to Minimize the Sum of Completion Times
Directory of Open Access Journals (Sweden)
Yong He
2012-01-01
Full Text Available We consider two single-machine group scheduling problems with deteriorating group setup and job processing times. That is, the job processing times and group setup times are linearly increasing (or decreasing functions of their starting times. Jobs in each group have the same deteriorating rate. The objective of scheduling problems is to minimize the sum of completion times. We show that the sum of completion times minimization problems remains polynomially solvable under the agreeable conditions.
SEMI-DEFINITE RELAXATION ALGORITHM FOR SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES
Institute of Scientific and Technical Information of China (English)
CHEN FENG; ZHANG LIANSHENG
2005-01-01
The authors present a semi-definite relaxation algorithm for the scheduling problem with controllable times on a single machine. Their approach shows how to relate this problem with the maximum vertex-cover problem with kernel constraints (MKVC).The established relationship enables to transfer the approximate solutions of MKVCinto the approximate solutions for the scheduling problem. Then, they show how to obtain an integer approximate solution for MKVC based on the semi-definite relaxation and randomized rounding technique.
ON-LINE SCHEDULING OF UNIT TIME JOBS WITH REJECTION ON UNIFORM MACHINES
Institute of Scientific and Technical Information of China (English)
Shoupeng LIU; Yuzhong ZHANG
2008-01-01
The authors consider the problem of on-line scheduling of unit execution time jobs on uniform machines with rejection penalty. The jobs arrive one by one and can be either accepted and scheduled, or be rejected. The objective is to minimize the total completion time of the accepted jobs and the total penalty of the rejection jobs. The authors propose an on-line algorithm and prove that the competitive ratio is 1/2 (2 + ) ≈ 1.86602.
A Scheduling System Based on Rules of the Machine Tools in FMS
Institute of Scientific and Technical Information of China (English)
LI De-xin; ZHAO Hua-qun; JIA Jie; LU Yan-jun
2003-01-01
In this paper, a model of the scheduling of machine tools in the flexible manufacturing line is presented by intensive analysis and research of the mathematical method of traditional scheduling. The various factors correlative with machine tools in the flexible manufacturing line are fully considered in this system. Aiming at this model, an intelligent decision system based on rules and simulation technolo-gy integration is constructed by using the OOP ( Object-Orented Programming) method, and the simula-tion experiment analysis is carried out. It is shown from the results that the model is better in practice.
Scheduling multiple orders per job with various constraints for hybrid flow shop%考虑多约束的混合流水车间MOJ调度
Institute of Scientific and Technical Information of China (English)
周炳海; 王腾
2016-01-01
With a comprehensive consideration of multiple product types and sequence-dependent setup times constraints in which processes of wafer fabrications, a scheduling model of multiple orders per job(MOJ) in a hybrid flow shop with an objective function of minimizing total completion time of the system is developed. On the basis of the descriptions, a column generation algorithm based on the job-product-machine three level disjunctive network flow is proposed. Furthermore, to improve the degradation effects of column generation algorithm, Lagrangian relaxation with sub-gradient optimization is combined into the frame of column generation algorithm, and then a modified column generation(MCG) algorithm adopting dual iteration is proposed. Finally, theory analysis and simulation experiments show that the developed MCG algorithm is valid and feasible.%考虑晶圆加工过程中的多品种和与次序相关的换模时间约束，以系统总完工时间最小为优化目标，建立混合流水车间MOJ调度模型。在此基础上，提出了基于作业-产品-机器三层析取网络流的列生成算法。为进一步改善列生成算法存在的尾效应，将基于次梯度优化的拉格朗日松弛算法嵌入列生成算法框架中，构建了采用双重迭代的改进型列生成(MCG)算法。最后，通过理论分析和仿真实验表明了MCG算法是有效、可行的。
Job Shop Scheduling Based on Improved Ant Colony Algorithm%基于改进蚁群算法的作业车间调度
Institute of Scientific and Technical Information of China (English)
王硕; 顾幸生
2012-01-01
提出了一种改进的蚁群算法,应用于经典的作业车间调度问题.编码采用基于机器的编码可以控制冗余解的数量,但同时会产生不可行解.本研究提出了控制不可行解产生的策略,同时对已出现的不可行解问题,在尽量保留种群基因的前提下,改变解的形式加以利用.在丰富了种群的多样性的同时解决了不可行解的问题.采用自适应参数法则,使参数的变化顺应种群发展过程各个阶段的需要.在一定代数的迭代后,通过改变某些参数跳出局部最优,从而达到了较好的搜索效果.%The improved ant colony algorithm is proposed and applied to solving the job shop scheduling problem. Using machine based coding, redundancy solution is perfectly limited. However, infeasible solutions can be generated by such coding method. In this paper, strategies to limit the infeasible solutions are put forward and the infeasible solution is transformed into feasible solution at the same time. Such strategies not only preserve the population in rich diversity, but also solved the problem of infeasible solutions. Adaptive parameter laws are issued to make the parameters changing every moment, which met the demands of population at all stages of evolution. After certain iterations, the algorithm may get out of local optimal value by merely changing some parameters. Finally, better searching results have been achieved.
An Improved Ant Colony Algorithm for a Single-machine Scheduling Problem with Setup Times
Institute of Scientific and Technical Information of China (English)
YE Qiang; LIU Xinbao; LIU Lin; YANG Shanglin
2006-01-01
Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutually independent and available at time zero. The machine processes the jobs sequentially and it is not idle if there is any job to be processed. The operation of each job cannot be interrupted. The machine cannot process more than one job at a time. A setup time is needed if the machine switches from one type of job to another. The objective is to find an optimal schedule with the minimal total jobs' completion time. While the sum of jobs' processing time is always a constant, the objective is to minimize the sum of setup times. Ant colony optimization (ACO) is a meta-heuristic that has recently been applied to scheduling problem. In this paper we propose an improved ACO-Branching Ant Colony with Dynamic Perturbation (DPBAC) algorithm for the single-machine scheduling problem. DPBAC improves traditional ACO in following aspects: introducing Branching Method to choose starting points; improving state transition rules; introducing Mutation Method to shorten tours; improving pheromone updating rules and introducing Conditional Dynamic Perturbation Strategy. Computational results show that DPBAC algorithm is superior to the traditional ACO algorithm.
Directory of Open Access Journals (Sweden)
Farahmand-Mehr Mohammad
2014-01-01
Full Text Available In this paper, a hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Since few works have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms. This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing. A mixed integer linear programming (MILP model is proposed to minimize the makespan. Since this problem is known as NP-Hard class, a meta-heuristic algorithm, named Genetic Algorithm (GA, and three heuristic algorithms (Johnson, SPTCH and Palmer are proposed. Numerical experiments of different sizes are implemented to evaluate the performance of presented mathematical programming model and the designed GA in compare to heuristic algorithms and a benchmark algorithm. Computational results indicate that the designed GA can produce near optimal solutions in a short computational time for different size problems.
Wei, Xiu; Zhang, Wenqiang; Weng, Wei; Fujimura, Shigeru
This paper proposed a multi-objective local search procedure (MOLS). It is combined with NSGA-II for solving bi-criteria PFSP with the objectives of minimizing makespan and maximum tardiness. Utilizing the properties of active blocks for flow shop scheduling problem, neighborhood structures MOINS (multi-objective insertion) and MOEXC (multi-objective exchange) are designed in order to improve efficiency of perturbation. Any perturbation based on MOINS and MOEXC takes effect on different criteria simultaneously. The original idea of MOLS is systematic change neighborhoods in the local search procedure. The search direction of MOLS on an individual is naturally guided by interaction of MOINS and MOEXC. Moreover, there is no need to set parameters in MOLS. The MOLS combined with popular multi-objective evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm-II) is called as “NSGA-II-MOLS”. To illustrate the efficacy of proposed approach, four different scaled problems are used to test performance of NSGA-II-MOLS. The numerous comparisons show efficacy of NSGA-II-MOLS is better than most of algorithms even with the same number of individual evaluations and parameters setting.
A Genetic Algorithm for Single Machine Scheduling with Fuzzy Processing Time and Multiple Objectives
Institute of Scientific and Technical Information of China (English)
吴超超; 顾幸生
2004-01-01
In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.
Directory of Open Access Journals (Sweden)
Wei-min Ma
2015-01-01
Full Text Available We consider parallel-machine scheduling problems with past-sequence-dependent (psd delivery times and aging maintenance. The delivery time is proportional to the waiting time in the system. Each machine has an aging maintenance activity. We develop polynomial algorithms to three versions of the problem to minimize the total absolute deviation of job completion times, the total load, and the total completion time.
Multiobjective Genetic Algorithm-Based Method for Job Shop Scheduling Problem%基于遗传算法的多目标车间调度问题的研究∗
Institute of Scientific and Technical Information of China (English)
张腾飞; 马跃; 胡毅; 安涛; 王帅; 郭安
2016-01-01
文章讨论了一个多目标车间调度问题( JSP)。在JSP问题中我们考虑一个具有n个工件和m台机器的生产线，每道工序在不同的机器上完成且有各自的持续时间。 JSP调度问题的目标是在所有工件的工序在m台机器上加工且不冲突的前提下找到一个最短的总调度时间。该文通过使用遗传算法来找到作业调度问题的最优方案。文中通过使用11种不同规格的标准测试用例来测试算法的性能。实验结果表明，实验的运行结果满足了调度要求，进一步证明了遗传算法的有效性和实用性。%In this paper we consider a multiobjective job shop scheduling problem ( JSP) . In JSP we consid-er m machines on a production line with n defined jobs, each job consists of different tasks for different ma-chines and each of them has its own duration. The goal is to find the shortest scheduling in which none of the jobs' tasks collide on all of the m machines. This part uses the Genetic Algorithm to find the optimal so-lution for the job scheduling problem. Performance of the proposed heuristic is evaluated through computa-tional experiments on 11 different sizes benchmarks. The result of the test shows the efficiency of search is increased and the convergence is improved in shop scheduling with the Genetic Algorithm.
Institute of Scientific and Technical Information of China (English)
初红艳; 李风光; 邓颖辉; 费仁元; 方娟
2011-01-01
针对作业车间批量生产的调度及仿真问题,根据等分批原则,建立分批调度的数学模型,之后把分好的子批看成一个新的工件,对其重新进行编号并计算新的加工时间,利用遗传算法良好的全局搜索性能和禁忌搜索算法优良的局部搜索性能,引入混合优化算法进行生产调度;然后利用OpenGL建立生产车间以及加工设备的三维模型,并赋予场景初始化、设备初始化功能和视点移动、模型整体变换功能;最后利用分批调度计算得出的最终结果,根据工件中每个工序的开始加工时间和加工消耗时间,设置触发器和定时器,并通过读取相应的加工设备编号确定加工的位置坐标,进行实时地调度仿真.%Aimed at solving the batch production of job-shop scheduling and simulation problems, a model of scheduling in batches is created based on the equal batch principle. We consider the distributed subbatch as a new work piece, renumber it, compute the time needed to process, and make a production scheduling, where we utilize the superb overall search performance of the Genetic Algorithm and the excellent local search performance of the Tabu search algorithm. Then the three-dimensional model of job -shop and machines is established by OpenGL. Giving it an initialized function of scene and machine,function about moving viewpoint and the overall changes of model. At last, according to the start times and end times of each process set trigger and timer, we acquire position of working by the number of machine to scheduling simulation.
Institute of Scientific and Technical Information of China (English)
张维存; 康凯
2012-01-01
提出一种求解柔性作业车间成组调度FGJSS(flexible grouped job-shop scheduling)问题的蚁群粒子群求解算法.算法采用主从递阶形式,主级为蚁群优化算法,选择零件加工设备；从级为粒子群优化算法,在主级零件加工设备约束下优化设备作业排序以实现流通时间最小的目标.算法中,以工序加工时间和设备承载的作业族数为启发式信息设计蚂蚁在工序可用设备间转移概率；以粒子向量优先权值和作业族号为依据设计解码方法实现设备上的成组作业排序.最后,通过仿真实验,验证了该算法的有效性.%A hybrid algorithm of ant colony optimisation and particle swarm optimisation is proposed to solve the flexible grouped job-shop scheduling problem. The algorithm is formulated in a form of hierarchical master-slave structure. The ant colony optimisation is performed at master level to select equipments for parts machining, while the particle swarm optimisation is carried out at the slave level to optimise job-scheduling of the equipments in constrained condition of equipments for parts machining at master level to achieve the target of minimized circulation time. In ihe algorithm, the processing time of working procedure and the number of job groups the equipments loaded are used as the heuristic information to design the transfer probability of ant between the available machines of working procedure. The particle vector priority values and the jobs group number are employed as the base to design decoding method in order to implement grouped job scheduling of the equipments. In the end, the validity of the proposed algorithm is verified through simulative experiment.
Research on multi-agent-based flexible job-shop scheduling%基于多Agent的柔性作业车间调度研究
Institute of Scientific and Technical Information of China (English)
潘颖; 孙伟; 马跃; 马沁怡
2011-01-01
Aiming at multi-objective flexible job-shop scheduling problem, job-shop scheduling model based on multi-agent is constructed. Exchange and coordination mechanism between agents is also researched. What＇s more, an improved genetic algorithm is presented and encapsulated in strategy agent. Through the improvement of coding rules, decoding algorithm, crossover and mutation operators, the practicality and optimization effect of scheduling optimization algorithm are enhanced, such methods realize multi-objective dynamic scheduling and improve system＇ s adaptability and robustness. The example in certain enterprise workshop testifies that the scheduling model can satisfy high efficient and stable demands of job-shop scheduling.%针对多目标柔性作业车间调度问题，构造了基于多Agent的车间调度模型，研究了多Agent之间的交换协调机制．提出一种改进遗传算法并封装在策略Agent中，通过对编码规则、解码算法与交叉、变异算子进行改进，提高了调度优化算法的实用性和优化效果，实现了多目标动态调度，提高了系统的适应性和健壮性．某企业车间应用实例证明其可以满足车间调度高效、稳定的要求．
Multi-bottleneck scheduling algorithm for large-scale Job Shop%大规模作业车间多瓶颈调度算法
Institute of Scientific and Technical Information of China (English)
翟颖妮; 孙树栋; 杨宏安; 牛刚刚; 袁宗寅
2011-01-01
To solve Large-Scale Job Shop Scheduling Problems(LSJSSP), a multi-bottleneck scheduling algorithm based on rolling horizon decomposition was proposed. This algorithm adopted critical path method to detect bottlenecks, and solved the LSJSSP by decomposing it into a series of sub-problems according to the process routines of the jobs. In the construction process of the sub-problems, the idea of load balanced distribution was proposed to distribute the load of each job in the sub-problems and to realize the stability of the solution process. In the solving process of the sub-problems. The bottleneck operations were scheduled by genetic algorithm, and the non-bottleneck operations were scheduled by dispatching rules according to the principle of "bottleneck machines lead non-bottleneck machines" in Theory of Constraints (TOC), the solving efficiency was improved. Through re-optimization process for the overlapping operations in the adjacent sub-problems and the strategy of evaluating the chromosome's fitness by the global solution, limitations of the decomposition and solving process were avoided, and the solution quality was improved. Simulation results showed that the proposed algorithm for LSJSSP was with satisfactory solution efficiency and quality.%针对大规模作业车间调度问题,提出一种基于滚动窗分解的多瓶颈调度算法.该算法基于关键路径法进行多瓶颈机器的识别,沿时域将大规模调度问题分解为多个子问题进行求解.在子问题创建过程中,提出负荷均衡分布的规则,使得各工件在各子问题中的负荷均匀分布,以实现算法求解过程的稳定性；在子问题的求解过程中,遵循约束理论中瓶颈机主导非瓶颈机的原则,采用瓶颈工序最优化调度、非瓶颈工序采用分派规则快速调度的调度策略,提高算法的求解效率；通过相邻子问题间的工序衔接再优化过程,以及全局解评价子问题染色体适应度值策略,有效避
基于TSAPO的柔性作业车间计划和调度%Flexible Job Shop Planning and Scheduling Based on TSAPO
Institute of Scientific and Technical Information of China (English)
李莉; 周春楠
2012-01-01
To make the multi-objective flexible job shop planning and scheduling more accord with the dynamic changing. Flexible Job Shop(FJS) planning model with dynamic feedback and Two Stages Ant Particle Optimization(TSAPO) algorithm are proposed. The update and feedback of practical product data are realized by dynamic monitoring. Through the decomposition of optimization objects by two stages, scheduling algorithm with feedback is designed. Experimental result shows the algorithm has better optimization effect in solving multi-objective flexible job shop scheduling problem.%为使多目标柔性作业车间计划与调度的制定更适合实际生产的动态变化,提出增加动态反馈的闭环柔性作业车间计划模型及二阶式蚁群粒子群混合优化算法TSAPO.通过增加动态监视功能,及时更新和反馈实际生产数据.利用对优化目标的二阶段分解,设计带有反馈机制的调度算法.实验结果证明,该算法在求解多目标柔性作业车间调度问题中具有较好的优化效果.
A Note on Two-Agent Scheduling with Resource Dependent Release Times on a Single Machine
Directory of Open Access Journals (Sweden)
Peng Liu
2015-01-01
Full Text Available We consider a scheduling problem in which both resource dependent release times and two agents exist simultaneously. Two agents share a common single machine, and each agent wants to minimize a cost function dependent on its own jobs. The release time of each A-agent’s job is related to the amount of resource consumed. The objective is to find a schedule for the problem of minimizing A-agent’s total amount of resource consumption with a constraint on B-agent’s makespan. The optimal properties and the optimal polynomial time algorithm are proposed to solve the scheduling problem.
Cost-Minimizing Scheduling of Workflows on a Cloud of Memory Managed Multicore Machines
Grounds, Nicolas G.; Antonio, John K.; Muehring, Jeff
Workflows are modeled as hierarchically structured directed acyclic graphs in which vertices represent computational tasks, referred to as requests, and edges represent precedent constraints among requests. Associated with each workflow is a deadline that defines the time by which all computations of a workflow should be complete. Workflows are submitted by numerous clients to a scheduler that assigns workflow requests to a cloud of memory managed multicore machines for execution. A cost function is assumed to be associated with each workflow, which maps values of relative workflow tardiness to corresponding cost function values. A novel cost-minimizing scheduling framework is introduced to schedule requests of workflows so as to minimize the sum of cost function values for all workflows. The utility of the proposed scheduler is compared to another previously known scheduling policy.
Preemptive Semi-online Algorithms for Parallel Machine Scheduling with Known Total Size
Institute of Scientific and Technical Information of China (English)
Yong HE; Hao ZHOU; Yi Wei JIANG
2006-01-01
This paper investigates preemptive semi-online scheduling problems on m identical parallel machines, where the total size of all jobs is known in advance. The goal is to minimize the maximum machine completion time or maximize the minimum machine completion time. For the first objective,we present an optimal semi-online algorithm with competitive ratio 1. For the second objective, we show that the competitive ratio of any semi-online algorithm is at least 2m-3/m-1 for any m ＞ 2 and presentoptimal semi-online algorithms for m = 2,3.
A Kind of Supply Chain Scheduling with Open-shop Problem%一类自由作业供应链排序的研究
Institute of Scientific and Technical Information of China (English)
陈荣军; 唐国春
2011-01-01
In this paper, we study an integrated scheduling model of production and distribution operations.In this model, a set of jobs(i.e., customer orders) are first processed in the processing facility of open-shop machine and then delivered to the manufacturers directly without intermediate inventory.The problem is to find a joint schedule of production and distribution so that an objective function that takes into account both productions cost and distribution cost is optimized, where production cost is measured by the sum of weighted delivery times and the distribution cost of a delivery shipment consists of a fixed charge and a variable cost proportional to the total distance of the route taken by the shipment.For the problem under an assumption that job weights are a-greeable, we use dynamic programming to provide a heuristic algorithm with worst-case performance analysis.Finally some special cases are also introduced.%本文研究一类集成工件生产和发送的排序模型.在该模型中,供应链的上游首先将工件安排在自由作业机器上加工,然后把加工完毕的工件分批发送给下游.问题是寻找生产和发送相连的排序,使得生产排序费用和发送费用总和最少.这里,生产排序费用是以工件带权送到时间和表示;发送费用由固定费用和与运输路径有关的变化费用组成.在指出问题的NP困难性后,本文用动态规划算法构造了一致条件下的多项式时间近似算法,并分析算法的性能比.本文最后还讨论了该问题的其它情形.
Dominance rules for single machine schedule with sequence dependent setup and due date
Institute of Scientific and Technical Information of China (English)
Xiaochuan LUO; Xiao LIU; Chengen WANG; Zhen LIU
2005-01-01
Some dominance rules are proposed for the problems of scheduling N jobs on a single machine with due dates,sequence dependent setup times and no preemption. Two algorithms based on Ragatz's branch and bound scheme are developed including the dominance rules where the objective is to minimize the maximum tardiness or the total tardiness. Computational experiments demonstrate the effectiveness of the dominance rules.
APPROXIMATION SCHEMES FOR SCHEDULING A BATCHING MACHINE WITH NONIDENTICAL JOB SIZE
Institute of Scientific and Technical Information of China (English)
Xianzhao ZHANG; Zengxia CAI; Yuzhong ZHANG; Zhigang CAO
2007-01-01
In this paper we study the problem of scheduling a batching machine with nonidentical job sizes. The jobs arrive simultaneously and have unit processing time. The goal is to minimize the total completion times. Having shown that the problem is NP-hard, we put forward three approximation schemes with worst case ratio 4, 2, and 3/2, respectively.
A Heuristic Algorithm for the Two-Machine Flowshop Group Scheduling Problem
Institute of Scientific and Technical Information of China (English)
王秀利; 吴惕华
2002-01-01
This paper presents the two-machine flowshop group scheduling problem with the optimal objective ofmaximum lateness. A dominance rule within group and a dominance rule between groups are established. Thesedominance rules along with a previously established dominance rule are used to develop a heuristic algorithm.Experimental results are given and analyzed.
Scheduling jobs and a variable maintenance on a single machine with common due-date assignment.
Wan, Long
2014-01-01
We investigate a common due-date assignment scheduling problem with a variable maintenance on a single machine. The goal is to minimize the total earliness, tardiness, and due-date cost. We derive some properties on an optimal solution for our problem. For a special case with identical jobs we propose an optimal polynomial time algorithm followed by a numerical example.
Mathematical programming approach to multidimensional mechanism design for single machine scheduling
Duives, Jelle; Uetz, Marc
2011-01-01
We consider an optimal mechanism design problem for single machine scheduling that has been proposed by Heydenreich et al. in 2008. There, an example was presented to show that the 2-dimensional mechanism design problem does not satisfy a condition called IIA - independence of irrelevant alternative
Institute of Scientific and Technical Information of China (English)
ZHANG Feng; CHEN Feng; TANG Guochun
2004-01-01
Scheduling unrelated parallel machines with controllable processing times subject to release times is investigated. Based on the convex quadratic programming relaxation and the randomized rounding strategy, a 2-approximation algorithm is obtained for a special case with the all-or-none property and then a 3-approximation algorithm is presented for general problem.
Institute of Scientific and Technical Information of China (English)
周炳海
2016-01-01
In order to improve the scheduling efficiency of photolithography, bottleneck process of wafer fabrications in the semiconductor industry, an effective estimation of distribution algorithm is pro-posed for scheduling problems of parallel litho machines with reticle constraints, where multiple reti-cles are available for each reticle type.First, the scheduling problem domain of parallel litho ma-chines is described with reticle constraints and mathematical programming formulations are put for-ward with the objective of minimizing total weighted completion time.Second, estimation of distribu-tion algorithm is developed with a decoding scheme specially designed to deal with the reticle con-straints.Third, an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally, simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.
UNBOUNDED BATCH SCHEDULING WITH A COMMON DUE WINDOW ON A SINGLE MACHINE
Institute of Scientific and Technical Information of China (English)
Hongluan ZHAO; Guojun LI
2008-01-01
The common due window scheduling problem with batching on a single machine is dealt with to minimize the total penalty of weighted earliness and tardiness. In this paper it is assumed that a job incurs no penalty as long as it is completed within the common due window. It is the first time for the due window scheduling to be extended to this situation so that jobs can be processed in batches. An unbounded version of batch scheduling is also considered. Hence, jobs, no matter how many there are, can be processed in a batch once the machine is free. For two cases that the location of due window is either a decision variable or a given parameter, polynomial algorithms are proposed based on several optimal properties.
A fuzzy modeling for single machine scheduling problem with deteriorating jobs
Directory of Open Access Journals (Sweden)
Mohammad Mahavi Mazdeh
2010-06-01
Full Text Available This paper addresses a bi-criteria scheduling problem with deteriorating jobs on a single machine. We develop a model for a single machine bi-criteria scheduling problem (SMBSP with the aim of minimizing total tardiness and work in process (WIP costs. WIP cost increases as a job passes through a series of stages in the production process. Due to the uncertainty involved in real-world scheduling problems, it is sometimes unrealistic or even impossible to acquire exact input data. Hence, we consider the SMBSP under the hypothesis of fuzzy L-R processing time's knowledge and fuzzy L-R due date. The effectiveness of the proposed model and the denoted methodology is demonstrated through a test problem.
Directory of Open Access Journals (Sweden)
Chunfeng Liu
2013-01-01
Full Text Available The paper presents a novel hybrid genetic algorithm (HGA for a deterministic scheduling problem where multiple jobs with arbitrary precedence constraints are processed on multiple unrelated parallel machines. The objective is to minimize total tardiness, since delays of the jobs may lead to punishment cost or cancellation of orders by the clients in many situations. A priority rule-based heuristic algorithm, which schedules a prior job on a prior machine according to the priority rule at each iteration, is suggested and embedded to the HGA for initial feasible schedules that can be improved in further stages. Computational experiments are conducted to show that the proposed HGA performs well with respect to accuracy and efficiency of solution for small-sized problems and gets better results than the conventional genetic algorithm within the same runtime for large-sized problems.
Good, James D.; DeVore, Mary Ann
This model has been designed for use by Missouri secondary schools in attracting females and males into nontraditional occupational programs. The research-based strategies are intended for implementation in the following areas: attracting females into building trades, electronics, machine shop, and welding; and males into secondary health…
Optimal Preemptive Online Algorithms for Scheduling with Known Largest Size on Two Uniform Machines
Institute of Scientific and Technical Information of China (English)
Yong HE; Yi Wei JIANG; Hao ZHOU
2007-01-01
In this paper, we consider the semi-online preemptive scheduling problem with known largest job sizes on two uniform machines. Our goal is to maximize the continuous period of time (starting from time zero) when both machines are busy, which is equivalent to maximizing the minimummachine completion time if idle time is not introduced. We design optimal deterministic semi-onlinealgorithms for every machine speed ratio s ∈ [1, ∞), and show that idle time is required to achieve the optimality during the assignment procedure of the algorithm for any s (s2 + 3s + 1)/(s2 + 2s + 1).The competitive ratio of the algorithms is (s2 + 3s + 1)/(s2 + 2s + 1), which matches the randomized lower bound for every s ≥ 1. Hence randomization does not help for the discussed preemptive scheduling problem.
Institute of Scientific and Technical Information of China (English)
黄瑜岳; 李克清; 郑晓峰
2013-01-01
To solve the problem of multi-objective flexible job shop scheduling with many varieties and large amount of products, a novel multi-object heuristic scheduling algorithm base on equal amount of batches is proposed.The algorithm, which considered the constraint of work-shifts in factory, could obtain three scheduling results by using EDD, SPT and OSPT batch selecting strategy in the condition of machine selecting strategy using FIFS.As a result, the decision maker could choose the most appropriate scheduling solution according to the performance of the three kinds of scheduling results.Finally, An example showed that the algorithm is efficient and feasible.%为解决产品种类多、中小批量的多目标柔性作业车间调度问题,提出了一种基于等量分批方法的多目标柔性分批启发式调度算法.考虑了实际生产中的班次作息时间等约束,采用FIFS与EDD、SPT及OSPT策略相结合的多种分派规则,使得算法在优先调度空闲机床的情况下,根据不同的分派策略得出短批次优先、短订单优先、交货时间优先的三种调度结果,决策者可根据三种调度结果的性能选择最适合的调度方案.实例计算结果表明,该算法是高效、可行的.
Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs
Directory of Open Access Journals (Sweden)
Wenming Cheng
2012-01-01
Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.
INVASIVE WEED OPTIMISATION ALGORITHM FOR JOB SHOP SCHEDULING%作业车间调度问题的杂草优化算法求解
Institute of Scientific and Technical Information of China (English)
黄霞; 叶春明; 包晓晓
2016-01-01
This paper introduces an invasive weed optimisation algorithm aimed at solving job shop scheduling problem.In this algorithm, the offspring diffuses around the parent individuals in the way of normal distribution,combining the global search and local search and adjusting different strength of both according to the number of iterations.Simulation tests are carried out through typical examples,and in repeated experiments the parameters of the algorithm are corrected.Test results demonstrate the feasibility and effectiveness of IWO in solving job shop scheduling problem,it is superior to the firefly algorithm and basic particle swarm optimisation,and is an effective approach for solving production scheduling problem.%针对作业车间调度问题JSP（Job-shop scheduling problem），提出一种入侵式杂草优化算法。该算法中，子代以正态分布方式在父代个体周围扩散，兼顾全局搜索和局部搜索，并根据迭代次数不同对二者强度进行调节。通过典型算例进行仿真试验，并在反复实验中对算法参数进行修正。测试结果表明杂草算法求解作业车间调度问题的可行性和有效性，优于萤火虫算法和基本粒子群算法，是解决生产调度问题的一种有效方法。
Directory of Open Access Journals (Sweden)
Sekhri Larbi
2014-12-01
Full Text Available The optimal resources allocation to tasks was the primary objective of the research dealing with scheduling problems. These problems are characterized by their complexity, known as NP-hard in most cases. Currently with the evolution of technology, classical methods are inadequate because they degrade system performance (inflexibility, inefficient resources using policy, etc.. In the context of parallel and distributed systems, several computing units process multitasking applications in concurrent way. Main goal of such process is to schedule tasks and map them on the appropriate machines to achieve the optimal overall system performance (Minimize the Make-span and balance the load among the machines. In this paper we present a Time Petri Net (TPN based approach to solve the scheduling problem by mapping each entity (tasks, resources and constraints to correspondent one in the TPN. In this case, the scheduling problem can be reduced to finding an optimal sequence of transitions leading from an initial marking to a final one. Our approach improves the classical mapping algorithms by introducing a control over resources allocation and by taking into consideration the resource balancing aspect leading to an acceptable state of the system. The approach is applied to a specific class of problems where the machines are parallel and identical. This class is analyzed by using the TiNA (Time Net Analyzer tool software developed in the LAAS laboratory (Toulouse, France.
Minimizing the total tardiness for the tool change scheduling problem on parallel machines
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Antonio Costa
2016-04-01
Full Text Available This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.
2010-10-01
... operator's seat shall be replaced or repaired within 24 hours or by the start of the machine's next tour of duty, whichever is later. The machine may be operated for the remainder of the operator's tour of duty... roadway maintenance machines; inspection for compliance and schedule for repairs. (a) The operator of...
Managing magnetic resonance imaging machines: support tools for scheduling and planning.
Carpenter, Adam P; Leemis, Lawrence M; Papir, Alan S; Phillips, David J; Phillips, Grace S
2011-06-01
We devise models and algorithms to estimate the impact of current and future patient demand for examinations on Magnetic Resonance Imaging (MRI) machines at a hospital radiology department. Our work helps improve scheduling decisions and supports MRI machine personnel and equipment planning decisions. Of particular novelty is our use of scheduling algorithms to compute the competing objectives of maximizing examination throughput and patient-magnet utilization. Using our algorithms retrospectively can help (1) assess prior scheduling decisions, (2) identify potential areas of efficiency improvement and (3) identify difficult examination types. Using a year of patient data and several years of MRI utilization data, we construct a simulation model to forecast MRI machine demand under a variety of scenarios. Under our predicted demand model, the throughput calculated by our algorithms acts as an estimate of the overtime MRI time required, and thus, can be used to help predict the impact of different trends in examination demand and to support MRI machine staffing and equipment planning.
Institute of Scientific and Technical Information of China (English)
刘爱军; 杨育; 邢青松; 陆惠; 张煜东
2011-01-01
It was difficult to obtain the optimal solution in multiobjective fuzzy flexible Job Shop scheduling by using common genetic algorithms.To solve this problem,based on the consideration of due date obeyed fuzzy time window distribution,a multiobjective fuzzy flexible Job Shop scheduling model was presented.It was aimed at maximize customer satisfaction and minimize completion time.Besides,crossbar collaborative multi-group genetic algorithm was proposed.In this algorithm,multiple initial populations were generated based on process and machine two layers coding mode.And then,migration and sharing of excellent individuals was achieved by competition among various groups.The simulation results of three classical Job Shop scheduling problems and instance demonstrated that the proposed algorithm could effectively overcome the stagnation and improve global search capability.Comparing to other algorithms,the optimal solution or near optimal solution obtained by the proposed algorithm was better.%针对多目标模糊柔性车间调度求解过程中普通遗传算法较难取得最优解的问题,以极大化客户满意度和最小化完工时间为目标,在考虑工件交货期服从模糊时间窗分布等约束条件的基础上,构建了多目标模糊柔性作业车间调度模型,并提出了纵横协同的多种群遗传算法。该算法首先基于工序和机器的两层编码方式产生多个初始种群,然后各种群之间通过相互竞争实现优秀个体的迁移共享,最后通过三个经典调度问题和实例仿真验证了该算法能有效克服停滞现象和增强全局搜索能力,并且与其他算法相比,该算法能够求得更好的最优解或近似最优解。
Optimal online algorithms for scheduling on two identical machines under a grade of service
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service (GoS) levels, so each job and machine are labelled with the GoS levels, and each job can be processed by a particular machine only when its GoS level is no less than that of the machine. The goal is to minimize the makespan. For non-preemptive version, we propose an optimal online algorithm with competitive ratio 5/3. For preemptive version, we propose an optimal online algorithm with competitive ratio 3/2.
Extension of the Dynasearch to the Two-Machine Permutation Flowshop Scheduling Problem
Tanaka, Shunji
The purpose of this study is to construct a solution algorithm for the two-machine permutation flowshop problem based on the dynasearch. The dynasearch is an efficient local search algorithm that employs a special neighborhood structure called dynasearch swap neighborhood. Its primary advantage is that the neighborhood of a solution can be explored in polynomial time although it is composed of an exponential number of solutions. The dynasearch for machine scheduling was originally developed for the single-machine total weighted tardiness problem. Then, it was extended to the problem with idle time and setup times. This study further extends the dynasearch to the two-machine permutation flowshop problem and its effectiveness is examined by numerical experiments for both total weighted tardiness and total weighted earliness-tardiness objectives.
Institute of Scientific and Technical Information of China (English)
袁坤; 朱剑英; 鞠全勇; 王有远
2006-01-01
In the flexible job-shop scheduling problem (FJSP), each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation (GOSR) and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm (IOGA) and its process are described.Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.%柔性作业车间调度(FJSP)中,在将任务按顺序分配到各机床前,首先要为任务选择加工机床.为求解多目标FJSP,本文在分析该问题特点的基础上,提出了一种面向甘特图的串编码(GORS)及相应的的遗传算法算子的基本操作.提出了集成算子遗传算法,并给出了其具体实现.文献算例的实验及与国际最近研究成果比较表明,该算法减小了目标参数值即生产周期、最大机床负载和总的机床负载.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs.The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.
Scheduling Jobs with Maintenance Subject to Load-Dependent Duration on a Single Machine
Directory of Open Access Journals (Sweden)
Yawei Qi
2015-01-01
Full Text Available This paper investigates a scheduling problem on a single machine with maintenance, in which the starting time of the maintenance is given in advance but its duration depends on the load of the machine before the maintenance. The goal is to minimize the makespan. We formulate it as an integer programming model and show that it is NP-hard in the ordinary sense. Then, we propose an FPTAS and point out that a special case is polynomial solvable. Finally, we design fast heuristic algorithms to solve the scheduling problem. Numerical experiments are implemented to evaluate the performance of the proposed heuristic algorithms. The results show the proposed heuristic algorithms are effective.
Institute of Scientific and Technical Information of China (English)
屈国强; 李俊芳; 侯东亮
2012-01-01
以NP-难的最小化时间表长为目标的混合流水车间调度问题为研究对象.把工件在第1阶段开始加工的排序问题转化为旅行商问题,采用蚁群系统求得初始排序；在第1阶段后各阶段采用工件先到先服务规则选择工件、最先空闲机器优先规则选择机器以构建初始工件的机器指派与排序；充分利用已知的机器布局和工件加工时间特点,确定工件加工瓶颈阶段,并以此为基础对工件的机器指派与排序进行改进.用Carlier和Neron设计的Benchmark算例仿真后与著名的NEH算法比较,表明这种算法是有效的.%The scheduling problem of hybrid flow shop with makespan as objective is discussed. In a hybrid flow shop, there are multiple machines at each stage and its scheduling problem is known to be NP-hard. A new method is proposed in this paper. By the proposed method, for the first stage, the job sequencing is formulated as a traveling salesman problem and the ant colony method is used to solve it. For the following stages, dispatching rules, such as first come first served and first available machine first, are used to obtain an initial solution. Then, the initial solution is improved by identifying the bottleneck stage in taking the advantage of knowledge about job processing times and machine configurations. To evaluate the performance of the proposed algorithm, it is tested by using the Carlier and Neron's benchmark problems. It is shown that proposed method is effective and outperforms the well-known Nawaz-Enscore-Ham (NEH) heuristic.
THE SINGLE MACHINE STOCHASTIC SCHEDULING WITH THE WEIGHTED JOB TARDINESS MINIMIZATION
Institute of Scientific and Technical Information of China (English)
Dequan YUE; Fengsheng TU
2004-01-01
This paper considers scheduling n jobs on a single machine where the job processing times and due dates are independent random variables with arbitrary distribution functions. We consider the case that the weighted job tardiness in expectation is minimized. It is assumed that job's due dates are compatible with processing times and weights. We show that the jobs should be sequenced in decreasing stochastic order of their due dates.
Number of Tardy Jobs of Single Machine Scheduling Problem with Variable Processing Time
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The number of tardy jobs of the single machine scheduling problem with a variable processing time is studied in accordance with the published instances of traffic transportation management engineering. It is proved by 3-partition problem that if the problem is of ready time and common deadline-constrained, its complexity is NP-hard in the strong sense. Finally, a polynomial algorithm for solving unit processing time and common deadline problems is proposed.
Institute of Scientific and Technical Information of China (English)
于善; 袁逸萍; 李晓娟; 马会玲
2015-01-01
On the research of the key technology and realization method of job-shop scheduling system based on genetic algorithm in MATLAB ,a kind implementation method of job-shop scheduling system based on MATLAB/GUI is put forward .Job-shop pro-blems ,job-shop genetic algorithm and job-shop scheduling system are established by mathematical description .And combined with the research of the technology of MATLAB/GUI and data exchange technology between MATLAB and Excel ,a convenient and practical job-shop scheduling system is developed .The effectiveness and practicability of the scheduling system are demonstrated by an example of job-shop scheduling .%针对MATLAB环境下基于遗传算法的作业车间调度系统的关键技术和实现方法进行了研究 ,提出一种基于MATLAB/GUI的作业车间调度系统的实现方法.对作业车间问题、作业车间遗传算法思想、作业车间调度系统建立进行描述 ,并结合对MATLAB/GUI技术、MATLAB与Excel数据交换技术的研究开发了一种方便、实用的作业车间调度系统.通过实例验证了调度系统的有效与实用性.
Path flexible job shop scheduling based on genetic algorithm%基于遗传算法的路径柔性作业车间调度优化
Institute of Scientific and Technical Information of China (English)
谢皓; 应保胜; 袁波
2012-01-01
In light of the diversity of processing route in the flexible job shop, a scheduling approach is presented for the minimized processing time, and genetic algorithm is employed for solving the problem. The approach uses a two-dimensional matrix coding methods that bases itself on production process and machine coding. A new operation is designed to change the extra information to expand the search range during the genetic evolution process, and analysis is carried out of crossover and mutation operators. The effectiveness of the algorithm is verified by computing results with a scheduling problem.%针对柔性作业车间调度问题中加工路径的多样性,以最长完工时间最短化为优化目标建立调度模型,采用遗传算法进行模型求解.提出一种基于工序与机器编码相融合的二维矩阵编码方法.在遗传进化过程中,通过附加方法产生新个体以扩展搜索范围,对交叉和变异算子进行了分析.通过算例验证了该算法的可行性和有效性.
Deterministic and randomized scheduling problems under the lp norm on two identical machines
Institute of Scientific and Technical Information of China (English)
LIN Ling; TAN Zhi-yi; HE Yong
2005-01-01
Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in large-size computing, task arrangement in flexible manufacturing systems, etc., are multiprocessor scheduling problem. In the traditional parallel machine scheduling problems, it is assumed that the problems are considered in offline or online environment. But in practice, problems are often not really offline or online but somehow in-between. This means that, with respect to the online problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi-online ones. In this paper, the semi-online problem P2|decr|lp (p＞1) is considered where jobs come in non-increasing order of their processing times and the objective is to minimize the sum of the lp norm of every machine's load. It is shown that LS algorithm is optimal for any lp norm, which extends the results known in the literature. Furthermore, randomized lower bounds for the problems P2|online|lp and P2|decr|lp are presented.
Machine Shop. Module 4: Power Saw and Drill Press Operation. Instructor's Guide.
Walden, Charles H.; Daniel, Bill
This document consists of materials for a six-unit course on the following topics: (1) power saw safety and maintenance; (2) cutting stock to length; (3) band machining and contouring; (4) drill press types and safety; (5) drill press work-holding devices; and (6) tools and tool holders. The instructor's guide begins with a list of competencies…
柔性作业车间调度中的组合遗传优化研究%Integrated genetic algorithm for flexible job-shop scheduling problem
Institute of Scientific and Technical Information of China (English)
邬文尧; 蔡鸿明; 姜丽红
2009-01-01
An integrated Genetic Algorithm(GA) is presented for solving the Flexible Job-shop Scheduling Problem(FJSP).In this algorithm,all kinds of strategies,used in population initialization,selection,crossover and mutation,are adopted.New crossover operator Job-baaed Machine Crossover(JMX) is designed and used in machine codes,in order to overcome the limitations of random crossover,which can not reserve parents' good genes.The feasibility and validity of the proposed algorithm is proved by the results obtained from the computational study and the comparison with others.%针对柔性作业车间调度问题,提出一种组合遗传算法.该算法在种群初始化、选择、交叉、变异各阶段,组合使用各种不同的策略.针对机器编码部分的交叉,提出一种基于工件的机器交叉算子,用以改进机器分配部分随机交叉引起的对父代优秀基因继承不足的缺陷.通过对典型算例的计算以及与其他文献的研究成果比较,证明该算法的优良性能.
Minimisation of total tardiness for identical parallel machine scheduling using genetic algorithm
Indian Academy of Sciences (India)
IMRAN ALI CHAUDHRY; ISAM A Q ELBADAWI
2017-01-01
In recent years research on parallel machine scheduling has received an increased attention. This paper considers minimisation of total tardiness for scheduling of n jobs on a set of m parallel machines. A spread-sheet-based genetic algorithm (GA) approach is proposed for the problem. The proposed approach is a domain-independent general purpose approach, which has been effectively used to solve this class of problem.The performance of GA is compared with branch and bound and particle swarm optimisation approaches. Two set of problems having 20 and 25 jobs with number of parallel machines equal to 2, 4, 6, 8 and 10 are solved with the proposed approach. Each combination of number of jobs and machines consists of 125 benchmark problems; thus a total for 2250 problems are solved. The results obtained by the proposed approach are comparable with two earlier approaches. It is also demonstrated that a simple GA can be used to produce results that are comparable with problem-specific approach. The proposed approach can also be used to optimise any objectivefunction without changing the basic GA routine.
Directory of Open Access Journals (Sweden)
Peng Liang
2015-01-01
Full Text Available This research considers an unrelated parallel machine scheduling problem with energy consumption and total tardiness. This problem is compounded by two challenges: differences of unrelated parallel machines energy consumption and interaction between job assignments and machine state operations. To begin with, we establish a mathematical model for this problem. Then an ant optimization algorithm based on ATC heuristic rule (ATC-ACO is presented. Furthermore, optimal parameters of proposed algorithm are defined via Taguchi methods for generating test data. Finally, comparative experiments indicate the proposed ATC-ACO algorithm has better performance on minimizing energy consumption as well as total tardiness and the modified ATC heuristic rule is more effectively on reducing energy consumption.
Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.
2017-08-01
This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.
Directory of Open Access Journals (Sweden)
Guanlong Deng
2016-01-01
Full Text Available This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms.
Institute of Scientific and Technical Information of China (English)
张沙清; 杨海东; 赵洁
2015-01-01
Flexible Job Shop scheduling problem of robotic manufacturing cell is a new kind of scheduling problem with wide engineering application background and tough challenges,which attracts much attention of academia and industry. The content and features of flexible Job Shop scheduling problem of robotic manufacturing cell were analyzed,a scheduling model based on molds manufacturing with the op-timizing targets to minimal makespan was proposed in this paper. A Chaotic Quantum-behaved Particle Swarm Optimization algorithm (CQPSO) was put forward to solve the model. Based on the Quantum-behaved Particle Swarm Optimization (QPSO),the improved Tend chaotic mapping mechanism was introduced. The shortcoming of easily falling into local minimum for QPSO could be avoided, meanwhile,the fast convergence speed of QPSO could be kept in this algorithm. So the effectiveness of algorithm was improved. The sim-ulation results show that CQPSO could effectively solved the flexible Job Shop scheduling problem of robotic manufacturing cell.%柔性Job Shop类型机器人制造单元调度问题是一类新的具有广泛工程应用背景而又极富挑战的调度问题,引起了学术界和工业界的极大关注。文中分析了柔性Job Shop类型机器人单元调度问题的内容与特点,并以模具生产为背景,构建了一种以工件组最大完工时间最小为目标的Job Shop类型机器人单元调度模型,进而提出了一种混沌量子粒子群算法( CQPSO)用于模型求解。该算法在量子粒子群算法( QPSO)基础上,引入改进的Tent混沌映射机制,在保持QPSO算法收敛速度快的同时,克服了其易陷入局部极小值的缺点,提高了算法求解效率。仿真实验结果表明,CQPSO算法在求解柔性Job Shop类型机器人调度问题方面具有较大的应用优势。
Salehi, Mojtaba; Bahreininejad, Ardeshir
2011-08-01
Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.
Assessment of New Load Schedules for the Machine Calibration of a Force Balance
Ulbrich, N.; Gisler, R.; Kew, R.
2015-01-01
New load schedules for the machine calibration of a six-component force balance are currently being developed and evaluated at the NASA Ames Balance Calibration Laboratory. One of the proposed load schedules is discussed in the paper. It has a total of 2082 points that are distributed across 16 load series. Several criteria were applied to define the load schedule. It was decided, for example, to specify the calibration load set in force balance format as this approach greatly simplifies the definition of the lower and upper bounds of the load schedule. In addition, all loads are assumed to be applied in a calibration machine by using the one-factor-at-a-time approach. At first, all single-component loads are applied in six load series. Then, three two-component load series are applied. They consist of the load pairs (N1, N2), (S1, S2), and (RM, AF). Afterwards, four three-component load series are applied. They consist of the combinations (N1, N2, AF), (S1, S2, AF), (N1, N2, RM), and (S1, S2, RM). In the next step, one four-component load series is applied. It is the load combination (N1, N2, S1, S2). Finally, two five-component load series are applied. They are the load combination (N1, N2, S1, S2, AF) and (N1, N2, S1, S2, RM). The maximum difference between loads of two subsequent data points of the load schedule is limited to 33 % of capacity. This constraint helps avoid unwanted load "jumps" in the load schedule that can have a negative impact on the performance of a calibration machine. Only loadings of the single- and two-component load series are loaded to 100 % of capacity. This approach was selected because it keeps the total number of calibration points to a reasonable limit while still allowing for the application of some of the more complex load combinations. Data from two of NASA's force balances is used to illustrate important characteristics of the proposed 2082-point calibration load schedule.
Machine Learning Based Online Performance Prediction for Runtime Parallelization and Task Scheduling
Energy Technology Data Exchange (ETDEWEB)
Li, J; Ma, X; Singh, K; Schulz, M; de Supinski, B R; McKee, S A
2008-10-09
With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as well as developing next-generation software requires assistance from hardware, compilers and runtime systems to exploit parallelism transparently within applications. These systems must decompose applications into tasks that can be executed in parallel and then schedule those tasks to minimize load imbalance. However, many systems lack a priori knowledge about the execution time of all tasks to perform effective load balancing with low scheduling overhead. In this paper, we approach this fundamental problem using machine learning techniques first to generate performance models for all tasks and then applying those models to perform automatic performance prediction across program executions. We also extend an existing scheduling algorithm to use generated task cost estimates for online task partitioning and scheduling. We implement the above techniques in the pR framework, which transparently parallelizes scripts in the popular R language, and evaluate their performance and overhead with both a real-world application and a large number of synthetic representative test scripts. Our experimental results show that our proposed approach significantly improves task partitioning and scheduling, with maximum improvements of 21.8%, 40.3% and 22.1% and average improvements of 15.9%, 16.9% and 4.2% for LMM (a real R application) and synthetic test cases with independent and dependent tasks, respectively.
Courtney P. Winston, DrPH, RD, LD, CDE; James F. Sallis, PhD; Michael D. Swartz, PhD; Deanna M. Hoelscher, PhD, RD; Melissa F. Peskin, PhD
2013-01-01
Introduction Hospitals are the primary worksite of over 5 million adults in the United States, and millions of meals are procured and consumed in this setting. Because many worksite nutrition initiatives use an ecological framework to improve the dietary habits of employees, the nutrition values of foods served in hospitals is receiving attention. Methods This study used the Hospital Nutrition Environment Scan for Cafeterias, Vending Machines, and Gift Shops to quantitatively describe the con...
Flexible job-shop scheduling optimization based on improved genetic algorithm%生产能力约束条件下的柔性作业车间调度优化
Institute of Scientific and Technical Information of China (English)
张铁男; 韩兵; 于渤
2011-01-01
Flexible job-shop scheduling problem (FJSP) under the condition of production capacity constraint is the deepening of classic JSP, and it provides the specific measures to solve the problem of resources limiting of job-shop scheduling in practical production system. FJSP model is established under the condition of production capacity constraint, takes minimizing maximum finishing time and minimizing maximum machine burden as objective function, and proposes improved genetic algorithm (IGA) based on that. IGA applies the coding mechanism combining with operation-based coding and machine-based mechanism. uses improved multi-previous generation crossover operators and multi-point preservative crossover to conduct genetic operation, and overcomes the shortcoming of early mature and slow constringency of classic genetic algorithm with retaining excellent previous generation at the same time. Finally, this paper uses emulation and comparison experiment to verify the feasibility and effectiveness of this algorithm in optimizing FJSP under the condition of production capacity constraint.%柔性作业车间调度问题是经典作业车间调度问题的深化,为解决实际生产系统中作业车间调度资源受限问题提供了方案.从生产能力约束条件出发构建柔性作业车间调度模型,以最大完工时间最小和最大机器负荷最小为目标函数,并提出了基于此的改进遗传算法.该算法采用基于工序和基于机器相结合的编码机制,利用改进多父代交叉算子和多点变异进行遗传操作,在充分保留父代优良基因的同时保证了种群的多样性,克服了传统遗传算法易于早熟或收敛慢的缺点.最后,通过仿真和比较实验,验证了该算法优化生产能力约束条件下柔性车间调度问题的可行性和有效性.
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.
Study of personnel flexibility impact on flexible Job-Shop scheduling%人员柔性度对作业车间调度的影响研究
Institute of Scientific and Technical Information of China (English)
林仁; 周国华; 夏方礼; 王扉; 吴承逊
2016-01-01
In view of the research shortage in the relationship between personnel flexibility and scheduling effect,this paper proposed the representation method of personnel flexibility distribution based on resource-ability matrix in order to reveal the quantitative relationship between personnel flexibility and scheduling effect.Then it established the model about Job-Shop scheduling problem under personnel flexible constraints.This paper presented an improved genetic algorithm (IGA)to solve the model.Finally,the case proves the effect of flexible degree of personnel resources on the scheduling result.It provides guidance for the construction of manufacturing system.%针对人力资源柔性与调度效果关系研究匮乏的问题，为了揭示两者之间的量化关系，提出了基于资源—能力矩阵对人力资源柔性分布进行表示的方法，建立了人力资源柔性约束下的作业车间调度问题模型，采用改进遗传算法对案例进行求解。案例分析证明了人力资源柔性程度对调度效果的显著影响，这为构建柔性制造系统提供了指导意见。
Optimization of rewards in single machine scheduling in the rewards-driven systems
Directory of Open Access Journals (Sweden)
Abolfazl Gharaei
2015-06-01
Full Text Available The single machine scheduling problem aims at obtaining the best sequence for a set of jobs in a manufacturing system with a single machine. In this paper, we optimize rewards in single machine scheduling in rewards-driven systems such that total reward is maximized while the constraints contains of limitation in total rewards for earliness and learning, independent of earliness and learning and etc. are satisfied. In mentioned systems as for earliness and learning the bonus is awarded to operators, we consider only rewards in mentioned systems and it will not be penalized under any circumstances. Our objective is to optimize total rewards in mentioned system by taking the rewards in the form of quadratic for both learning and earliness. The recently-developed sequential quadratic programming (SQP, is used by solve the problem. Results show that SQP had satisfactory performance in terms of optimum solutions, number of iterations, infeasibility and optimality error. Finally, a sensitivity analysis is performed on the change rate of the objective function obtained based on the change rate of the “amount of earliness for jobs (Ei parameter”.
Institute of Scientific and Technical Information of China (English)
肖世昌; 孙树栋; 杨宏安
2014-01-01
Aiming at the uncertainty caused by the randomness of the processing times in job shop, we propose the stochastic model of job shop scheduling problem with stochastically controllable processing times (SCPT-JSP).We adopt a scheduling method that optimizes this problem with two objectives:(1) efficiency measure;(2) robustness measure.To solve this dual-objective scheduling problem, we propose a two stage hierarchical strategy as well as a simulation based genetic algorithm ( GA) in which optimal computing budget allocation is embedded.The feasibility of the proposed model and the strategy and algorithm for solving the problem are proved with simulation experiments.According to the comparison with the optimization results obtained with mean-variance model which optimize the dual-objective directly, we find that our hierarchical strategy and corresponding algorithm can obtain the scheduling solution with superior comprehensive performance.%针对Job Shop环境中工序加工时间的不确定性，建立加工时间随机可控Job Shop调度问题随机模型。采用效率指标和鲁棒性指标对调度方案进行双目标评价。提出一种分层求解策略实现双目标优化，并采用嵌入最优计算量分配策略的遗传算法求解模型。仿真实验证明了所提出模型及优化算法的可行性。通过与直接采用均值－方差模型进行双目标优化得到的结果进行比较，证明了所提出的分层求解策略和算法可以获得综合性能更好的调度方案。
A branch-and-bound algorithm for single-machine earliness-tardiness scheduling with idle time
Hoogeveen, J.A.; Velde, van de S.L.
1996-01-01
We address the NP-hard single-machine problem of scheduling n independent jobs so as to minimize the sum of α times total completion time and β times total earliness with β > α, which can be rewritten as an earliness–tardiness problem. Postponing jobs by leaving the machine idle may then be advantag
A branch-and-bound algorithm for single-machine earliness-tardiness scheduling with idle time
Hoogeveen, J.A.; van de Velde, S.L.; van de Velde, S.L.
1996-01-01
We address the NP-hard single-machine problem of scheduling n independent jobs so as to minimize the sum of α times total completion time and β times total earliness with β > α, which can be rewritten as an earliness–tardiness problem. Postponing jobs by leaving the machine idle may then be
Institute of Scientific and Technical Information of China (English)
赵诗奎
2015-01-01
针对柔性作业车间调度问题(Flexible job shop scheduling problem，FJSP)，以优化最大完工时间为目标，提出一种融合两级邻域搜索和遗传算法的混合算法。基于通过利用机器空闲时间来减小最大完工时间的想法，构造邻域结构，对关键路径上的关键工序进行移动，实现邻域搜索，以改进当前解；设计针对FJSP问题特点的两级邻域搜索方式，第一级邻域搜索为跨机器移动工序，将工序移动到除当前加工机器之外的其他可选机器上，第二级邻域搜索为同机器移动工序，将工序在当前加工机器上进行移动；给出两级邻域搜索相应的保证可行解工序移动条件；兼顾FJSP问题求解算法的全局搜索能力和局部搜索能力，利用遗传算法实现全局搜索，两级邻域搜索实现局部搜索；采用国际通用的FJSP问题基准算例进行测试，验证了所提方法的有效性。%For the flexible job shop scheduling problem (FJSP), in order to optimize the maximum completion time, a hybrid algorithm mixed with bilevel neighborhood search and genetic algorithm is proposed. The neighborhood structure is constructed by using machine idle time to reduce the maximum completion time. In order to improve the current solution, critical operations of the critical path are moved to achieve neighborhood search. The method of bilevel neighborhood search is designed according to the characteristics of FJSP. The first level neighborhood search is the cross-machine moving operation, and the operation is moved to other optional machines in addition to current processing machine. The second level neighborhood search is the same-machine moving operation, and the operation is moved on current processing machine. Operation moving conditions corresponding to the bilevel neighborhood search are given to ensure feasible solutions. Both of global search ability and local search ability of FJSP solving algorithm are
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, we give a mathematical model for earliness-tardiness job scheduling problem with a common due window on parallel and non-identical machines. Because the job scheduling problem discussed in the paper contains a problem of minimizing make-span, which is NP-complete on parallel and uniform machines, a heuristic algorithm is presented to find an approximate solution for the scheduling problem after proving an important theorem. Two numerical examples illustrate that the heuristic algorithm is very useful and effective in obtaining the near-optimal solution.
Scheduling a three-machine no-wait flowshop with separated setup time
Institute of Scientific and Technical Information of China (English)
CHANG Jun-lin; SHAO Hui-he
2006-01-01
In many practical flowshop production environments, there is no intermediate storage space available to keep partially completed jobs between any two machines. The workflow has to be continuous, implying that the no-wait conditions must be abided, which is typical in steel and plastic production. We discuss the threemachine no-wait flowshop scheduling problem where the setup times are considered as separated from processing times and sequence independent. The scheduling goal is to minimize the total flowtime. An optimal property and two heuristic algorithms for this problem are proposed. Evaluated over a large number of problems, the proposed heuristics are found that they can yield good solutions effectively with low computational complexity, and have more obvious advantage for the large size problem compared with the existing one.
Single-machine scheduling with family setup times in a manufacturing system
Chen, Wen-Jinn
2008-06-01
This study considers a single-machine scheduling problem with sequence-dependent setup times. Specifically, this article discusses the problem with several families. In this research, the study assumes that the job being processed must be stopped if workers do not want to work at the weekend. This article calls the weekend period 'vacation'. Owing to complications in the production system, the setup time will be affected if the setup time is interrupted due to vacations. An efficient heuristic is developed to solve the problem of minimizing the maximum tardiness, subject to the family-setup time and vacation constraints. The article presents a heuristic to solve large-sized problems. A branch-and-bound algorithm that utilizes several theorems is also proposed to find the optimal schedules for the problem. Computational results are provided to demonstrate the effectiveness of the heuristic.
Directory of Open Access Journals (Sweden)
Chao Lu
2017-01-01
Full Text Available The scheduling problem with controllable processing times (CPT is one of the most important research topics in the scheduling field due to its widespread application. Because of the complexity of this problem, a majority of research mainly addressed single-objective small scale problems. However, most practical problems are multiobjective and large scale issues. Multiobjective metaheuristics are very efficient in solving such problems. This paper studies a single machine scheduling problem with CPT for minimizing total tardiness and compression cost simultaneously. We aim to develop a new multiobjective discrete backtracking search algorithm (MODBSA to solve this problem. To accommodate the characteristic of the problem, a solution representation is constructed by a permutation vector and an amount vector of compression processing times. Furthermore, two major improvement strategies named adaptive selection scheme and total cost reduction strategy are developed. The adaptive selection scheme is used to select a suitable population to enhance the search efficiency of MODBSA, and the total cost reduction strategy is developed to further improve the quality of solutions. For the assessment of MODBSA, MODBSA is compared with other algorithms including NSGA-II, SPEA2, and PAES. Experimental results demonstrate that the proposed MODBSA is a promising algorithm for such scheduling problem.
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HE Cheng; LIN Hao; DOU Jun-mei; MU Yun-dong
2014-01-01
It is known that the problem of minimizing total weighted completion time on a series-batching machine is NP-hard. We consider a series-batching bicriteria scheduling problem of minimizing makespan and total weighted completion time with equal length job simultaneously. A batching machine can handle up to b jobs in a batch, where b is called the batch capacity of the machine. We study the unbounded model with b≥n, where n denotes the number of jobs. A dynamic programming algorithm is proposed to solve the unbounded model, which can find all Pareto optimal schedules in O(n3) time.
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Ömer Öztürkoğlu
2017-07-01
Full Text Available This study focuses on identical parallel machine scheduling of jobs with deteriorating processing times and rate-modifying activities. We consider non linearly increasing processing times of jobs based on their position assignment. Rate modifying activities are also considered to recover the increase in processing times of jobs due to deterioration. We also propose heuristics algorithms that rely on ant colony optimization and simulated annealing algorithms to solve the problem with multiple RMAs in a reasonable amount of time. Finally, we show that ant colony optimization algorithm generates close optimal solutions and superior results than simulated annealing algorithm.
Comparing the performance of different meta-heuristics for unweighted parallel machine scheduling
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Adamu, Mumuni Osumah
2015-08-01
Full Text Available This article considers the due window scheduling problem to minimise the number of early and tardy jobs on identical parallel machines. This problem is known to be NP complete and thus finding an optimal solution is unlikely. Three meta-heuristics and their hybrids are proposed and extensive computational experiments are conducted. The purpose of this paper is to compare the performance of these meta-heuristics and their hybrids and to determine the best among them. Detailed comparative tests have also been conducted to analyse the different heuristics with the simulated annealing hybrid giving the best result.
An Optimal Algorithm for a Class of Parallel Machines Scheduling Problem
Institute of Scientific and Technical Information of China (English)
常俊林; 邵惠鹤
2004-01-01
This paper considers the parallel machines scheduling problem where jobs are subject to different release times. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In general, the quality of the solutions provided by heuristics degrades with the increase of the probiem's scale. Combined the global search ability of genetic algorithm, this paper proposed a hybrid heuristic to improve the quality of solutions further. The computational results show that the hybrid heuristic combines the advantages of heuristic and genetic algorithm effectively and can provide very good solutions to some large problems in a reasonable amount of computer time.
Robust and Flexible Scheduling with Evolutionary Computation
DEFF Research Database (Denmark)
Jensen, Mikkel T.
(schedules expected to perform well after some degree of modification when the environment changes). This thesis presents two fundamentally different approaches for scheduling job shops facing machine breakdowns. The first method is called neighbourhood based robustness and is based on an idea of minimising...... environments include machine breakdowns, uncertain processing times, workers getting sick, materials being delayed and the appearance of new jobs. These possible environmental changes mean that a schedule which was optimal for the information available at the time of scheduling can end up being highly...... suboptimal when it is implemented and subjected to the uncertainty of the real world. For this reason it is very important to find methods capable of creating robust schedules (schedules expected to perform well after a minimal amount of modification when the environment changes) or flexible schedules...
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Amir Ebrahimzadeh Pilerood
2012-04-01
Full Text Available This paper addresses scheduling a set of weighted jobs on a single machine in presence of release date for delivery in batches to customers or to other machines for further processing. The problem is a natural extension of minimizing the sum of weighted flow times by considering the possibility of delivering jobs in batches and introducing batch delivery costs. The classical problem is NP-hard and then the extended version of the problem is NP-hard. The objective function is that of minimizing the sum of weighted flow times and delivery costs. The extended problem arises in a real supply chain network by cooperation between two layers of chain. Structural properties of the problem are investigated and used to devise a branch-and-bound solution scheme. Computational experiments show the efficiency of suggested algorithm for solving instances up to 40 jobs.
Dynamic scheduling of virtual machines running hpc workloads in scientific grids
Khalid, Omer; Anthony, Richard; Petridis, Miltos; Parrot, Kevin; Schulz, Markus; 10.1145/1330555.1330556
2010-01-01
The primary motivation for uptake of virtualization has been resource isolation, capacity management and resource customization allowing resource providers to consolidate their resources in virtual machines. Various approaches have been taken to integrate virtualization in to scientific Grids especially in the arena of High Performance Computing (HPC) to run grid jobs in virtual machines, thus enabling better provisioning of the underlying resources and customization of the execution environment on runtime. Despite the gains, virtualization layer also incur a performance penalty and its not very well understood that how such an overhead will impact the performance of systems where jobs are scheduled with tight deadlines. Since this overhead varies the types of workload whether they are memory intensive, CPU intensive or network I/O bound, and could lead to unpredictable deadline estimation for the running jobs in the system. In our study, we have attempted to tackle this problem by developing an intelligent s...
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M.M.S. Abdulkader
2013-09-01
Full Text Available The introduction of robotic cells to manufacturing systems improved the efficiency, productivity and reliability of the system. The main objective of the scheduling problem of multi-item multi-machine robotic cells is the identification of the optimum robot cycle/s and jobs sequencing for certain processing conditions which yield the higher possible production rate. The objective of this work is to solve the scheduling problem in four-machine blocking robotic cells producing identical and different part types while minimizing the cycle time. A genetic algorithm is developed to find the parts sequence that minimizes the robot-moves cycle time for each robot cycle. The results showed that the developed genetic algorithm yields competitive results compared to the results of the full enumeration of all possible parts sequences. The results show also that the ratio between the average processing time of all parts and the robot travel time determines the cycle having the optimal robot-moves.
Run-time scheduling and execution of loops on message passing machines
Saltz, Joel; Crowley, Kathleen; Mirchandaney, Ravi; Berryman, Harry
1990-01-01
Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.
A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem
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Xiaohui Li
2010-01-01
Full Text Available A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific problem. Then, since this problem is NP hard in the strong sense, two well-known approximated methods, NSGA-II and SPEA-II, are adopted to solve it. Experimental results show the advantages of NSGA-II for the studied problem. An exact method is then applied to be compared with NSGA-II algorithm in order to prove the efficiency of the former. Experimental results show the advantages of NSGA-II for the studied problem. Computational experiments show that on all the tested instances, our NSGA-II algorithm was able to get the optimal solutions.
GA-ACO for solving flexible job shop scheduling problem%求解柔性作业车间调度问题的遗传-蚁群算法
Institute of Scientific and Technical Information of China (English)
陈成; 邢立宁
2011-01-01
为更有效地求解柔性作业车间调度问题,提出了一种遗传一蚁群算法,该算法采用遗传算法解决机器分配问题,采用蚁群算法解决工序排序问题.存算法的求解过程中,不断从前期优化中挖掘、学习知识,并采用已获得的知识指导后续优化过程.通过标准实例测试,验证了所提算法的有效性.%To solve flexible job shop scheduling problem effectively, a hybrid approach which combined Genetic Algorithm(GA)with Ant Colony Optimization(ACO)was proposed. GA was applied to tackle machine assignment problem, while AC() was employed to deal with operation sequencing problem. In the solution process, knowledge was continuously learned from previous optimization process and then adopted to guide subsequent optimization. Effectiveness of the proposed algorithm was validated through an experiment.
Institute of Scientific and Technical Information of China (English)
吴小康; 叶春明
2014-01-01
Personnel Flexibility Flow Shop Scheduling Problem is more realistic and practical than classical FSP .First , the personnel‐machine diagram is proposed .Second ,it extends the PM matrix and FI index to measure the personnel flexibil‐ity .After improving the classical FSP model ,it is used to solve the Car system problems and practical example through two steps by firefly algorithm at last .All of these prove that it is effective and feasible .%具有人员柔性的FS P问题较之于经典的FS P问题更具有现实性和应用前景。首先提出人员‐机器关系图并引出度量人员柔性的PM矩阵和FI指数，然后对传统FSP模型进行补充和改进，以萤火虫算法为工具，通过人员模式的选择和对应模式下的问题寻优两大步骤进行求解并利用经典Car类问题进行仿真，最后将其应用于实例求解。仿真和实例求解结果都充分说明了算法的有效性和可行性。
用于作业车间调度的模拟退火算法%A simulated annealing algorithm on solving job shop scheduling problem
Institute of Scientific and Technical Information of China (English)
赵良辉; 邓飞其
2006-01-01
作业车间调度问题(Job Shop Scheduling Problem,JSP)是一类NP完全问题,解决此类问题较常使用非数值算法,而模拟退火算法是其中较为突出的而且应用广泛的一种算法.本文结合车间调度问题的特点阐述了模拟退火算法在解决车间调度问题上的应用,提出了基于模拟退火算法的车间调度问题模型,并以Matlab为工具进行了仿真实验.
Flexible Personnel Scheduling in the Parallel Environment
Institute of Scientific and Technical Information of China (English)
XU Ben-zhu; ZHANG Xing-ling
2014-01-01
In the view of staff shortages and the huge inventory of products in the current market, we put forward a personnel scheduling model in the target of closing to the delivery date considering the parallelism. Then we designed a scheduling algorithm based on genetic algorithm and proposed a flexible parallel decoding method which take full use of the personal capacity. Case study results indicate that the flexible personnel scheduling considering the order-shop scheduling, machine automatic capabilities and personnel flexible in the target of closing to the delivery date optimize the allocation of human resources, then maximize the efficiency.
Institute of Scientific and Technical Information of China (English)
张静; 王万良; 徐新黎; 介婧
2012-01-01
Flexible job-shop scheduling is a very important branch in both fields of production management and combinatorial optimization. A hybrid particle-swarm optimization algorithm is proposed to study the mutli-objective flexible job-shop scheduling problem based on Pareto-dominance. First, particles are represented based on job operation and machine assignment, and are updated directly in the discrete domain. Then, a multi-objective local search strategy including Baldwinian learning mechanism and simulated annealing technology is introduced to balance global exploration and local exploitation. Third, Pareto-dominance is applied to compare different solutions, and an external archive is employed to hold and update the obtained non-dominated solutions. Finally, the proposed algorithm is simulated on numerical classical benchmark examples and compared with existing methods. It is shown that the proposed method achieves better performance in both convergence and diversity.%柔性作业车间调度问题是生产管理领域和组合优化领域的重要分支.本文提出一种基于Pareto支配的混合粒子群优化算法求解多目标柔性作业车间调度问题.首先采用基于工序排序和机器分配的粒子表达方式,并直接在离散域进行位置更新.其次,提出基于BaldWinian学习策略和模拟退火技术相结合的多目标局部搜索策略,以平衡算法的全局探索能力和局部开发能力.然后引入Pareto支配的概念来比较粒子的优劣性,并采用外部档案保存进化过程中的非支配解.最后用于求解该类问题的经典算例,并与已有算法进行比较,所提算法在收敛性和分布均匀性方面均具有明显优势.
Tabu search algorithms for job-shop problems with a single transport robot
Hurink, Johann; Knust, Sigrid
2005-01-01
We consider a generalized job-shop problem where the jobs additionally have to be transported between the machines by a single transport robot. Besides transportation times for the jobs, empty moving times for the robot are taken into account. The objective is to determine a schedule with minimal ma
Tabu search algorithms for job-shop problems with a single transport robot
Hurink, J.L.; Knust, S.
2001-01-01
We consider a generalized job-shop problem where the jobs additionally have to be transported between the machines by a single transport robot. Besides transportation times for the jobs, empty moving times for the robot are taken into account. The objective is to determine a schedule with minimal ma
Directory of Open Access Journals (Sweden)
Kun Li
2015-01-01
Full Text Available This paper investigates a special single machine scheduling problem derived from practical industries, namely, the selective single machine scheduling with sequence dependent setup costs and downstream demands. Different from traditional single machine scheduling, this problem further takes into account the selection of jobs and the demands of downstream lines. This problem is formulated as a mixed integer linear programming model and an improved particle swarm optimization (PSO is proposed to solve it. To enhance the exploitation ability of the PSO, an adaptive neighborhood search with different search depth is developed based on the decision characteristics of the problem. To improve the search diversity and make the proposed PSO algorithm capable of getting out of local optimum, an elite solution pool is introduced into the PSO. Computational results based on extensive test instances show that the proposed PSO can obtain optimal solutions for small size problems and outperform the CPLEX and some other powerful algorithms for large size problems.
Institute of Scientific and Technical Information of China (English)
2015-01-01
The job shop scheduling problem is one of the most classical combinatorial optimization problems,which con-cerns allocation of a set of jobs on a set of machines to meet certain criteria. Flexible job shop scheduling problem (FJSSP) is an extension of JSSP and very difficult to achieve an optimal solution with traditional optimization approach-es owing to the high computational complexity. Artificial bee colony (ABC) algorithm invented recently is a biologi-cal-inspired optimization algorithm,which simulates the foraging behaviors of honey bee swarm. A discrete artificial bee colony algorithm (DABC) is proposed to solve multi-objective flexible job shop scheduling problem. In DABC, the crossover strategy is introduced to search for the better solution (food source). Besides,an adaptive mutation strategy is adopted to overcome the shortcoming of premature convergence. Finally, the proposed algorithm is tested on different scale problems and compared with the proposed efficient algorithms in the literature recently. The results show that DP-SO is an effective and efficient.%作业车间调度问题是一类典型的组合优化问题，要求多个作业在不同的机器上进行加工，目的是获得最好的作业加工序列，以满足特定的性能指标。柔性作业车间调度问题是对传统的作业车间调度问题的进一步扩展，由于求解的复杂性，使得传统方法很难在有效的时间内获得问题的最优解。人工蜂群算法是近年来提出的一种受生物行为启发的优化算法，该算法主要通过模拟蜜蜂的觅食来实现问题的求解。提出了一种离散的人工蜂群算法于求解柔性作业车间调度问题，算法通过交叉方式来搜索潜在的更好的蜜源，并采用自适应的变异策略来降低早熟收敛的可能性。最后通过对比实验证明算法对于求解多目标柔性作业车间调度问题是有效的。
A two-phase fuzzy programming model for a complex bi-objective no-wait flow shop scheduling
Directory of Open Access Journals (Sweden)
Reza Tavakkoli-Moghaddam
2012-08-01
Full Text Available In this paper, we study no-wait flow shop problem where setup times depend on sequence of operations. The proposed problem considers sequence-independent removal times, release date with an additional assumption that there are some preliminary setup times. There are two objectives of weighted mean tardiness and makespan associated with the proposed model of this paper. We formulate the resulted problem as a mixed integer programming, where a two-phase fuzzy programming is implemented to solve the model. To examine the performance of the proposed model, we generate several sample data, randomly and compare the results with other methods. The preliminary results indicate that the proposed two-phase model of this paper performed relatively better than Zimmerman's single-phase fuzzy method.
Directory of Open Access Journals (Sweden)
Xuefei Shi
2014-01-01
Full Text Available We consider a single machine scheduling problem with multiple maintenance activities, where the maintenance duration function is of the linear form ft=a+bt with a≥0 and b>1. We propose an approximation algorithm named FFD-LS2I with a worst-case bound of 2 for problem. We also show that there is no polynomial time approximation algorithm with a worst-case bound less than 2 for the problem with b≥0 unless P=NP, which implies that the FFD-LS2I algorithm is the best possible algorithm for the case b>1 and that the FFD-LS algorithm, which is proposed in the literature, is the best possible algorithm for the case b≤1 both from the worst-case bound point of view.
Task scheduling and vir tual machine allocation policy in cloud computing environment
Institute of Scientific and Technical Information of China (English)
Xiong Fu; Yeliang Cang
2015-01-01
Cloud computing represents a novel computing model in the contemporary technology world. In a cloud system, the com-puting power of virtual machines (VMs) and network status can greatly affect the completion time of data intensive tasks. How-ever, most of the current resource al ocation policies focus only on network conditions and physical hosts. And the computing power of VMs is largely ignored. This paper proposes a comprehensive resource al ocation policy which consists of a data intensive task scheduling algorithm that takes account of computing power of VMs and a VM al ocation policy that considers bandwidth between storage nodes and hosts. The VM al ocation policy includes VM placement and VM migration algorithms. Related simulations show that the proposed algorithms can greatly reduce the task comple-tion time and keep good load balance of physical hosts at the same time.
Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem
Directory of Open Access Journals (Sweden)
S. Molla-Alizadeh-Zavardehi
2014-01-01
Full Text Available This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA, variable neighborhood search (VNS, and simulated annealing (SA frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.
Hybrid metaheuristics for solving a fuzzy single batch-processing machine scheduling problem.
Molla-Alizadeh-Zavardehi, S; Tavakkoli-Moghaddam, R; Lotfi, F Hosseinzadeh
2014-01-01
This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.
Federal Laboratory Consortium — Projects at IARC can benefit from Fermilab's experienced machinists, welders, and extensive on-site equipment. Equipment includes conventional and CNC mills, lathes,...
Institute of Scientific and Technical Information of China (English)
潘理; 杨勃
2016-01-01
Interval job-shop scheduling problem is a new research hotspot inwork-shop scheduling. The existing research work focused on problem description and optimization, but substantial results is lacking on theoretical model and dynamic properties.We present a time Petri net to model interval job-shop scheduling problems, and uses a reachability method based on state classes to analyze all feasible schedules of this model, and thensolves optimal schedules with least upper bound and least lower bound. The proposed method can provide a helpful reference for modelling and analyzing interval job-shop scheduling problems.%区间作业车间调度问题近年来已成为生产调度研究的热点，现有研究工作主要集中于问题描述和优化求解方面，在理论模型、动态性质等方面还缺乏实质性成果。使用时间Petri网模型建模区间作业车间调度问题，并运用状态类可达性分析方法，分析模型所有可行调度，进而求解具有最小下界和最小上界的优化调度，为区间作业车间调度问题的建模与分析提供有益参考。
Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
Directory of Open Access Journals (Sweden)
Hongtao Hu
2016-01-01
Full Text Available A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.
Energy Technology Data Exchange (ETDEWEB)
Schmid, W.
2002-07-01
This article describes the clever combination of various techniques to achieve the goal of providing a stable ambient temperature with an accuracy of +/- 1 K in the assembly shop of a German manufacturer of precision machine tools. The requirements placed on the assembly and operation of machine tools operating to an accuracy of less that a hundredth of a millimetre are discussed. The award-winning heating and cooling system, which features the use of gravity cooling, geothermal energy (ground water for cooling) and the use of constructional elements (floor, facades, windows) for thermal buffering is described. The ingenious control system with 32 control zones and 64 sensors is described, which also provides the company's management with long-term documentation of temperature conditions for quality assurance purposes. Technical data on the installation is provided in table form.
SOLVABLE CASES OF THE NO-WAIT FLOWSHOP SCHEDULING PROBLEM
VANDERVEEN, JAA; VANDAL, R
1991-01-01
The no-wait flow-shop scheduling problem (NWFSSP) with a makespan objective function is considered. As is well known, this problem is NP-hard for three or more machines. Therefore, it is interesting to consider special cases, i.e. special structured processing time matrices, that allow polynomial
Institute of Scientific and Technical Information of China (English)
曾强; 沈玲; 杨育; 宋红娜
2012-01-01
Aiming at the multi-objective optimization problem for the equal lot splitting flexible job-shop scheduling, an integrated optimization method is proposed. Firstly, a multi-objective optimization model is established with the objective to minimize the makespan and minimize the manufacturing cost. Then, an improved Non-dominated Sorting Genetic Algorithm II (NSGA II) is presented and designed to solve the model. In the algorithm, an object-oriented technique is introduced to deal with the complicated logical relation between different entities, a three-segment encoding technique is used to encode the lot splitting scheme, the process sequences and machines, a three-segment hybrid crossover and mutation operator is used to implement genetic evolution, and two delicacy scheduling techniques are applied to reduce the flow time of each sub-batch. Finally, the effectiveness of the scheduling method proposed is validated by case study.%针对多目标等量分批柔性作业车间调度问题,提出了一种集成优化方法.构建了一种以完工时间最短、生产成本最低为优化目标的多目标等量分批柔性调度集成优化模型.提出并设计了一种改进的非支配排序遗传算法对模型加以求解.算法中引入面向对象技术处理复杂的实体逻辑关系,采用三段式分段编码技术分别对分批方案、加工顺序、设备进行编码,采用三段式分段交叉和变异的混合遗传算子实现遗传进化,采用两种精细化调度技术进行解码以缩短流程时间.通过案例分析验证了所提方法的有效性.
Directory of Open Access Journals (Sweden)
T. K. Jana
2015-09-01
Full Text Available There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS framework facilitates dynamic scheduling with improved performance under such situations. The responsiveness of the resources having cognitive capabilities helps to overcome the adverse consequences of resource failure in a better way.
Research Status and Development Trend of Flexible Job Shop Scheduling Problem%柔性作业车间调度问题研究现状及发展趋势
Institute of Scientific and Technical Information of China (English)
李传鹏; 王桂从; 崔焕勇
2012-01-01
文章描述了柔性作业车间调度问题,并根据目标、约束、批量等不同的分类标准对其进行了分类,总结了柔性作业车间调度问题建模方法及优化算法的研究现状,最后通过现存问题的分析探讨了发展趋势.%This paper describes the flexible job shop scheduling problem, classifies according to the different classification criteria of objectives, constraints, batches and so on, and summarizes research status of flexible job shop scheduling problem' s modeling methods and optimization algorithm, finally through the analysis of the existing problems, discusses the development trend.
Institute of Scientific and Technical Information of China (English)
王进峰; 阴国富; 雷前召; 范顺成
2013-01-01
针对柔性作业车间调度问题(FJSP)的特点和发展现状,提出一种基于基本遗传算法的改进算法.构建了一种新的染色体表达方案,将染色体分为工序染色体部分和机床染色体部分.通过加权处理设计了适应度函数,将多目标优化问题转变为线性优化问题.针对改进的染色体表达方案,重新设计了种群初始化算法,采用复制、交叉,以及变异操作策略优化调度方案.通过实例验证了该算法对FJSP的优化过程,试验结果表明了该算法的可行性和有效性.%Examines the characteristic and development of the Flexible Job-shop Scheduling Problem (FJSP).An improved algorithm for the FJSP is proposed based on a basic genetic algorithm,a new chromosome representation is represented,and the chromosome is divided into two parts:Operation Assignment (OA) and Machine Selection (MS).The fitness function is built with weight,and the multi-objective optimization problem was transformed to linear optimization problems.According to the chromosome representation,the algorithm of initializing population is redesigned,different strategies for crossover and mutation operator are adopted.The experimental results have shown that the proposed algorithm is a viable and effective approach for the FJSP.
Directory of Open Access Journals (Sweden)
T. K. Wang
2014-01-01
Full Text Available Surgery scheduling must balance capacity utilization and demand so that the arrival rate does not exceed the effective production rate. However, authorized overtime increases because of random patient arrivals and cycle times. This paper proposes an algorithm that allows the estimation of the mean effective process time and the coefficient of variation. The algorithm quantifies patient flow variability. When the parameters are identified, takt time approach gives a solution that minimizes the variability in production rates and workload, as mentioned in the literature. However, this approach has limitations for the problem of a flow shop with an unbalanced, highly variable cycle time process. The main contribution of the paper is to develop a method called takt time, which is based on group technology. A simulation model is combined with the case study, and the capacity buffers are optimized against the remaining variability for each group. The proposed methodology results in a decrease in the waiting time for each operating room from 46 minutes to 5 minutes and a decrease in overtime from 139 minutes to 75 minutes, which represents an improvement of 89% and 46%, respectively.
Institute of Scientific and Technical Information of China (English)
刘韵; 胡毅; 罗企; 房超
2015-01-01
柔性车间作业调度问题( FJSP)作为经典车间作业调度问题( JSP)的扩展，早在上个世纪已经被证明为是NP-难的问题。目前启发式搜索方法作为解决NP-难问题的一个重要方法，已经被广泛用于解决车间调度问题。文章提出了一种基于启发式搜索的粒子群优化算法( PSO)，用以解决柔性车间作业调度问题，旨在获得最优的最小总工作时间。实验的结果与基于分布式估计算法( BEDA)以及改进后的遗传算法( GA)比较，证明本文提出的PSO算法，可以有效处理FJSP问题。%Flexible Job Shop Scheduling Problem ( JSP) , which as an extension of Classical Job Shop Sched-uling Problem, had been proved as NP-Hard problem since last century. As one of the most popular approa-ches, heuristic search has been widely used for solving Job Shop Scheduling Problem. In this paper, we pro-pose an Particle Swarm Optimization( PSO) Algorithm, which based on heuristic search, to solve the Flexi-ble Job Shop Scheduling Problem. Compared with Based Estimation of Distribution Algorithm and Improved Genetic Algorithm proves that the algorithm we proposed can solve the FJSP effectively.
EA/G-GA for Single Machine Scheduling Problems with Earliness/Tardiness Costs
Directory of Open Access Journals (Sweden)
Yuh-Min Chen
2011-06-01
Full Text Available An Estimation of Distribution Algorithm (EDA, which depends on explicitly sampling mechanisms based on probabilistic models with information extracted from the parental solutions to generate new solutions, has constituted one of the major research areas in the field of evolutionary computation. The fact that no genetic operators are used in EDAs is a major characteristic differentiating EDAs from other genetic algorithms (GAs. This advantage, however, could lead to premature convergence of EDAs as the probabilistic models are no longer generating diversified solutions. In our previous research [1], we have presented the evidences that EDAs suffer from the drawback of premature convergency, thus several important guidelines are provided for the design of effective EDAs. In this paper, we validated one guideline for incorporating other meta-heuristics into the EDAs. An algorithm named “EA/G-GA” is proposed by selecting a well-known EDA, EA/G, to work with GAs. The proposed algorithm was tested on the NP-Hard single machine scheduling problems with the total weighted earliness/tardiness cost in a just-in-time environment. The experimental results indicated that the EA/G-GA outperforms the compared algorithms statistically significantly across different stopping criteria and demonstrated the robustness of the proposed algorithm. Consequently, this paper is of interest and importance in the field of EDAs.
Institute of Scientific and Technical Information of China (English)
2008-01-01
This article addresses the problem of scheduling n jobs with a common due date on a machine subject to stochastic breakdowns to minimize absolute early-tardy penalties.We investigate the problem under the conditions that the uptimes follow an exponential distribution,and the objective measure in detail is to minimize the expected sum of the absolute deviations of completion times from the common due date.We proceed to study in two versions (the downtime follows an exponential distribution or is a constant entailed for the repeat model job),one of which is the so-called preempt- resume version,the other of which is the preempt-repeat version.Three terms of work have been done.(i)Formulations and Preliminaries.A few of necessary definitions,relations and basic facts are established.In particular,the conclusion that the expectation of the absolute deviation of the completion time about a job with deterministic processing time t from a due date is a semi-V-shape function in t has been proved.(ii) Properties of Optimal Solutions.A few characteristics of optimal solutions are established.Most importantly,the conclusion that optimal solutions possess semi-V- shape property has been proved.(iii) Algorithm.Some computing problems on searching for optimal solutions are discussed.
Institute of Scientific and Technical Information of China (English)
CHENG CongDian; TANG HengYong; ZHAO ChuanLi
2008-01-01
This article addresses the problem of scheduling n jobs with a common due date on a machine subject to stochastic breakdowns to minimize absolute early-tardy penalties. We investigate the problem under the conditions that the uptimes follow an exponential distribution, and the objective measure in detail is to minimize the expected sum of the absolute deviations of completion times from the common due date. We proceed to study in two versions (the downtime follows an exponential distribution or is a constant entailed for the repeat model job), one of which is the so-called preempt-resume version, the other of which is the preempt-repeat version. Three terms of work have been done. (ⅰ) Formulations and Preliminaries. A few of necessary definitions, relations and basic facts are established. In particular, the conclusion that the expectation of the absolute deviation of the completion time about a job with deterministic processing time t from a due date is a semi-V-shape function in t has been proved. (ⅱ) Properties of Optimal Solutions. A few characteristics of optimal solutions are established. Most importantly, the conclusion that optimal solutions possess semi-V-shape property has been proved. (ⅲ) Algorithm. Some computing problems on searching for optimal solutions are discussed.
Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines
Directory of Open Access Journals (Sweden)
Kawal Jeet
2016-04-01
Full Text Available Nature-inspired algorithms are recently being appreciated for solving complex optimization and engineering problems. Black hole algorithm is one of the recent nature-inspired algorithms that have obtained inspiration from black hole theory of universe. In this paper, four formulations of multi-objective black hole algorithm have been developed by using combination of weighted objectives, use of secondary storage for managing possible solutions and use of Genetic Algorithm (GA. These formulations are further applied for scheduling jobs on parallel machines while optimizing bi-criteria namely maximum tardiness and weighted flow time. It has been empirically verified that GA based multi-objective Black Hole algorithms leads to better results as compared to their counterparts. Also the use of combination of secondary storage and GA further improves the resulting job sequence. The proposed algorithms are further compared to some of the existing algorithms, and empirically found to be better. The results have been validated by numerical illustrations and statistical tests.
Burckley, Elizabeth; Tincani, Matt; Guld Fisher, Amanda
2015-04-01
To evaluate the iPad 2™ with Book Creator™ software to provide visual cues and video prompting to teach shopping skills in the community to a young adult with an autism spectrum disorder and intellectual disability. A multiple probe across settings design was used to assess effects of the intervention on the participant's independence with following a shopping list in a grocery store across three community locations. Visual cues and video prompting substantially increased the participant's shopping skills within two of the three community locations, skill increases maintained after the intervention was withdrawn, and shopping skills generalized to two untaught shopping items. Social validity surveys suggested that the participant's parent and staff favorably viewed the goals, procedures, and outcomes of intervention. The iPad 2™ with Book Creator™ software may be an effective way to teach independent shopping skills in the community; additional replications are needed.
DEFF Research Database (Denmark)
Jørgensen, Michael Søgaard
1999-01-01
The paper prsents the overall concept of science shops as practised in most of the European science shops and present the concept practised and some experience obtained at the Technical University of Denmark. An outline for the planning of new sceince shops is presented.......The paper prsents the overall concept of science shops as practised in most of the European science shops and present the concept practised and some experience obtained at the Technical University of Denmark. An outline for the planning of new sceince shops is presented....
DEFF Research Database (Denmark)
Jørgensen, Michael Søgaard
1999-01-01
The paper prsents the overall concept of science shops as practised in most of the European science shops and present the concept practised and some experience obtained at the Technical University of Denmark. An outline for the planning of new sceince shops is presented.......The paper prsents the overall concept of science shops as practised in most of the European science shops and present the concept practised and some experience obtained at the Technical University of Denmark. An outline for the planning of new sceince shops is presented....
Directory of Open Access Journals (Sweden)
Kuo-Ching Ying
2017-01-01
Full Text Available This work addresses four single-machine scheduling problems (SMSPs with learning effects and variable maintenance activity. The processing times of the jobs are simultaneously determined by a decreasing function of their corresponding scheduled positions and the sum of the processing times of the already processed jobs. Maintenance activity must start before a deadline and its duration increases with the starting time of the maintenance activity. This work proposes a polynomial-time algorithm for optimally solving two SMSPs to minimize the total completion time and the total tardiness with a common due date.
SCHEDULING PROBLEMS-AN OVERVIEW
Institute of Scientific and Technical Information of China (English)
Asmuliardi MULUK; Hasan AKPOLAT; Jichao XU
2003-01-01
There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days.These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition, other approaches to solving scheduling problems, for instance approaches based on human factors, prefer the scheduling system to be more flexible in both design and implementation. After discussion of these factors, the authors propose the integration of a different set of criteria for the development of scheduling systems which not only appears to have a better flexibility but also increased customer-focus.
Minimizing the Makespan for Scheduling Problems with General Deterioration Effects
Directory of Open Access Journals (Sweden)
Xianyu Yu
2013-01-01
Full Text Available This paper investigates the scheduling problems with general deterioration models. By the deterioration models, the actual processing time functions of jobs depend not only on the scheduled position in the job sequence but also on the total weighted normal processing times of the jobs already processed. In this paper, the objective is to minimize the makespan. For the single-machine scheduling problems with general deterioration effects, we show that the considered problems are polynomially solvable. For the flow shop scheduling problems with general deterioration effects, we also show that the problems can be optimally solved in polynomial time under the proposed conditions.
Institute of Scientific and Technical Information of China (English)
刘胜军; 李霞
2015-01-01
Aiming at the Hybrid lfow shop scheduling problem, a mathematical model is established with the minimum of makespan, the lowest cost and the minimum of the defective goods as the objective function. The NSGA-II algorithm is applied to solve the hybrid lfow shop scheduling problem. Through MATLAB simulation of an example, a group of Pareto solutions is obtained, then standardizing the data. The weight coefifcient of each target is determined by the analytic hierarchy process. A satisfactory scheduling scheme is selected from the Pareto solutions by weighted sum. The results show that the algorithm is effective and feasible in solving the hybrid lfow shop scheduling problem and provide reference for the enterprise of the production scheduling.%针对混合流水生产车间调度问题，以生产周期最短、机器加工成本最少和生产次品率最低为目标，建立了多目标优化模型，将NSGA-II算法应用于求解混合流水生产车间调度问题。通过MATLAB对算例仿真，得到一组Pareto解，将数据标准化处理。然后，利用层次分析法确定各目标的权重，对标准化后的数据加权求和来选择出满意的调度方案。表明了该算法在解决混合流水车间多目标调度问题的有效性和可行性，同时为企业的生产调度排序提供方法借鉴。
Institute of Scientific and Technical Information of China (English)
李俊青; 潘全科; 王法涛
2015-01-01
In this paper , we propose a hybrid discrete artificial bee colony ( HDABC ) algorithm for solving the hybridflow-shop scheduling(HFS)problems.In the hybrid algorithm, each solution is coded by a job-permuta-tion mechanism .Four neighborhood structures are designed .The employed bees are assigned to each solution in the population set , to complete the local search task with a detailed designed local search approach .Onlooker bees randomly fetch two updated solutions and select the better one as the current solution , and then complete a further exploitation process .The scouts help the algorithm jump out of the local best by applying three different approaches .Then, the proposed algorithm is tested on the 34 identical parallel machines HFS and two un-related parallel machines HFS problems .The performance comparisons with other efficient algorithms are provided .It is concluded that the proposed algorithm is competitive to the compared existing algorithms for the problem consid -ered, in terms of searching quality , diversity, robustness and convergence ability .%本文给出了一种离散的人工蜂群算法（ HDABC）用于求解混合流水车间调度（ HFS）问题。采用工件排序的编码方式，并设计了四种邻域结构。雇佣蜂依次分派到解集中每个解，采用结合问题特征的局部搜索策略完成挖掘搜索工作。跟随蜂随机选择两个解并挑选较优者作为当前解，完成进一步的探优过程。侦察蜂采用三种策略跳出局部极小。通过34个同构并行机HFS问题和2个异构并行机HFS实际调度问题的实验，并与当前文献中的典型算法对比，验证了本文提出的算法无论在算法时间还是在求解质量上，都具备良好的性能。
Institute of Scientific and Technical Information of China (English)
Li Kai; Yang Shanlin
2008-01-01
A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time.Models and relaxations are collected.Most of these problems are NP-hard,in the strong sense,or open problems,therefore approximation algorithms are studied.The review reveals that there exist some potential areas worthy of further research.
Institute of Scientific and Technical Information of China (English)
赵诗奎
2016-01-01
In order to optimize the maximum completion time, a hybrid solving method with a new neighborhood structure is proposed for the job shop scheduling problem (JSP). In the hybrid algorithm, genetic algorithm is adopted for global search, and local search is achieved based on neighborhood structure. In the design of the neighborhood structure, the calculation method of operation head and tail length, and the key operations searching method are studied based on Gantt chart. Through the analysis of various neighborhood structures and related theories, it points out that the foundation of neighborhood structure is to guide the key operations to utilize machine idle time, and can be divided into two types: direct use and indirect use. The two utilization ways are both comprehensively considered, and the corresponding movement strategies are defined according to the type of key operations with scientific guidance. The effective movement range is expanded, breaking through the location restrictions of inside, direct adjacent before and behind of the operation block. The experimental results of 43 benchmarks show that the proposed algorithm has good performance. In addition, the new neighborhood structure can further be integrated with other intelligent algorithms for solving JSP problem.%针对作业车间调度问题(Job shop scheduling problem，JSP)，以优化最大完工时间为目标，提出一种融合新型邻域结构的混合求解方法。混合算法由具有全局搜索能力的遗传算法和基于邻域结构的邻域搜索算法构成。在邻域结构的设计中，研究了基于甘特图的工序头尾长度计算方法，以及关键工序查找方法。通过分析已有各种邻域结构及相关理论性质，指出邻域结构的根本在于引导关键工序对机器空闲时间进行利用，并将利用方式分为两种情况：直接利用和间接利用。综合两种利用方式，科学指导关键工序的移动，根据关键工序的类
Directory of Open Access Journals (Sweden)
Rui Zhang
2013-01-01
Full Text Available We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. The objective functions to be minimized consist of two parts; the first part is related with the due date performance (i.e., the tardiness of the jobs, while the second part is related with the setting of machine speeds. Therefore, the decision variables include both the production schedule (sequences of jobs and the production rate of each machine. The optimization process, however, is significantly complicated by the stochastic factors in the manufacturing system. To address the difficulty, a simulation-based three-stage optimization framework is presented in this paper for high-quality robust solutions to the integrated scheduling problem. The first stage (crude optimization is featured by the ordinal optimization theory, the second stage (finer optimization is implemented with a metaheuristic called differential evolution, and the third stage (fine-tuning is characterized by a perturbation-based local search. Finally, computational experiments are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also discussed.
Indian Academy of Sciences (India)
V K MANUPATI; G RAJYALAKSHMI; FELIX T S CHAN; J J THAKKAR
2017-03-01
This paper addresses a fuzzy mixed-integer non-linear programming (FMINLP) model by considering machine-dependent and job-sequence-dependent set-up times that minimize the total completion time,the number of tardy jobs, the total flow time and the machine load variation in the context of unrelated parallel machine scheduling (UPMS) problem. The above-mentioned multi-objectives were considered based on nonzero ready times, machine- and sequence-dependent set-up times and secondary resource constraints for jobs.The proposed approach considers unrelated parallel machines with inherent uncertainty in processing times and due dates. Since the problem is shown to be NP-hard in nature, it is a challenging task to find the optimal/nearoptimal solutions for conflicting objectives simultaneously in a reasonable time. Therefore, we introduced a new multi-objective-based evolutionary artificial immune non-dominated sorting genetic algorithm (AI-NSGA-II) to resolve the above-mentioned complex problem. The performance of the proposed multi-objective AI-NSGA-II algorithm has been compared to that of multi-objective particle swarm optimization (MOPSO) and conventionalnon-dominated sorting genetic algorithm (CNSGA-II), and it is found that the proposed multi-objective-based hybrid meta-heuristic produces high-quality solutions. Finally, the results obtained from benchmark instances and randomly generated instances as test problems evince the robust performance of the proposed multiobjective algorithm.
Based on genetic algorithm for Job Shop scheduling problem%基于遗传算法的Job Shop调度问题研究
Institute of Scientific and Technical Information of China (English)
景波; 刘莹; 黄兵
2013-01-01
在多平行工作站环境下,为使限定资源分配下的车间调度问题(Job Shop problem,JSP)具有最小总延迟时间；同时又可设定各订单具有不同的开工日(release date)及到期日,提出以可开工时间与结束时间为基础的分解解法,并在遗传算法的基础上构造混合遗传算法(hybrid genetic algorithm,HGA)来实现目标设定.实验结果表明,HGA在问题求解质量与Lingo解的最佳解差异在15％以内,并具备较基本型遗传算法更佳的稳定性.结果显示该算法可帮助管理人员实现智能资源配置与订单调度.%This study addressed a job scheduling and resource allocation problem with distinct release dates and due dates to minimize total tardiness in parallel work centers with a multi-processor environment. To solve the problem, this study also proposed a hybrid genetic algorithm (HGA) with release and due dates based decomposition heuristic. Experimental results show that the percentage deviations between the HGA and Lingo are smaller than 15% , and the HGA has smaller variance than the GA. This study proposed a decision-supporting model, which integrated simulation, genetic algorithms and decision support tools, for solving the JSRA problem by practical perspective.
Institute of Scientific and Technical Information of China (English)
张宇; 孙宪鹏
2001-01-01
把基于多代理技术的JobShop动态调度方法与基于规则的调度策略相结合，在提出的基于多代理的JobShop动态调度系统结构的基础上，着重研究了规则调度策略在各级Agent行为设计中的应用，提出了Agent之间竞争与协作方式及投标计算方法，并在实验系统中对仿真结果进行了分析，为解决车间零件加工动态调度问题提供了一种新的方法。%This paper combines the Job shop dynamic scheduling method based on MAS with the ruled-based scheduling strategy. On the basis of the proposed system framework, we study with emphasis on the applications of scheduling strategy in the agent's behavior design, provide the way of the competition and cooperation among agents and the bid calculation method. The experiment results have proved that this work provides a new method for Job shop dynamic scheduling.
Institute of Scientific and Technical Information of China (English)
欧阳珍; 包先建; 刘志
2016-01-01
针对由电缆的生产路径回流及临时插单现象给该类作业车间带来的排程困难问题，提出了一种基于改进遗传算法的电缆柔性作业车间调度方法。首先研究了电缆柔性生产作业车间计划调度体系，并设计了一种引入元包数组及结合贪婪程序的改进遗传算法，然后给出顺序调度和插单调度问题的求解算法，最后，通过仿真实验对比分析验证了该方法的有效性。%Aiming at the difficulties in flexible job-shop scheduling of cable caused by re-flow manufac-ture,a job-shop planning and scheduling system were studied in this paper and an improved genetic algo-rithm combining with cell array and greedy algorithm were designed to solve the schedule problem in this system,which can simplify the solving process,optimize insertion order schedule and increase the flexibil-ity of the algorithm.Finally,the simulation experiment results proved the effectiveness of method.
Institute of Scientific and Technical Information of China (English)
邹攀; 李蓓智; 杨建国; 施烁; 梁越昇
2015-01-01
A hierarchical antgenetic algorithmbased multiobjective intelligent scheduling algoG rithm was proposed for flexible job shop problem.Its basic features were:(1)the approach was based on the realtime resource information of different scheduling periods;(2)its targets were completion time and machine load etc.;(3)the multiobjective optimization strategy and method were used in an antgenetic hybrid algorithm to obtain the optimal solution.This method could be used in the periodiG cal normal scheduling,the dynamic scheduling scenario and the situation of urgent jobs inserting. Some tests were done on the standard cases and a combined case.Compared to MOGV hybrid algoG rithm,the proposed approach outperformed in 25% of the test cases with a 5%~7% decrease in comG pletion time.As for rests 75% of test cases,the above two algorithms show the same results.ThereG fore,with the ability of optimizing results based on the priorities of objectives and the comprehensive performance of all objective automatically,the effectiveness of the method proposed in this paper was verified.%针对离散制造柔性作业车间实际工况,提出了一种基于分层蚁群遗传算法的柔性作业车间资源驱动的多目标调度方法,其基本特征是：基于连续生产中不同调度周期剩余或空闲资源等调度相关实时信息；基于完工时间和机床负荷等多目标；采用分层蚁群遗传混合算法进行决策,通过逐步筛选,获得优化解.该方法特别适用于车间资源变化、任务执行情况变化、急件任务必须插入等情况下的动态调度.应用标准案例并设计相关组合案例进行了测试,与 MOGV 混合算法相比,25％的案例计算结果优于 MOGV 算法,最大完工时间减少5％~7％,62．5％的案例计算结果等同 MOGV 算法.因此,该智能调度方法不仅可以有效地取得对指定优先目标的最佳优化效果,且可自动获得多目标综合的最优解,智能调度效果显著.
Flexible job-shop scheduling based on multiple ant colony algo-rithm%基于多种群蚁群算法的柔性作业车间调度研究
Institute of Scientific and Technical Information of China (English)
薛宏全; 魏生民; 张鹏; 杨琳
2013-01-01
To the characteristics of flexible job-shop scheduling, this paper designs the disjunctive graph model of the flexible job-shop scheduling and presents the solution of the multiple ant colony algorithm for the competitive rule. According to the labor mode of ant colony, different colonies are located in different processing nodes in the algorithm. By the command of core colony, all types of ant colonies with pheromone updating mechanism and searching traits have mutual compensation of advantages as well as mutual competitive exclusion so that they can potentially cooperate smoothly, and fulfill the scheduling requirements of flexible job-shop scheduling. Through the analysis of the simulating experiment results prove the feasibility and effectiveness of the algorithm.%针对柔性作业车间调度的特点，设计了柔性作业车间调度析取图模型，结合蚁群分工组织的工作方式，给出了基于竞争规则的多种群蚁群算法求解方法。算法中不同种群的蚂蚁被放置在析取图中不同的工序节点上，通过核心种群的引导，充分发挥蚁群协作竞争的并行高效特点，满足柔性作业车间调度的要求。仿真实验表明该算法求解柔性作业车间调度具有可行性和有效性。
Two-Agent Single-Machine Scheduling of Jobs with Time-Dependent Processing Times and Ready Times
Directory of Open Access Journals (Sweden)
Jan-Yee Kung
2013-01-01
Full Text Available Scheduling involving jobs with time-dependent processing times has recently attracted much research attention. However, multiagent scheduling with simultaneous considerations of jobs with time-dependent processing times and ready times is relatively unexplored. Inspired by this observation, we study a two-agent single-machine scheduling problem in which the jobs have both time-dependent processing times and ready times. We consider the model in which the actual processing time of a job of the first agent is a decreasing function of its scheduled position while the actual processing time of a job of the second agent is an increasing function of its scheduled position. In addition, each job has a different ready time. The objective is to minimize the total completion time of the jobs of the first agent with the restriction that no tardy job is allowed for the second agent. We propose a branch-and-bound and several genetic algorithms to obtain optimal and near-optimal solutions for the problem, respectively. We also conduct extensive computational results to test the proposed algorithms and examine the impacts of different problem parameters on their performance.
Institute of Scientific and Technical Information of China (English)
罗润梓; 孙世杰
2005-01-01
In this paper, a semi on-line version on m identical machines M1 , M2, …, Mm ( m ≥ 3 ) was considered, where the processing time of the largest job is known in advance. Our goal is to maximize the minimum machine load, an NPLS algorithm was presented and its worst-case ratio was proved to be equal to m - 1 which is the best possible value. It is concluded that if the total processing time of jobs is also known to be greater than (2 m - 1 )Pmax where pmax is the largest job's processing time, then the worstcase ratio is 2 - 1/m.
Hybrid Genetic Algorithm for Mixed-model Hybrid-shop Scheduling Problem%基于混合遗传算法的混流混合车间协同调度问题
Institute of Scientific and Technical Information of China (English)
李修琳; 鲁建厦; 柴国钟; 汤洪涛; 蒋玲玲
2012-01-01
The paper focused on solving a kind of coordinated scheduling problem for mixed-model hybrid-shop,which composed of job-shop,flow-shop and has the characteristics of mixed-model.First,the model of hybrid shop scheduling problem was presented based on the cost of work piece in process.Then,a hybrid algorithm with genetic algorithm and SA algorithm was proposed to solve the model.In the hybrid algorithm,a three-stage encoding was put to make coordinated code for production sequences of parts,components and final products.And a dynamic temperature parameter was introduced to SA to balance the algorithm＇s efficiency.And finally,an example from freezer production was given to test the model and algorithms presented herein.And the testing results prove the method is effective and excellent.%为解决一类具有多品种混流生产特征和作业车间与流水车间集成的混流混合车间协同调度问题,给出了以在制品成本最小为目标的混流混合车间调度问题模型;采用零件加工、部件装配、产品总装的三段协同编码方法,给出了一种集成模拟退火算法的混合遗传算法,并在模拟退火算法中引入变温度参数来平衡算法效率。最后,通过某冰箱混流装配企业典型实例验证了模型和算法的有效性。
Directory of Open Access Journals (Sweden)
Hadi Mokhtari
2013-01-01
Full Text Available In this paper, the problem of received order scheduling by a manufacturer, with the measure of maximum completion times of orders, has been formulated and then an analytical approach has been devised for its solution. At the beginning of a planning period, the manufacturer receives a number of orders from customers, each of which requires two different stages for processing. In order to minimize the work in process inventories, the no-wait condition between two operations of each order is regarded. Then, the equality of obtained schedules is proved by machine idle time minimization, as objective, with the schedules obtained by maximum completion time minimization. A concept entitled “Order pairing” has been defined and an algorithm for achieving optimal order pairs which is based on symmetric assignment problem has been presented. Using the established order pairs, an upper bound has been developed based on contribution of every order pair out of total machines idle time. Out of different states of improving upper bound, 12 potential situations of order pairs sequencing have been also evaluated and then the upper bound improvement has been proved in each situation, separately. Finally, a heuristic algorithm has been developed based on attained results of pair improvement and a case study in printing industry has been investigated and analyzed to approve its applicability.
Institute of Scientific and Technical Information of China (English)
胡乃平; 王培丽
2011-01-01
针对以最小化完工时间为目标的柔性作业车间调度问题,提出了一种基于微粒群算法的求解方法.该方法利用二元组粒子的形式并采用基于扩展工序和优先规则的编码方法,解决了工序调度的优先级问题和机器分配问题；应用动态惯性权重系数提高了算法的收敛速度.实验仿真证明了该方法可以有效地解决偏柔性作业车间调度问题.%A new method based on particle swarm optimization is proposed to deal with minimizing completion time of flexible job shop scheduling problems. In this method, particle is presented in the form of binary group. Encoding process based on extended operation and priority rule is designed to solve process scheduling priority issues and machinery distribution. Besides, the dynamic inertia weight factor is used to improve the convergence speed of the algorithm. The simulation experiment results indicate that the proposed algorithm is an efficient for the flexible job shop scheduling problems.
基于多Agent的柔性作业车间预先/重调度系统%A Flexible Job Shop Pre/re-scheduling System Based on Agent
Institute of Scientific and Technical Information of China (English)
任海英; 邹艳蕊
2012-01-01
For the problem of random interference from the outside for dynamic scheduling of flexible job shop,a pre/re -scheduling approach was proposed while multi - Agent approach was used and the mean tardiness and the deviation of start time were taken as main objective functions. The method was based on flexible job shop scheduling,and it was system optimized by the negotiation among Agents. Finally,the system was implemented in Java on the Eclipse platform. By the comparison with the genetic algorithm of Jain and the traditional right - shift rescheduling method, the results show that the proposed method significantly outperforms traditional dispatching rules.%针对柔性作业车间动态调度受到来自外部的随机干扰问题,运用多Agent方法,以平均滞后和开始时间背离为主要目标函数,提出了基于柔性作业车间调度问题的预先/重调度方法,并通过Agent之间的协商来达到系统优化.运用Java语言实现调度系统并进行仿真实验分析,通过与Jain的遗传算法和传统的right-shift重调度方法比较,显示了所提出方法的优越性.
Guo, Peng; Cheng, Wenming; Wang, Yi
2015-11-01
This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical parallel machines. In this problem, the processing time of each job is a step function dependent upon its starting time. An individual extended time is penalized when the starting time of a job is later than a specific deterioration date. The possibility of deterioration of a job makes the parallel machine scheduling problem more challenging than ordinary ones. A mixed integer programming model for the optimal solution is derived. Due to its NP-hard nature, a hybrid discrete cuckoo search algorithm is proposed to solve this problem. In order to generate a good initial swarm, a modified Biskup-Hermann-Gupta (BHG) heuristic called MBHG is incorporated into the population initialization. Several discrete operators are proposed in the random walk of Lévy flights and the crossover search. Moreover, a local search procedure based on variable neighbourhood descent is integrated into the algorithm as a hybrid strategy in order to improve the quality of elite solutions. Computational experiments are executed on two sets of randomly generated test instances. The results show that the proposed hybrid algorithm can yield better solutions in comparison with the commercial solver CPLEX® with a one hour time limit, the discrete cuckoo search algorithm and the existing variable neighbourhood search algorithm.
ISAPS: Intelligent Scheduling And Planning System
Energy Technology Data Exchange (ETDEWEB)
King, M.S.; Rutherford, W.C.; Grice, J.V. (Allied-Signal Aerospace Co., Kansas City, MO (USA). Kansas City Div.); Kessel, K.L.; Orel, M. (Intellicorp, Mountain View, CA (USA))
1990-08-01
ISAPS is a scheduling and planning tool for shop floor personnel working in a Flexible Manufacturing System (FMS) environment. The ISAP system has two integrated components: the Predictive Scheduler (PS) and the Reactive Scheduler (RS). These components work cooperatively to satisfy the four goals of the ISAP system, which are: (G1) meet production due dates, (G2) maximize machining center utilization, (G3) minimize cutting tool migration, and (G4) minimize product flow time. The PS is used to establish schedules for new production requirements. The RS is used to adjust the schedules produced by the PS for unforeseen events that occur during production operations. The PS and RS subsystems have been developed using IntelliCorp's Knowledge Engineering Environment (KEE), an expert system development shell, and Common LISP. Software Quality Assurance (SQA) techniques have been incorporated throughout the development effort to assure the ISAP system meets the manufacturing goals and end user requirements. 5 refs., 4 figs.
Research on Dual Resource Constrained Job Shop Scheduling Based on Time Window%基于时窗的双资源约束车间调度研究
Institute of Scientific and Technical Information of China (English)
李兢尧; 孙树栋; 黄媛; 牛刚刚
2011-01-01
针对复杂制造环境下双资源约束作业车间调度问题,提出基于时窗调度策略的继承式遗传算法.该算法基于时窗交集充分利用数控设备加工时工人的时窗空隙；以信息素为载体传承父辈染色体种群的进化经验,并采用基于流量的改进伪随机比例转移规则和自适应云调整参数,生成分支种群；仿照动物的种群组织模式提出多种群King交叉进化模式,并针对双资源约束特点引入资源进化算子；基于被支配域的概念提出扇形分割的轮盘赌选择算子,以较小的计算复杂度选择非劣解集和较优个体.在采用马尔科夫链知识对整个算法的全局收敛性进行理论分析后,通过对随机算例仿真运算结果的统计分析,表明该算法虽然解分布均匀程度不甚理想,但算法搜索性能和收敛性较优.%An inherited genetic algorithm based on time window scheduling is proposed to solve the dual resource constrained job shop scheduling problem with complex manufacturing environment. This algorithm makes full use of the time window of workers during the process of numerical control machines based on the intersection of time windows to actualize positive scheduling. Then the evolutionary experience of parent chromosomes is inherited with pheromone as carrier and the branch population is generated with improved pseudo-random probability transfer rule and adaptive adjusting parameters based on cloud theory. The King crossover operator is proposed on the basis of imitating animal population organization mode and some resource evolutionary operators are introduced in response to the features of dual resource constrained. At last, an efficient roulette selection operator with sector partition is used to select Pareto-optimal solutions and better chromosomes. After the theoretical analysis of the global convergence via Markov chain, the statistical analysis on the simulation results of random benchmarks shows that this
解决柔性车间作业调度问题的侦查包围搜索算法%Probe and Encircle Algorithm for Solving Flexible Job-shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
刘韵; 胡毅; 房超; 罗企
2015-01-01
车间作业调度算法是影响车间生产效率的重要因素之一. 由于调度算法属于NP-难问题,至今仍然没有办法在有限时间内找到最优解. 文章提出了一种元启发式搜索方法:侦查包围算法( PEA) ,通过局部搜索,旨在有限时间内最大可能的趋近于最优解. 该算法吸取了禁忌搜索算法和模拟退火算法的优点,对其缺点进行改进. 文中将此算法应用到柔性车间作业调度问题,阐述算法的实践. 实验结果与遗传算法和禁忌搜索进行比较,证明在作业数目较大的情况下,具有良好的效果.%Scheduling Algorithm has become one of the most important factors which influence Job-shop productivity. Because of being proved as NP-hard problem, there are no Job-shop Scheduling Algorithms can achieve optimal solution. This paper proposes a meta-algorithm:Probe and Encircle Algorithm ( PEA) aim to get the approximate optimum solution via local search within a limited time. This algorithm absorbs the merit of Taboo Search Algorithm ( TSA) and The Simulated Annealing Algorithm ( SAA) , and so do a-void their flaws. A Flexible Job-shop Scheduling Problem has been solved by Probe and Encircle Algorithm which will be described in detail. Compared with GA and TS, it has been proved more effective in large scale problems.
HYBRID PARTICLE SWARM OPTIMISATION FOR FLEXIBLE JOB-SHOP SCHEDULING PROBLEM%求解柔性作业车间调度的混合粒子群算法
Institute of Scientific and Technical Information of China (English)
李俊; 刘志雄; 邵正宇
2015-01-01
将粒子群算法运用于求解柔性作业车间调度问题，采用基于轮盘赌的编码方法以及基于邻域互换的局部搜索方法。通过两个不同规模算例的试验计算，与基于粒子位置取整的编码方法进行对比分析，说明了轮盘赌编码方法求解柔性作业车间调度问题的有效性。且采用该编码方法的混合粒子群算法在求解柔性作业车间调度问题时具有更好的求解性能。%Applying the particle swarm optimisation to solving the flexible job-shop scheduling problem,we adopted the roulette-based encoding method and the neighbourhood swap-based local search method.By the test calculation of two examples with different scales and analysing the comparison of them with the encoding method based on particle position rounding,we proved the effectiveness of the roulette-based encoding method in solving flexible job-shop scheduling problem.Moreover,the hybrid particle swarm optimisation using this encoding method has better solution performance in optimising the flexible job-shop scheduling problem.
Institute of Scientific and Technical Information of China (English)
黄英杰; 姚锡凡; 古耀达
2012-01-01
In order to better solve large-scale flexible shop scheduling problems and improve the searching performance of flexible shop scheduling algorithms, a hybrid particle swarm optimization(HPSO) algorithm based on entropy was proposed, which combines the particle swarm optimization, genetic algorithm with simulated annealing algorithm, and the inertia factor and mutation probability were adjusted adaptive-ly according to population entropy in order to enhance the searching ability of the algorithm and overcome the premature convergence of the algorithm. Simulation results on benchmark instances have shown that the proposed algorithm can solve flexible shop scheduling problems, and has obvious advantages in the accuracy of optimization over traditional optimization algorithms.%为了更好地求解大规模柔性车间调度问题,提高柔性车间调度算法的寻优性能,提出一种基于熵的混合粒子群算法.该算法把粒子群算法、遗传算法和模拟退火算法相结合,同时用种群熵自适应调节惯性系数和变异概率,以增强算法的寻优能力和克服算法的过早收敛.典型实例仿真结果表明,该算法能更好地求解柔性车间调度问题,与传统的优化算法相比,在优化精度上具有明显的优越性.
Institute of Scientific and Technical Information of China (English)
陆志强; 张思源; 崔维伟
2015-01-01
针对离散流水车间,设备故障率函数服从威布尔分布,在考虑维护策略的基础上,以工件的最终完工时间期望值为质量鲁棒性指标、以所有工序的开始加工时间的延迟总和的期望值为解鲁棒性指标,建立了不确定性环境下预防性维护(Preventive maintenance, PM)和生产调度的集成优化模型,联合决策各工序的开始加工时间和预防性维护位置。进一步,设计了基于工件优先列表、有效代理指标、邻域搜索机制的三阶段启发式算法对模型进行求解。最后,数值实验与传统方法对比结果表明,系统最优缓冲时间随着解鲁棒性权重的增大而逐渐增加,且质量鲁棒性堕化速度远小于解鲁棒性提升的速度,使得其与传统方法相比总体目标愈加优异。%For the flow-shops, where the machines0 failure function is governed by the Weibull distribution, considering the maintenance strategy, a joint model of integrating run-based preventive maintenance (PM) and production scheduling is proposed under the uncertainty environment, in which the planned start times of jobs and the PM times are determined simultaneously. And, the makespan is selected as the quality robustness measure;the total delay of the jobs0 start time is selected as the solution robustness measure. Then, a three-phase heuristic algorithm based on the priority list, surrogate measure, and local search is devised to solve the mathematic model. Experimental results demonstrate that the solution robustness can be significantly improved at the cost of very little degradation in quality robustness using our algorithm compared with the traditional way.
Institute of Scientific and Technical Information of China (English)
王长军; 席裕庚
2005-01-01
Considering the independent optimization requirement for each demander of modern manufacture, we explore the application of noncooperative game in production scheduling research,and model scheduling problem as competition of machine resources among a group of selfish jobs.Each job has its own performance objective. For the single machine, multi-jobs and non-preemptive scheduling problem, a noncooperative game model is established. Based on the model, many problems about Nash equilibrium solution, such as the existence, quantity, properties of solution space,performance of solution and algorithm are discussed. The results are tested by numerical example.
Parallel machine scheduling with release dates, due dates and family setup times
Schutten, J.M.J.; Leussink, R.A.M.
1996-01-01
In manufacturing, there is a fundamental conflict between efficient production and delivery performance. Maximizing machine utilization by batching similar jobs may lead to poor delivery performance. Minimizing customers' dissatisfaction may lead to an inefficient use of the machines. In this paper,
Institute of Scientific and Technical Information of China (English)
WU Bo; SHI Guoxin; DING Yufeng; JIANG Zhengfeng
2006-01-01
Shop scheduling problem is core part and research hot in modern manufacture system, it has important meaning for decreasing operating costs, shortening production period and so on. Based on shop scheduling problems, this paper mainly discuss and classify uncertainty factors of the shop scheduling, Meanwhile set up corresponding reliability evaluation model according to some uncertainty factors, and so it can better direct shop scheduling.
Birgin, Ernesto G.; Ronconi, Débora P.
2012-10-01
The single machine scheduling problem with a common due date and non-identical ready times for the jobs is examined in this work. Performance is measured by the minimization of the weighted sum of earliness and tardiness penalties of the jobs. Since this problem is NP-hard, the application of constructive heuristics that exploit specific characteristics of the problem to improve their performance is investigated. The proposed approaches are examined through a computational comparative study on a set of 280 benchmark test problems with up to 1000 jobs.
Directory of Open Access Journals (Sweden)
Hamidreza Haddad
2012-04-01
Full Text Available This paper tackles the single machine scheduling problem with dependent setup time and precedence constraints. The primary objective of this paper is minimization of total weighted tardiness. Since the complexity of the resulted problem is NP-hard we use metaheuristics method to solve the resulted model. The proposed model of this paper uses genetic algorithm to solve the problem in reasonable amount of time. Because of high sensitivity of GA to its initial values of parameters, a Taguchi approach is presented to calibrate its parameters. Computational experiments validate the effectiveness and capability of proposed method.
Directory of Open Access Journals (Sweden)
Chinyao Low
2016-01-01
Full Text Available This paper addresses the problem of scheduling n independent jobs on a single machine with a fixed unavailability interval, where the aim is to minimize the total earliness and tardiness (TET about a common due date. Two exact methods are proposed for solving the problem: mixed integer linear programming formulations and a dynamic programming based method. These methods are coded and tested intensively on a large data set and the results are analytically compared. Computational experiments show that the dynamic programming method is efficient in obtaining the optimal solutions and no problems due to memory requirement.
Directory of Open Access Journals (Sweden)
Mansooreh Madani-Isfahani
2013-04-01
Full Text Available In this paper, we present a new Imperialist Competitive Algorithm (ICA to solve a bi-objective scheduling of parallel-unrelated machines where setup times are sequence dependent. The objectives include mean completion tasks and mean squares of deviations from machines workload from their averages. The performance of the proposed ICA (PICA method is examined using some randomly generated data and they are compared with three alternative methods including particle swarm optimization (PSO, original version of imperialist competitive algorithm (OICA and genetic algorithm (GA in terms of the objective function values. The preliminary results indicate that the proposed study outperforms other alternative methods. In addition, while OICA performs the worst as alternative solution strategy, PSO and GA seem to perform better.
Parallel patterns determination in solving cyclic flow shop problem with setups
Directory of Open Access Journals (Sweden)
Bożejko Wojciech
2017-06-01
Full Text Available The subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP. We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.
Development of a diagnostic schedule for a defective LC-195V5 CNC milling machine using PERT
Directory of Open Access Journals (Sweden)
Oluwole Olayinka AGBOOLA
2016-07-01
Full Text Available Computer Numerical Control CNC machine tools usage are more and more extensive, its fault diagnosis research is becoming more essential. Failure forms accorded these machines are diversified, and fault reasons are very complicated. It should not be left unattended to, because this could lead to further deterioration. One of the parameters used in determining the efficiency of a technician (who repairs machine tools is the time saved in locating faults, hence the development of a diagnostic schedule which shows the sequential means of troubleshooting within a possible shortest time. In this research two approaches were used to diagnose a defective LC-195V5 CNC milling machine. Forward Pass (FP, which involves the diagnosis from electrical parts through Computer (CNC to mechanical component and Backward Pass (BP which involves the diagnosis from computer component through electrical parts to mechanical parts. Three different trials were conducted for each of the mode of diagnosis and the time to diagnose each component part was recorded. Based on the interrelationship of the component parts, two separate PERT (Project Evaluation & Review Techniques network diagrams were drawn and their Critical Paths were determined. The study reveals that Foward Pass method was able to save more time.
Institute of Scientific and Technical Information of China (English)
刘洪毓
2004-01-01
Nowadays you no longer need to walk round hundreds of shops looking for the items you need. You can shop for just about anything from your armchair. All you need is a computer and access(进入) to the Internet.
Ant Foraging Behavior for Job Shop Problem
Directory of Open Access Journals (Sweden)
Mahad Diyana Abdul
2016-01-01
Full Text Available Ant Colony Optimization (ACO is a new algorithm approach, inspired by the foraging behavior of real ants. It has frequently been applied to many optimization problems and one such problem is in solving the job shop problem (JSP. The JSP is a finite set of jobs processed on a finite set of machine where once a job initiates processing on a given machine, it must complete processing and uninterrupted. In solving the Job Shop Scheduling problem, the process is measure by the amount of time required in completing a job known as a makespan and minimizing the makespan is the main objective of this study. In this paper, we developed an ACO algorithm to minimize the makespan. A real set of problems from a metal company in Johor bahru, producing 20 parts with jobs involving the process of clinching, tapping and power press respectively. The result from this study shows that the proposed ACO heuristics managed to produce a god result in a short time.
Institute of Scientific and Technical Information of China (English)
薄洪光; 潘裕韬; 马晓燕
2013-01-01
针对由异速机构成的双机成比例无等待流水线的加工特点，研究了机器扰动工况下的生产重调度问题，提出了兼顾初始调度目标（最小化制造期）和扰动修复目标（最小化工件滞后时间和）的干扰管理方法。在最短加工时间优先（ SPT）排序规则的最优解特性分析基础上，证明了右移初始加工时间表是事后干扰管理的最优调度方案，建立了基于SPT规则的事前干扰管理模型，设计了基于理想点趋近的多目标处理策略，提出了离散量子微粒群优化与局部搜索机制相结合的启发式模型求解算法。算例实验结果表明，本文提出的干扰管理模型和算法是有效的。%To solve the rescheduling problem for a random or an anticipated machine disruption in proportional two-machine no-wait flow shop , a disruption management method is proposed that considering both the original objective(min.makespan)and the disruption repairing objective (min.summation of delay time).Based on the shortest processing time ( SPT) rule optimal analyzing , it is proved that the right shift original schedule is optimal for the post-disruption management problem .And a predictive disruption management model is formulated based on SPT rule .By combining the ideal point-based multi-objective approaching policy with the discrete quantum-behaved particle swarm optimization and local search mechanism , a heuristic algorithm is proposed .The numeri-cal experiments show that the model and algorithm are effective .
Fuzzy Gain Scheduling of PI Controller for Dual Star Induction Machine fed by a Matrix Converter
B. Meliani; A. Meroufel; H. Khouidmi
2012-01-01
The aim of this paper is to present a full digital implementation of a field orientation controlled Double Star induction Machine, and a PI controller is designed to control the speed, the machine is fed by a matrix converter. The advent of vector control technique has partially solved DSIM control problems because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Fuzzy logic and neural network Based controllers are consider...
利用猫群算法求解流水车间调度问题%The research of flow-shop scheduling problem based on cat swarm optimization
Institute of Scientific and Technical Information of China (English)
马邦雄; 叶春明
2014-01-01
Flow-shop Scheduling Problem ( FSP) is a kind of traditional production scheduling problem ,which has been shown to be NP-hard problem ,swarm intelligence algorithm showed excellent performance in solving such problems .Cat swarm optimization is a relatively new swarm intelligence algorithm ,the patterns of behavior of cats is divided into search mode and tracking mode to achieve the purpose of optimization performed by a certain percentage of the number of cats in two different modes .By the results of the comparison with standard particle swarm optimization and bats algorithm for solving the flow shop scheduling problem ,indi-cating that the basic cat swarm optimization scheduling problem in a well-optimized performance and application prospects .%流水车间调度问题是一类传统的生产调度问题，其已被证明是NP-hard问题，而群体智能算法在求解此类问题中表现出优秀的性能。猫群算法是一种较新颖的群体智能算法，将猫群的行为模式分为搜寻模式和跟踪模式，通过一定比例的猫群数量执行两种不同的模式来达到优化的目的。通过将猫群算法与标准粒子群算法和蝙蝠算法在求解流水车间调度问题的结果进行比较，表明了猫群算法在调度问题中的良好优化性能以及应用前景。
Chaos genetic programming method for job-shop scheduling problem%一种求解车间调度问题的混沌遗传规划方法
Institute of Scientific and Technical Information of China (English)
周强; 崔逊学
2011-01-01
作业车间调度问题是制造业的一个经典 NP-hard 组合优化难题.提出一种基于混沌遗传规划的调度算法,利用遗传规划进行染色体的结构设计,采用混沌序列改善初始种群质量,利用混沌扰动来维持进化群体的多样性,并自适应调整个体权重,使算法具有优良的综合求解性能.实验表明,算法对典型的标准调度测试问题具有较强的全局搜索能力,甘特图表明其获得的最优解优于当前已知的最优解历史记录,对比结果表明了该方法的有效性.%The job-shop scheduling problem is an NP-hard combinational optimization problem in the manufacturing field. The paper proposes a job-shop scheduling algorithm based on chaos genetic programming. Genetic programming is adopted to design a chromosome structure,the chaos sequence method is used to improve the quality of initial population,chaos disturbances are taken to maintain the diversity of evolutionary population, and the self-adaptive adjusting method of individual weight is applied.Accordingly the proposed algorithm has a comprehensive solving capacity for a scheduling problem. Simulation experiments show that it has better ability to find the global optimum for several typical scheduling testing benchmarks. The results of Gantt charts point out that the optimum solutions obtained by this novel algorithm are better than the historic ones. The comparison of the results reveals the feasibility and efficiency of the method.
Hybrid bee colony algorithm for flexible Job Shop scheduling problem%混合蜂群算法求解柔性作业车间调度问题
Institute of Scientific and Technical Information of China (English)
李修琳; 鲁建厦; 柴国钟; 汤洪涛
2011-01-01
To solve the flexible Job Shop scheduling problem, a hybrid intelligent optimization algorithm based on bee colony model to improve the searching accuracy and efficiency was proposed. Combined bee colony optimization with stochastic methods, a novel method for generating initial population was put forward to improve initial population quality. To improve search accuracy, simulated annealing was used to update onlooker bees, and annealing coefficient was used to refine neighbor domains. Aiming at characteristics of flexible Job Shop scheduling problem, update method for neighborhood with controlled scale was established. By using flexible Job Shop standard algorithm, the validity and superiority of the algorithm was proved by comparing the simulation program with other algorithm.%为解决柔性作业车间调度问题,提出一种基于蜂群模型的混合群智能优化算法.在算法初始化阶段提出了蜂群优化算法结合随机方法的种群初始化方法,提高了初始种群质量；为提高算法搜索精度,在观察蜂阶段采用模拟退火算法更新观察蜂群,并以退温系数调节邻域规模,随算法进程细化搜索范围；针对柔性作业车间调度问题特点,建立了可控规模的邻域更新方法.采用柔性作业车间标准算例,通过仿真编程和与其他算法的比较,验证了算法的有效性和优越性.
Single-machine scheduling of two activities with slack:CPM to minimize the total tardiness
Institute of Scientific and Technical Information of China (English)
LI Xing-mei; QI Jian-xun
2007-01-01
In a CPM network, the longest path problem is one of the most important subjects. According to the intrinsic principle of CPM network, the length of the paths between arbitrary two nodes is presented. Furthermore, the length of the longest path from start node to arbitrary node and from arbitrary node to end node is proposed. In view of a scheduling problem of two activities with float in the CPM scheduling, we put forward Barycenter Theory and prove this theory based on the algorithm of the length of the longest path. By this theory, we know which activity should be done firstly. At last, we show our theory by an example.
Directory of Open Access Journals (Sweden)
Mohammad Hossein Zarei
2016-01-01
Full Text Available Job selection and scheduling are among the most important decisions for production planning in today’s manufacturing systems. However, the studies that take into account both problems together are scarce. Given that such problems are strongly NP-hard, this paper presents an approach based on two heuristic algorithms for simultaneous job selection and scheduling. The objective is to select a subset of candidate jobs and schedule them in such a way that the total net profit is maximized. The cost components considered here include jobs' processing costs and weighted earliness/tardiness penalties. Two heuristic algorithms; namely scatter search (SS and simulated annealing (SA, were employed to solve the problem for single machine environments. The algorithms were applied to several examples of different sizes with sequence-dependent setup times. Computational results were compared in terms of quality of solutions and convergence speed. Both algorithms were found to be efficient in solving the problem. While SS could provide solutions with slightly higher quality for large size problems, SA could achieve solutions in a more reasonable computational time.
Fuzzy Gain Scheduling of PI Controller for Dual Star Induction Machine fed by a Matrix Converter
Directory of Open Access Journals (Sweden)
B. Meliani
2012-06-01
Full Text Available The aim of this paper is to present a full digital implementation of a field orientation controlled Double Star induction Machine, and a PI controller is designed to control the speed, the machine is fed by a matrix converter. The advent of vector control technique has partially solved DSIM control problems because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Fuzzy logic and neural network Based controllers are considered as potential candidates for such an application. In this paper the fuzzy logic system is used on-line to generate the PI controller parameters. Simulink results for a 4.5 kW six-phase induction machine are presented and analyzed using a matlab environment. Obtained results demonstrated that the proposed control scheme is able to obtain high performances.
Feyock, Anthony J.
This paper presents an analysis of the job performed by an offset press operator (alternate title is offset duplicating machine operator) of a Multilith 1250 W. First covered is work performed, as follows: prepares dampening unit for printing run, prepares inking unit for printing, readies printing plate for printing, sets up press for running,…
Institute of Scientific and Technical Information of China (English)
帅旗; 姚锡凡; 杨莹
2012-01-01
对于多目标job-shop柔性制造系统调度决策问题,在实际调度过程中不同优化目标之间存在层次关系,同时在实际生产环境中所调度追求目标并非固定常常处于变动之中.为此提出了基于Agent多层次目标任务调度规划模型,将复杂的求解问题按层次分解为具有相对独立性的各求解子问题单元并建立各单元间的联系机制,采用交互式策略对复杂调度问题进行求解.通过对不同调度算例的求解并得到满意调度方案,并验证此方法的合理性及可行性.%To solve the problem of flexible job-shop scheduling with multi- objective optimization, it is impossible and difficult to get a global optimized result because of the complexity of the optimization and the related hierarchy of multi- objective group. This paper proposes a scheduling algorithm based on multi - agent which is used to decompose the complex problem into some simple problem units and establish the hierarchical relation between those problem units. Using the algorithm with interactive strategy, some job- shop scheduling problems wit h multi- objective optimization are solved, and the proposed algorithm is proved to be reasonable and feasible.
Institute of Scientific and Technical Information of China (English)
潘逢山; 叶春明
2012-01-01
微粒群优化算法(Particle Swarm Optimization,PSO)是起源于鸟群和鱼群群体运动行为的研究,是在蚁群算法提出之后的又一种新的进化计算技术,具有典型的群体智能特性.本文构建了干扰为工件到达的流水车间调度干扰管理模型,其经典目标函数为最大完工时间和干扰目标函数为干扰时间差相混合.本文运用微粒群优化算法求解流水线干扰管理调度问题,给出了计算实例并进行了详细分析,并对干扰管理问题和重调度问题进行了测试分析,得出了有参考意义的结果.%Particle swarm optimization (PSO) with the typical characteristic of swarm intelligence is a kind of novel evolution algorithm after ant colony algorithm, it inspired by social behavior of bird flocking or fish schooling. In addition, computation model is set up for disruption management on the flow shop scheduling with the arrival of new job, whose objective function is mix makespan with the time difference. Particle swarms optimization algorithm is adopted to test the disruption management scheduling problems for flow shop and a detailed analysis is given. The disruption management and re-scheduling issues are also tested and analyzed. The results of the reference is obtained.
Institute of Scientific and Technical Information of China (English)
MA Feng-cai; ZHANG Qun
2009-01-01
In this paper, daily production scheduling is studied based on the Third Steelmaking Plant of Wuhan Iron and steel corporation (WISCO). To make sure the daily production plan is feasible, method of casting gToup is established, and the compatibility between two converters and three continuous casting devices in the Third Steelmaking Plant of WISCO is analyzed. The process flow chart of daily production scheduling is given in this paper. Then, algorithms and procedures for the simulation of daily production plan is developed. Using the actual data from the Third Steelmaking Plant, the feasible daily steelmaking plan and cast plan are given. The plan contains 7 groups of cast plan, figured out 54 converters, and a- bout 13,500 tons steel.
Single-machine group scheduling problems with deteriorating and learning effect
Xingong, Zhang; Yong, Wang; Shikun, Bai
2016-07-01
The concepts of deteriorating jobs and learning effects have been individually studied in many scheduling problems. However, most studies considering the deteriorating and learning effects ignore the fact that production efficiency can be increased by grouping various parts and products with similar designs and/or production processes. This phenomenon is known as 'group technology' in the literature. In this paper, a new group scheduling model with deteriorating and learning effects is proposed, where learning effect depends not only on job position, but also on the position of the corresponding job group; deteriorating effect depends on its starting time of the job. This paper shows that the makespan and the total completion time problems remain polynomial optimal solvable under the proposed model. In addition, a polynomial optimal solution is also presented to minimise the maximum lateness problem under certain agreeable restriction.
Full Glowworm Swarm Optimization Algorithm for Whole-Set Orders Scheduling in Single Machine
Directory of Open Access Journals (Sweden)
Zhang Yu
2013-01-01
Full Text Available By analyzing the characteristics of whole-set orders problem and combining the theory of glowworm swarm optimization, a new glowworm swarm optimization algorithm for scheduling is proposed. A new hybrid-encoding schema combining with two-dimensional encoding and random-key encoding is given. In order to enhance the capability of optimal searching and speed up the convergence rate, the dynamical changed step strategy is integrated into this algorithm. Furthermore, experimental results prove its feasibility and efficiency.
Full Glowworm Swarm Optimization Algorithm for Whole-Set Orders Scheduling in Single Machine
Zhang Yu; Xiaomei Yang
2013-01-01
By analyzing the characteristics of whole-set orders problem and combining the theory of glowworm swarm optimization, a new glowworm swarm optimization algorithm for scheduling is proposed. A new hybrid-encoding schema combining with two-dimensional encoding and random-key encoding is given. In order to enhance the capability of optimal searching and speed up the convergence rate, the dynamical changed step strategy is integrated into this algorithm. Furthermore, experimental results prove it...
Full glowworm swarm optimization algorithm for whole-set orders scheduling in single machine.
Yu, Zhang; Yang, Xiaomei
2013-01-01
By analyzing the characteristics of whole-set orders problem and combining the theory of glowworm swarm optimization, a new glowworm swarm optimization algorithm for scheduling is proposed. A new hybrid-encoding schema combining with two-dimensional encoding and random-key encoding is given. In order to enhance the capability of optimal searching and speed up the convergence rate, the dynamical changed step strategy is integrated into this algorithm. Furthermore, experimental results prove its feasibility and efficiency.
Sansone, Lori A.
2012-01-01
Doctor shopping is defined as seeing multiple treatment providers, either during a single illness episode or to procure prescription medications illicitly. According to the available literature, prevalence rates of doctor shopping vary widely, from 6.3 to 56 percent. However, this variability is partially attributable to research methodology, including the study definition of doctor shopping as well as the patient sample. The reasons for doctor shopping are varied. Some patient explanations for this phenomenon relate to clinician factors, such as inconvenient office hours or locations, long waiting times, personal characteristics or qualities of the provider, and/or insufficient communication time between the patient and clinician. Some patient explanations relate to personal factors and include both illness factors (e.g., symptom persistence, lack of understanding or nonacceptance of the diagnosis or treatment) as well as psychological factors (e.g., somatization, prescription drug-seeking). Importantly, not all doctor shopping is driven by suspect motivations. Being aware of these various patient justifications for doctor shopping is important in understanding and managing these challenging patients in the clinical setting, whether they emerge in psychiatric or primary care environments. PMID:23346518
A comparison of rescheduling policies for online flow shops to minimize tardiness
Tokola, Henri; Ahlroth, Lauri; Niemi, Esko
2014-02-01
In practical situations, flow shops usually have some policies on rescheduling previously scheduled jobs. This article compares three of these rescheduling policies: an unrestricted one where previously scheduled jobs can be moved freely, one where jobs can only be moved forward in the schedule, and one where jobs that have already been scheduled cannot be moved at all. The comparison is performed by considering the minimization of tardiness. While unrestricted rescheduling should generally give the best solution, moving jobs only forward can be more practical as in general production, material orders can be delayed but seldom advanced. This article points out that moving jobs only forward is not significantly worse than the unrestricted scheduling. When cases with small numbers of jobs and machines are analysed both policies give similar tardiness. Numerical experiments show that the differences between these two rescheduling policies are rather small in larger problems as well.
Yang, Yahong; Zhao, Fuqing; Hong, Yi; Yu, Dongmei
2005-12-01
Integration of process planning with scheduling by considering the manufacturing system's capacity, cost and capacity in its workshop is a critical issue. The concurrency between them can also eliminate the redundant process and optimize the entire production cycle, but most integrated process planning and scheduling methods only consider the time aspects of the alternative machines when constructing schedules. In this paper, a fuzzy inference system (FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop manufacturing system is presented. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The mean time to failure (MTF) values is input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the particle swarm optimization (PSO) have been used to balance the load for all the machines. Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling.
Deadline aware virtual machine scheduler for scientific grids and cloud computing
Khalid, Omer; Anthony, Richard; Petridis, Miltos; Parrot, Kevin; Schulz, Markus; 10.1109/WAINA.2010.107
2010-01-01
Virtualization technology has enabled applications to be decoupled from the underlying hardware providing the benefits of portability, better control over execution environment and isolation. It has been widely adopted in scientific grids and commercial clouds. Since virtualization, despite its benefits incurs a performance penalty, which could be significant for systems dealing with uncertainty such as High Performance Computing (HPC) applications where jobs have tight deadlines and have dependencies on other jobs before they could run. The major obstacle lies in bridging the gap between performance requirements of a job and performance offered by the virtualization technology if the jobs were to be executed in virtual machines. In this paper, we present a novel approach to optimize job deadlines when run in virtual machines by developing a deadline-aware algorithm that responds to job execution delays in real time, and dynamically optimizes jobs to meet their deadline obligations. Our approaches borrowed co...
Wang Ting; Cai Lin-qin; Fu Yao; Zhu Tingcheng
2013-01-01
It is wellknown that mine gas gushing forecasting is very significant to ensure the safety of mining. A wavelet-based robust relevance vector machine based on sensor data scheduling control for modeling mine gas gushing forecasting is presented in the paper. Morlet wavelet function can be used as the kernel function of robust relevance vector machine. Mean percentage error has been used to measure the performance of the proposed method in this study. As the mean prediction error of mine gas g...
Institute of Scientific and Technical Information of China (English)
李蓓智; 杨建国; 周亚勤; 邵世煌
2003-01-01
Based on the biological immune concept, immune response mechanism and expert system, a dynamic and intelligent scheduling model toward the disturbance of the production such as machine fault,task insert and cancel etc. Is proposed. The antibody generation method based on the sequence constraints and the coding rule of antibody for the machining procedure is also presented. Using the heuristic antibody generation method based on the physiology immune mechanism, the validity of the scheduling optimization is improved, and based on the immune and expert system under the event-driven constraints, not only Job-shop scheduling problem with multi-objective can be solved, but also the disturbance of the production be handled rapidly. A case of the job-shop scheduling is studied and dynamic optimal solutions with multi-objective function for agile manufacturing are obtained in this paper. And the event-driven dynamic rescheduling result is compared with right-shift rescheduling and total rescheduling.
Directory of Open Access Journals (Sweden)
Shangchia Liu
2015-01-01
Full Text Available In the field of distributed decision making, different agents share a common processing resource, and each agent wants to minimize a cost function depending on its jobs only. These issues arise in different application contexts, including real-time systems, integrated service networks, industrial districts, and telecommunication systems. Motivated by its importance on practical applications, we consider two-agent scheduling on a single machine where the objective is to minimize the total completion time of the jobs of the first agent with the restriction that an upper bound is allowed the total completion time of the jobs for the second agent. For solving the proposed problem, a branch-and-bound and three simulated annealing algorithms are developed for the optimal solution, respectively. In addition, the extensive computational experiments are also conducted to test the performance of the algorithms.
Directory of Open Access Journals (Sweden)
Shang-Chia Liu
2015-01-01
Full Text Available In the recent 20 years, scheduling with learning effect has received considerable attention. However, considering the learning effect along with release time is limited. In light of these observations, in this paper, we investigate a single-machine problem with sum of processing times based learning and ready times where the objective is to minimize the makespan. For solving this problem, we build a branch-and-bound algorithm and a heuristic algorithm for the optimal solution and near-optimal solution, respectively. The computational experiments indicate that the branch-and-bound algorithm can perform well the problem instances up to 24 jobs in terms of CPU time and node numbers, and the average error percentage of the proposed heuristic algorithm is less than 0.5%.
Sum-of-Processing-Times-Based Two-Agent Single-Machine Scheduling with Aging Effects and Tardiness
Directory of Open Access Journals (Sweden)
Do Gyun Kim
2015-01-01
Full Text Available We consider a two-agent single-machine scheduling problem that minimizes the total weighted tardiness of one agent under the restriction that the second agent is prohibited from having tardy jobs. The actual processing times of all jobs are affected by a sum-of-processing-times-based aging effect. After showing the NP-hardness of the problem, we design a branch-and-bound (B&B algorithm to find an optimal solution by developing dominance properties and a lower bound for the total weighted tardiness to increase search efficiency. Because B&B takes a long time to find an optimal solution, we propose a genetic algorithm as an efficient, near optimal solution approach. Four methods for generating initial populations are considered, and edge recombination crossover is adopted as a genetic operator. Through numerical experiments, we verify the outstanding performance of the proposed genetic algorithm.
Institute of Scientific and Technical Information of China (English)
Foulds,L.R.; TangGuochun
1999-01-01
A single machine scheduling problem with controllable processing times and compression costs is considered. The objective is to find an optimal sequence to minimize the cost ofcompletion times and the cost of compression. The complexity of this problem is still unknown.In Part Ⅱ of this paper,the authors have considered a special case where the compression timesand the compression costs are equal among all jobs. Such a problem appears polynomiafiy solvable by developing an O(n2) algorithm. In this part(Part Ⅱ ),a general case where the controllable processing times and the compression costs are not equal is discussed. Authors proposehere two heuristics with the first based on some previous work and the second based on the algorithm developed in Part Ⅱ . Computational results are presented to show the efficiency and therobustness of these heuristics.
Shopping Malls - ShoppingCenters
NSGIC GIS Inventory (aka Ramona) — Collected from a variety of sources both commercial and internal, this layer represents shopping center locations within Volusia County and is maintained by the...
Shopping Malls - ShoppingCenters
NSGIC Local Govt | GIS Inventory — Collected from a variety of sources both commercial and internal, this layer represents shopping center locations within Volusia County and is maintained by the...
Institute of Scientific and Technical Information of China (English)
吴立华; 陈新度; 陈庆新; 陈新
2011-01-01
由于模具生产属于非重复性生产模式,各工序的工时具有很强的随机不确定性,这给模具车间制定合理可行的作业计划带来了一定的困难。针对这一实际问题,提出了一种考虑任务工时不确定性的前摄性车间调度算法。首先,分析了模具精加工环节的两道关键工序对制造系统稳定性的影响,并基于工序的工时不确定特性,建立了任务工时不确定的离散概率模型;然后,以调度方案的稳定度作为优化目标,构建了两阶段流水车间前摄性调度模型,针对该模型,提出了一种变宽集束搜索求解算法;最后,将该算法与定宽集束搜索算法进行对比分析,结果表明该算法能很好地兼顾求解质量和计算时间。%Due to non-repetitive manufacturing of mould die industry,the processing time of operations is random uncertainty.Hence,it is difficult to make a reasonable and feasible baseline schedule in the mould shop floor.To deal with this problem,a proactive scheduling algorithm with uncertain processing times was proposed herein.Firstly,how did two critical operations in the mould finishing stage to impact the stability of whole manufacturing system was analyzed.Based on the characteristics of uncertainty of processing time quota,a discrete probability model of processing time uncertainty was developed.Secondly,a proactive scheduling model of two-stage flow shop was built,whose objective was schedule stability.Furthermore,a width-variable beam search（VBS） algorithm was presented for solving the proactive scheduling model.Finally,the comparative analysis with the fixed width beam search（FBS） was pursued.And,the computational results show that the presented algorithm has a good balance between solution quality and computation time.
Research on grading scheduling model of flexible job distributed work-shop%面向柔性作业分布式车间的分层调度模型研究
Institute of Scientific and Technical Information of China (English)
杨江波; 陈友玲; 曹楠
2014-01-01
针对多车间分布式制造系统调度优化问题，结合车间实际生产情况，提出一种基于目标级联法和遗传算法的层次调度模型。模型将生产调度过程划分为生产计划层、车间调度层和零件规划层，并将整体时间最短的优化目标划分到各个层次，通过层层优化达到时间最优后反馈至上层，以实现整体调度时间最优。以3个制造车间协调调度问题为例，验证了该模型在零件分配和零件的工艺路线选择上的合理性和有效性。%Aiming at the workshop distributed manufacturing system scheduling optimization problems, combined with the actual production situation, a hierarchical scheduling model based on analytical target cascading and genetic algo-rithms is proposed. The model divides the scheduling process into three parts:the planning layer, the workshop scheduling layer and the job planning layer, the whole time minimal as its target is divided into various levels, to achieve the overall optimal scheduling time. Taking a three job-shop system as an example to verify the proposed model could be used in jobs allocation and program the path of each job.
Directory of Open Access Journals (Sweden)
Vinícius Vilar Jacob
2016-01-01
Full Text Available This paper addresses a single-machine scheduling problem with sequence-dependent family setup times. In this problem the jobs are classified into families according to their similarity characteristics. Setup times are required on each occasion when the machine switches from processing jobs in one family to jobs in another family. The performance measure to be minimized is the total tardiness with respect to the given due dates of the jobs. The problem is classified as NP-hard in the ordinary sense. Since the computational complexity associated with the mathematical formulation of the problem makes it difficult for optimization solvers to deal with large-sized instances in reasonable solution time, efficient heuristic algorithms are needed to obtain near-optimal solutions. In this work we propose three heuristics based on the Iterated Local Search (ILS metaheuristic. The first heuristic is a basic ILS, the second uses a dynamic perturbation size, and the third uses a Path Relinking (PR technique as an intensification strategy. We carry out comprehensive computational and statistical experiments in order to analyze the performance of the proposed heuristics. The computational experiments show that the ILS heuristics outperform a genetic algorithm proposed in the literature. The ILS heuristic with dynamic perturbation size and PR intensification has a superior performance compared to other heuristics.
Directory of Open Access Journals (Sweden)
Chiuh Cheng Chyu
2012-06-01
Full Text Available This paper studies the unrelated parallel machine scheduling problem with three minimization objectives – makespan, maximum earliness, and maximum tardiness (MET-UPMSP. The last two objectives combined are related to just-in-time (JIT performance of a solution. Three hybrid algorithms are presented to solve the MET-UPMSP: reactive GRASP with path relinking, dual-archived memetic algorithm (DAMA, and SPEA2. In order to improve the solution quality, min-max matching is included in the decoding scheme for each algorithm. An experiment is conducted to evaluate the performance of the three algorithms, using 100 (jobs x 3 (machines and 200 x 5 problem instances with three combinations of two due date factors – tight and range. The numerical results indicate that DAMA performs best and GRASP performs second for most problem instances in three performance metrics: HVR, GD, and Spread. The experimental results also show that incorporating min-max matching into decoding scheme significantly improves the solution quality for the two population-based algorithms. It is worth noting that the solutions produced by DAMA with matching decoding can be used as benchmark to evaluate the performance of other algorithms.
Single-machine scheduling to minimize total completion time and tardiness with two competing agents.
Lee, Wen-Chiung; Shiau, Yau-Ren; Chung, Yu-Hsiang; Ding, Lawson
2014-01-01
We consider a single-machine two-agent problem where the objective is to minimize a weighted combination of the total completion time and the total tardiness of jobs from the first agent given that no tardy jobs are allowed for the second agent. A branch-and-bound algorithm is developed to derive the optimal sequence and two simulated annealing heuristic algorithms are proposed to search for the near-optimal solutions. Computational experiments are also conducted to evaluate the proposed branch-and-bound and simulated annealing algorithms.
Institute of Scientific and Technical Information of China (English)
黄英杰; 姚锡凡
2012-01-01
针对传统的单车间调度优化不能满足分布式车间调度优化的需求,提出一种基于目标级联法和粒子群算法的层次化柔性分布式车间调度优化模型,其中的生产计划层负责零件的分配,车间调度层负责零件加工路线的规划.以2个柔性制造车间组成的调度优化问题为例,验证该调度模型的有效性.研究结果表明:所提出的模型在将加工零件合理地分配到适当车间的同时,实现了零件加工路径的规划,从而为解决柔性分布式车间调度优化问题提供一种有效方法.%Because the traditional scheduling model of single job-shop can not meet the requirements of distributed scheduling systems of multiple job-shops, a planning and scheduling model of multiple job-shops based on analytical target cascading and particle swarm optimization was established, where the planning layer was responsible for distributing jobs to each workshop, and the workshop scheduling layer was responsible for planning job operations in each workshop. Take a two job-shop system as an illustrated example to verify the proposed model. The results show that distributed scheduling problems of multiple flexible-shops can be solved effectively, and jobs can be distributed to the workshops rationally, and meanwhile job schedule in each workshop is realized.
Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model
Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled
2017-05-01
The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.
A hybrid genetic algorithm for flexible job shop scheduling problem%一种求解柔性工作车间调度问题的混合遗传算法
Institute of Scientific and Technical Information of China (English)
宋莉波; 徐学军; 孙延明; 查靓
2010-01-01
针对柔性工作车间调度问题(Flexible job-shop scheduling problem, FJSP),提出了一种基于混合遗传算法的求解方案,在初始种群中引入基于启发式规则生成的优良个体,并使用有效的交叉、变异算子避免不可行个体的产生,同时利用混沌序列的随机性和遍历性特点,在遗传进化的过程中增加基于混沌序列的邻域搜索功能,以提高遗传算法的执行效率.通过仿真实验验证了该算法的可行性和有效性.
Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.
2016-02-01
In the manufacturing industry, several identical parts can be processed in batches, and setup time is needed between two consecutive batches. Since the processing times of batches are not always fixed during a scheduling period due to learning and deterioration effects, this research deals with batch scheduling problems with simultaneous learning and deterioration effects. The objective is to minimize total actual flow time, defined as a time interval between the arrival of all parts at the shop and their common due date. The decision variables are the number of batches, integer batch sizes, and the sequence of the resulting batches. This research proposes a heuristic algorithm based on the Lagrange Relaxation. The effectiveness of the proposed algorithm is determined by comparing the resulting solutions of the algorithm to the respective optimal solution obtained from the enumeration method. Numerical experience results show that the average of difference among the solutions is 0.05%.
Institute of Scientific and Technical Information of China (English)
韩玉艳; 巩敦卫; 张勇
2015-01-01
For the blocking lot-streaming flow shop scheduling problem with stochastic processing time,a method is proposed to transform it into a determinate one using Monte Carlo sampling method.An improved artificial bee colony algorithm is developed, in which a harmony search and local search based on insertion operators are adopted to balance the algorithm’s capability in explo-ration and exploitation.The proposed algorithm is applied to 24 instances of blocking lot-streaming flow shop scheduling prob-lem.The experimental results show that the improved algorithm can generate solutions with high quality and reduce the influence resulting from uncertainties.%针对含有随机加工时间的阻塞批量流水线调度问题，利用蒙特卡洛采样方法，将不确定加工时间的阻塞批量流水线调度问题转化为确定加工时间的阻塞批量调度问题。采用改进的人工蜂群算法，对上述转化后的调度问题进行求解。算法中加入了和声搜索和基于插入操作的局部搜索算子，以改进全局探索和局部开发能力，并将改进的算法应用到阻塞批量调度的24个算例中。仿真实验结果表明，改进的人工蜂群算法能够降低调度中的不确定因素带来的影响，产生高质量的解。
Institute of Scientific and Technical Information of China (English)
王云; 冯毅雄; 谭建荣; 李中凯
2011-01-01
针对柔性作业车间的多目标调度问题,构建了以制造工期、加工成本及提前/拖期惩罚值为目标函数的柔性作业车间调度模型,提出基于密集距离排序的自适应多目标粒子群算法.采用精英策略保留进化过程中的优势个体,基于个体密集距离降序排列进行外部种群的缩减和全局最优值的更新,并引入小概率的变异机制以增强解的多样性和算法的全局寻优能力.最后,将该方法应用于某机械公司的柔性作业车间多目标调度中,仿真结果证明了该方法的有效性和适应性.%To solve flexible job-shop multiobjective scheduling problem, the optimization model was set up. Considering of the makespan, manufacturing cost and earliness/tardiness penalties, a crowding distance sorting based on multiobjective particle swarm optimization algorithm was proposed. With the elitism strategy, dominant individuals were preserved in evolution process. The shrink of the external population and update of the global best were achieved by the individuals' crowding distance sorting in descending order. A small ratio mutation was introduced to enhance the diversity of solutions and the global searching capacity of the algorithm. Finally, the feasibility and validity of the method was proved by the simulation results of a flexible job-shop multiobjective scheduling in a workshop.
Institute of Scientific and Technical Information of China (English)
赵亚玲; 葛茂根; 扈静; 张铭鑫; 张玺
2015-01-01
文章针对单件小批量生产的柔性生产方式，考虑操作人员技能的多样性和对于不同任务技能水平的差异性等特点，根据操作人员对各任务的累计工作时间计算任务人员之间的匹配度，在此基础上建立柔性生产中资源受限下人员调度数学模型；通过启发式算法得到模型的初始解，并运用改进的遗传算法对模型进行求解，得到最优的人员调度方案以实现任务总完成时间最小的优化目标；最后结合具体实例验证了该求解模型的准确性与可行性。%For single piece and small batch production of flexible job‐shop problem ,considering the di‐versity of operator skills and different skill levels for different tasks ,the person‐task matching degree is calculated according to accumulated working time of each operator on each task ,and the mathemati‐cal model of personnel scheduling under resource constraint is constructed for flexible job‐shop prob‐lem .T he initial solution of the model is obtained by the heuristic algorithm ,and the optimal person‐nel scheduling plan is obtained with the minimum duration by using the revised genetic algorithm to solve the model .Finally ,the feasibility and accuracy of the model are verified by real cases .
Application of honey-bee mating optimization algorithm to job-shop scheduling%蜜蜂交配优化算法在车间作业调度中的应用
Institute of Scientific and Technical Information of China (English)
李小霞; 刘峰; 刘建晓
2013-01-01
To solve the Job-shop Scheduling Problem(JSP), a solution method-honey-bee mating optimization algorithm is presented on the basis of the JSP’s description. The method takes a set of job scheduling schemes as the bee swarm, and mini-mizing the processing time as the optimization goal. The optimal scheduling scheme is obtained by simulating the procedure of honey-bee mating. The test is carried out by the JSP test cases on Matlab. The experimental results show that this method can not only solve JSP but also find a better optimal scheduling scheme than the traditional optimization methods.%为了解决车间作业调度问题，在对其进行分析描述的基础上，提出了采用蜜蜂交配优化算法的求解方法。该方法把由多个作业调度方案组成的集合作为蜂群，以最小化加工时间作为算法的优化目标，通过模拟蜂群交配繁衍培养蜂王的优化过程来获得最优作业调度方案。采用车间作业调度测试案例在Matlab平台上进行实验，实验结果表明，该方法不仅能够有效地求解车间作业调度问题，而且能够取得了比传统优化方法更好的优化结果。
Institute of Scientific and Technical Information of China (English)
任传荣; 康丽英
2007-01-01
In this paper, a parallel machine scheduling problem was considered, where the processing time of a job is a simple linear function of its starting time. The objective is to minimize makespan. A fully polynomial time approximation scheme for the problem of scheduling n deteriorating jobs on two identical machines was worked out. Furthermore, the result was generalized to the case of a fixed number of machines.
Off-Line and Dynamic Production Scheduling – A Comparative Case Study
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Bożek Andrzej
2016-03-01
Full Text Available A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.
Institute of Scientific and Technical Information of China (English)
莫建麟; 吴喆
2013-01-01
Aiming at the solving FJSP (Flexible job-shop scheduling problem), a scheduling algorism combined gene and tabu algorism were proposed. Firstly, the FJSP problem model was defined, then the improve gene algorism was used to obtain the solution, the chromosome was coded as double-stranded and the NEH algorism was used to get the initial solution. And the adaptive selection strategy, compound cross strategy and mutation strategy were introduced to protect the optimum chromosome and renew. When the gene algorism got the local optimum solution, the tabu algorism was used to get the global solution. The simulation experiment shows our method in this paper can resolve the FJSP effectively and get the optimal solution, compared with the other methods; the method has the rapid convergence and high solution efficiency.%针对多目标柔性作业车间调度问题(Flexible job-shop scheduling problem,FJSP),提出了一种结合遗传算法和禁忌算法求解FJSP的调度算法.首先,定义了FJSP问题模型,然后提出采用改进的遗传算法对其进行求解,采用双链进行染色体编码和NEH方法获得初始解,并提出了自适应的选择策略、混合交叉策略和复合变异策略以实现个体保优和更新,当遗传算法陷入局部最优解时,采用禁忌算法跳出局部最优,以实现全局最优解的获取.仿真实验证明文中的方法能有效地解决FJSP问题,获得全局最优解,且与其他方法相比,文中方法具有收敛速度快和求解效率高的优势.
加工时间不确定的柔性作业车间鲁棒调度方法%Robust Scheduling on Flexible Job Shop with Uncertain Processing Time
Institute of Scientific and Technical Information of China (English)
汪俊亮; 张洁; 秦威; 银莉; 陈定方
2015-01-01
This paper investigated the flexible job-shop scheduling problem (FJSP)with uncertain processing time in a multi-type and low-volume environment.A minimax regret based robust schedu-ling model was built to minimize the makespan.A novel sequential search rule was put forward to re-duce the calculation amount of the algorithm and a two stage genetic algorithm was designed to figure out the redundant and optimal solutions.Orthogonal test was designed to optimize significant parame-ters,and then,a simulation model was established to evaluate the robustness and obj ective perform-ance of the algorithm.The results show the proposed algorithm has a better performance than genetic algorithm on flexible j ob-shop scheduling problem under uncertain and dynamic environment.%针对中小批量环境下加工时间不确定的柔性作业车间调度问题，采用冗余处理方法构建了以最大完工时间为目标的鲁棒调度模型。为降低算法的搜索规模和提高算法的求解速度，提出了顺序搜索机制，并设计两阶段遗传算法，分阶段获取冗余状态和最优结果。采用某柔性生产线的数据进行正交试验，优化了算法关键参数，并构建了柔性生产线仿真模型，对调度结果的鲁棒性和优化目标性能进行了分析。结果表明，该算法在目标性能和鲁棒性上都显著优于标准遗传算法，能有效处理加工时间不确定的柔性作业车间调度问题。
An Efficient Constructive Heuristic for Permutation Flow Shops to Minimize Total Flowtime
Institute of Scientific and Technical Information of China (English)
LIXiaoping; WUCheng
2005-01-01
In this paper, FFC (Fast fiowtime-computing) is presented for fiowtime computing in flow shops. The CPU-time of an algorithm for flow shops can be reduced considerably by replacing classical flowtime computing with FFC based on the facts that FFC is faster than the classical one and that flowtime computing of schedules/partial schedules is the main computational burden of most algorithms for flow shops. This is illustrated by modifying RZ, one of the three best existing heuristics(FL, WY and RZ) for flowtime minimization, with FFC in which about half of the CPU-time is saved. An efficient constructive heuristic is proposed for permutation flow shops with flowtime minimization, of which the CPU-time is more than that of RZ but much less than those of FL and WY. Our proposal is compared with FL, WYand RZ in terms of ARPD (Average relative percentage deviation), STD (Standard deviation) and BEST (number of best solutions obtained for a given size of problems). Computational results show that the proposed heuristic outperforms WY and RZ, and also outperforms FL when job-machine ratio is small. However, as the ratio increases, the proposal will finally be outperformed by FL but needs far less CPU-time than FL does.
Directory of Open Access Journals (Sweden)
Ahmad Zeraatkar Moghaddam
2012-01-01
Full Text Available This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.
GENETIC ALGORITHM BASED MULTIPLE OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING METHOD%基于遗传算法的多目标柔性车间作业调度方法
Institute of Scientific and Technical Information of China (English)
许秀林; 胡克瑾
2012-01-01
多目标柔性车间作业调度通常将多个目标进行无量纲处理,加权转换成单一目标函数用于解的优化筛选,但权重选择难免存在一定的随意和偏好,影响调度效果.针对这一问题,提出单目标决策下的多目标调度解决方案,从多个目标中选择一个重要的目标作为决策目标,其他目标作为算法搜索的导向目标.其中对遗传算法变异算子进行改造,将随机性变异转换成目标诱导性变异.实例仿真结果表明了算法的有效性和可行性.%Multiple objective flexible job shop scheduling usually handles multiple objects as dimcnsionlcss. i. e. , weighted transforming them into one single object function for solutions optimal filtration. However the selection of weights is inevitably influenced by casualty and preference, so that the scheduling performance is also influenced. To solve this problem, a multiple objective scheduling solution under single objective decision is proposed. It selects one important object from multiple objects as decisive object while the remaining as inductive objects. In the genetic algorithm, the mutation operator is reformed from random variation to induced variation. Simulation results show that the algorithm is effective and feasible.
Directory of Open Access Journals (Sweden)
Mohamad_Bagher Fakhrzad
2012-06-01
Full Text Available In this paper, a non linear mathematical model has been proposed for solving a single machine scheduling problem with a linear earliness and quadratic tardiness cost, where machine idle time and preemptions are allowed. As the model is complex and cannot be solved in polynomial time, it has been assumed to be a NP hard problem, so the known optimal solution methods may not be applicable for its solution. A Genetic Algorithm approach has been developed for solving the model and numerical examples has been presented, which imply that the proposed method is efficient and effective.
Hybrid heuristic algorithm for integrated scheduling in flexible Job Shops%柔性Job Shops集成调度启发式算法
Institute of Scientific and Technical Information of China (English)
周炳海; 赵猛
2016-01-01
为有效解决柔性作业车间(Job Shops)的加工与搬运集成调度问题,以最小化最大完工时间(Makespan)为调度目标,建立非线性规划模型,提出基于贪婪启发式策略的变邻域搜索算法(GRS-RVNS).根据准时(JIT)生产和均衡生产思想构建贪婪启发式策略快速求初始解.利用析取图表示可行解并根据析取图调度的性质定理构建有效的搜索邻域,进而利用随机变邻域搜索算法对初始解进行优化.对提出的算法进行仿真实验分析,结果表明:该算法求解时间短、调度方法有竞争性.
Kaplan, Sezgin; Rabadi, Ghaith
2013-01-01
This article addresses the aerial refuelling scheduling problem (ARSP), where a set of fighter jets (jobs) with certain ready times must be refuelled from tankers (machines) by their due dates; otherwise, they reach a low fuel level (deadline) incurring a high cost. ARSP is an identical parallel machine scheduling problem with release times and due date-to-deadline windows to minimize the total weighted tardiness. A simulated annealing (SA) and metaheuristic for randomized priority search (Meta-RaPS) with the newly introduced composite dispatching rule, apparent piecewise tardiness cost with ready times (APTCR), are applied to the problem. Computational experiments compared the algorithms' solutions to optimal solutions for small problems and to each other for larger problems. To obtain optimal solutions, a mixed integer program with a piecewise weighted tardiness objective function was solved for up to 12 jobs. The results show that Meta-RaPS performs better in terms of average relative error but SA is more efficient.
Institute of Scientific and Technical Information of China (English)
刘婷
2011-01-01
Aiming at the traditional multi-objective genetic algorithm for solving job shop scheduling problem in slow convergence rate and easy to fall into local optimization, a transition point crossover fashion is proposed using multi-objective genetic algorithms. The initial approach of the multi-point crossover operator is to improve convergence speed which gradually reduces in the latter part of the intersection of computing, until cross with two and single-point crossover approach to avoid missing the optimal solution leading to premature convergence. At the same time, the weight will transform an interactive multi-objective problem into single objective problem to reflect the decision maker preferences, while simplifying the solution process. The improved algorithm is applied to a job shop scheduling problem in contrast with no preference for multi-objective optimization Pareto genetic algorithm niche (NPGA) , and the results show the effectiveness of the algorithm.%针对传统多目标遗传算法在求解作业车间调度问题时收敛速度慢和容易陷入局部最优化的不足,提出一种采用变点交叉方式的多目标遗传算法.运算初期采用多点交叉的方式,在于提高收敛速度.在运算后期逐步减少交叉点,直至采用两点交叉、单点交叉的方式,避免丢失最优解导致早熟收敛.同时设计一种交互权重将多目标问题变为单一目标问题,体现决策者偏好,同时简化求解过程.最后将提出的改进算法运用于作业车间调度问题,与无偏好多目标优化的小生境Pareto遗传算法(NPGA)进行了对比,结果显示了该算法的有效性.
Modified simulated annealing algorithm for flexible job-shop scheduling problem%柔性作业车间调度优化的改进模拟退火算法
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李俊; 刘志雄; 张煜; 贺晶晶
2015-01-01
A modified simulated annealing algorithm was put forward to resolve the flexible job‐shop scheduling problem ,which used two kinds of individual encoding method respectively based on parti‐cle position rounding and roulette probability assignment in particle swarm algorithm .Three different local search methods were employed to constitute the neighborhood structure .The computational re‐sults show that the modified simulated annealing algorithm is more effective than particle swarm algo‐rithm ,hybrid particle swarm algorithm and simulated annealing algorithm in resolving the flexible job‐shop scheduling problem .Compared with the position rounding encoding method ,the roulette‐probability‐assignment‐based encoding method can render the algorithm more effective ,and the local search method based on crossing‐over operation is better than the other two search methods in impro‐ving the solving performance of the algorithm .%针对柔性作业车间调度问题，提出一种改进模拟退火算法来进行求解。该算法引入粒子群算法中的基于位置取整和基于轮盘赌两种个体编码方法，并采用3种不同的局部搜索方法来构造个体的邻域结构。算例计算表明，改进模拟退火算法在求解柔性作业车间调度问题时，比粒子群算法、混合粒子群算法以及模拟退火算法具有更好的求解性能，其中采用轮盘赌编码时，算法的求解性能要优于采用位置取整时的求解性能，且基于互换的局部搜索方法要优于其他两种局部搜索方法，能更有效地改善算法的求解性能。
Institute of Scientific and Technical Information of China (English)
刘丽琴; 张学良; 谢黎明; 温淑花
2013-01-01
A hybrid particle swarm optimization algorithm with Pareto archives set was proposed for solving the multi-objective flexible job-shop scheduling problem (FJSP). The multi-objective FJSP optimization model was developed, including the total completion time, the total workload and the maximal workload. To improve the quality of the initial population and accelerate the speed of the algorithm's convergence, a new initialization method was proposed, which combined with global search, local search and random generation. Applying the improved quick sorting to reduce the time for computation, and a speed-up Pareto set updating algorithm based on dynamic crowding distance was developed to ensure sufficient diversity amongst the solutions of the non-dominated fronts. A reversion tactics was introduced to enhance the diversity of the solutions. Three typical simulation results were provided to demonstrate the feasibility and effectiveness of the proposed method.%针对多目标柔性作业车间调度问题(Flexible Job-shop Scheduling Problem,FJSP)的复杂性,建立了以总完工时间、所有机器总负载及最大机器负载为目标函数的多目标调度模型,提出了一种带有Pareto档案集的混合粒子群优化算法.该算法首先通过全局搜索、局部搜索和随机产生相结合的初始化方法产生高质量的初始种群,利用改进的快速排序法构造Pareto档案集,并给出了一种快速更新Pareto档案集的算法.既保持了种群的多样性,避免了算法陷σ局部最优,又有效地提高了算法的收敛速度；算法中还引σ逆转策略来进一步增加解的多样性.通过3个经典算例的实验仿真,验证了该算法的可行性和有效性.
Shy, Oz
2013-01-01
The terms "window shopping" and "showrooming" refer to the activity in which potential buyers visit a brick-and-mortar store to examine a product but end up either not buying it or buying the product from an online retailer. This paper analyzes potential buyers who differ in their preference for after-sale service that is not offered by online retailers. For some buyers, making a trip to the brick-and-mortar store is costly; however, going to the store to examine the product has the advantage...
SHY, Oz
2013-01-01
The terms "window shopping" and "showrooming" refer to the activity in which potential buyers visit a brick-and-mortar store to examine a product but end up either not buying it or buying the product from an online retailer. This paper analyzes potential buyers who differ in their preference for after-sale service that is not offered by online retailers. For some buyers, making a trip to the brick-and-mortar store is costly; however, going to the store to examine the product has the advantage...
Directory of Open Access Journals (Sweden)
Huixin Tian
2016-01-01
Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.
Institute of Scientific and Technical Information of China (English)
张国辉; 党世杰
2016-01-01
Low carbon production mode has become the current accepted production mode, it is also the in-evitable requirement of sustainable development. Low carbon flexible job shop scheduling model is built to meet the target of minimum makespan and producing carbon emissions. An improved genetic algorithm is proposed to solve the workshop production mode with low carbon requirements, in the process of solving, the initial solution and genetic operator are improved to enhance the algorithm convergence speed. Finally, the experimental results show that the proposed improved genetic algorithm is feasible in solving low carbon production scheduling.%低碳生产方式已成为当前各国所认可的生产方式，是可持续发展的必然要求。从满足最大完工时间最小和生产碳排放量最小角度出发，构建低碳车间调度模型。使用改进的遗传算法对有低碳需求的车间生产方式进行求解，在求解过程中对初始解生成机制和遗传算子进行改进，提高算法收敛速度。实验结果证明提出的改进遗传算法在求解车间低碳生产调度中是可行的。
作业车间调度问题的布谷鸟搜索算法求解%Solving job-shop scheduling problem by cuckoo search algorithm
Institute of Scientific and Technical Information of China (English)
姚远远; 叶春明
2015-01-01
布谷鸟搜索算法是一种新型元启发式优化算法，该算法受到自然界中布谷鸟的巢寄生行为启发而提出。首先分析了布谷鸟搜索算法的仿生原理和数学描述，采用基于工序的编码方式对最小化最大完工时间的作业车间调度问题进行布谷鸟搜索算法求解。通过典型算例进行仿真实验，测试结果表明布谷鸟搜索算法求解作业车间调度问题的可行性和有效性，优于萤火虫算法和基本粒子群算法，是解决生产调度问题的一种有效方法。%Cuckoo Search(CS)is one of the latest nature-inspired metaheuristic algorithm, which is based on the obli-gate brood parasitism behavior of some cuckoo species. Firstly, this paper analyzes the bionic principle of CS and its mathe-matical description. The code rule based on sequence is adopted to solve job-shop scheduling problem, whose objective is to minimize the makespan. Then the paper validates the CS algorithm against some typical benchmark instances and com-pares its performance with those of firefly algorithm and basic particle swarm optimization. Simulations and results show that CS is very effective, superior and promising in solving production scheduling problem.
Institute of Scientific and Technical Information of China (English)
周超; 胡燕海; 李建辉
2015-01-01
针对柔性作业车间柔性分批调度问题的复杂性，采用遗传算法进行求解，在引入柔性分批方法后，并提出了染色体的两级编码方法，设计了2种交叉和变异操作方法，以防止操作中非法解的产生，提高求解效率。该算法不仅解决批量分批，而且也解决子批排序和选择加工路线的问题。对比整批调度和柔性分批调度的 Makespan 后，仿真结果表明，柔性分批调度可缩短生产周期，验证了采用新算法的可行性和有效性。%In this paper, genetic algorithm is employed to solve the complex problems in flexible job-shop scheduling and size-lot splitting. A two-stage encoding method of chromosomes is presented and two kinds of crossover and mutation methods are designed to prevent the incorrect solutions in the manipulation. The algorithm not only solves the problem with lot splitting, but also the problem of sorting and selection of flexible size-lot splitting processing route. Based on the Makespan comparison of entire batch scheduling and flexible size-lot splitting, it is found that the production cycle with flexible size-lot splitting can be shortened using the proposed method, with which the feasibility and effectiveness of the proposed method are hence verified.
Institute of Scientific and Technical Information of China (English)
张志鹏; 黄明
2015-01-01
为解决混合流水车间调度问题（HFSP），基于多目标遗传算法和粒子群算法的优点，提出一种多目标混合算法。该算法引入一种扩展的基于工序的编码，将两种算法产生的最优解分别作为彼此的初始因子，增强了遗传算法的进化速度，有效避免了粒子群算法陷入局部最优，并实现了不同加工路线的生产车间的灵活性调度。最后通过实例的数值仿真验证了算法的有效性。%Based on the advantages of multi-objective genetic algorithm and particle swarm optimisation,we proposed a multi-objective hy-brid algorithm for solving hybrid flow-shop scheduling problem (HFSP).It introduces an extended process-based encoding,takes the optimal solutions of these two algorithms as the initial factor for each other,and speeds up the evolution of genetic algorithm as well as avoids PSO falling into local optimum,thus realises the flexible scheduling of production workshops with different processing routes.Finally,through nu-merical simulation of example we verified the effectiveness of the algorithm.
一种基于混合遗传算法的车间生产调度的研究%Study on job-shop scheduling based on hybrid genetic algorithm
Institute of Scientific and Technical Information of China (English)
刘红军; 赵帅
2011-01-01
车间生产调度问题(Job-shop scheduling problem,JSSP)属于NP完全问题,现在多使用现代优化算法来解决此类问题.本文将模拟退火算法、禁忌搜索算法的思想融入到遗传算法中,提出了模拟退火-交叉机制和禁忌搜索-变异机制,形成了一种适用于解决车间调度方面问题的新的混合遗传算法.三种算法取长补短,使得遗传算法局部搜索能力差和易早熟的缺点得以改善.同时运用这种混合遗传算法对经典车间调度问题进行了仿真.
Institute of Scientific and Technical Information of China (English)
柳寅; 马良; 黄钰
2013-01-01
针对传统人工蜂群算法早熟收敛问题,基于模糊化处理和蜂群寻优的特点,提出一种模糊人工蜂群算法.将模糊输入输出机制引入到算法中来保持蜜源访问概率的动态更新.根据算法计算过程中的不同阶段对蜜源访问概率有效调整,避免算法陷入局部极值.通过对置换流水车间调度问题的仿真实验和与其他算法的比较,表明本算法可行有效,有良好的鲁棒性.%Aiming at the premature convergence problem in traditional artificial bees colony algorithm,fuzzy artificial bees colony algorithm is proposed,which is based on the principles of fuzzy processing and bees colony behavior.Fuzzy inputs and fuzzy outputs are introduced into the algorithm to maintain dynamic updates of the nectar access probability.According to effective adjustment on nectar access probability during the different stages of algorithm calculation,the algorithm avoids local optima.Simulated tests of permutation flow shop scheduling problem and comparisons with other algorithms show the algorithm is feasible and effective and the algorithm has strong global optimization ability.
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2016-06-01
Full Text Available In the competitive business world, applying a reliable and powerful mechanism to support decision makers in manufacturing companies and helping them save time by considering varieties of effective factors is an inevitable issue. Advanced Available-to-Promise is a perfect tool to design and perform such a mechanism. In this study, this mechanism which is compatible with the Make-to-Forecast production systems is presented. The ability to distinguish between batch mode and real-time mode advanced available-to-promise is one of the unique superiorities of the proposed model. We also try to strengthen this mechanism by integrating the inventory allocation and job shop scheduling by considering due dates and weighted earliness/tardiness cost that leads to more precise decisions. A mixed integer programming (MIP model and a heuristic algorithm according to its disability to solve large size problems are presented. The designed experiments and the obtained results have proved the efficiency of the proposed heuristic method.
Problem of Flexible Job-Shop Scheduling Based on Improved Genetic Algorithm%基于改进遗传算法的柔性作业车间调度问题
Institute of Scientific and Technical Information of China (English)
蒋良宵
2014-01-01
针对柔性作业车间调度问题的特点，以最大完工时间作为性能指标，提出一种基于改进遗传算法的柔性作业车间调度方法。采用一种新的初始化方法来提高种群初始解的质量，加快遗传算法的收敛速度，并通过实例测试验证了该算法的可行性。%Based on the analysis of the traits of flexible job-shop scheduling problem, proposes an improved genetic algorithm to minimize the makespan. Adopts a new initialization method to improve the quality of the initial population and accelerate the speed of the algorithm's convergence. Consides the characteristic of the problem, reasonable chromosome encoding, gives crossover and mutation operator, and proves the effectiveness of the improved algorithm is by testing.