Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

Science.gov (United States)

Santosa, B.; Siswanto, N.; Fiqihesa

2018-04-01

This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

A bi-criteria M-machine SDST flow shop scheduling using modified ...

African Journals Online (AJOL)

user

In the present work, a modified heuristic based genetic algorithm ..... Due to the large search space in flow shop scheduling, it is expected that random generation ..... ergonomics, anthropometry, inventory management and quality control etc.

Two-agent scheduling in open shops subject to machine availability and eligibility constraints

Directory of Open Access Journals (Sweden)

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. 

Preemptive scheduling in a two-stage multiprocessor flow shop is NP-hard

NARCIS (Netherlands)

Hoogeveen, J.A.; Lenstra, J.K.; Veltman, B.

1996-01-01

In 1954, Johnson gave an efficient algorithm for minimizing makespan in a two-machine flow shop; there is no advantage to preemption in this case. McNaughton's wrap-around rule of 1959 finds a shortest preemptive schedule on identical parallel machines in linear time. A similarly efficient algorithm

No-Wait Job Shop Scheduling, a Constraint Propagation Approach

NARCIS (Netherlands)

Lennartz, P.M.

2006-01-01

Multi-machine scheduling problems have earned themselves a reputation of intractability. In this thesis we try to solve a special kind of these problems, the so-called no-wait job shop problems. In an instance of this problem-class we are given a number of operations that are to be executed on a

The Effects of Machine Load Sitnations on Performance of Job Shop and Group Scheduling

OpenAIRE

Torkul, O.

2018-01-01

Perfonnance of job shop and group scheduling ndermulti­natch work input environment was exarnined against two nachine load (light and high load) situations. n order to conduct the analysis, a deterministic computer ;im ulation program was written and used. A job shop {JS) model is applied to the shop floor area and :ompared with a simulation of a similar proposal except hat group technology (GT) model was used in the shop loor area instead. )etailed analysis of the results from applying diffe...

The Effects of Machine Load Sitnations on Performance of Job Shop and Group Scheduling

OpenAIRE

O.TORKUL TORKUL

1998-01-01

Perfonnance of job shop and group scheduling ndermulti­natch work input environment was exarnined against two nachine load (light and high load) situations. n order to conduct the analysis, a deterministic computer ;im ulation program was written and used. A job shop {JS) model is applied to the shop floor area and :ompared with a simulation of a similar proposal except hat group technology (GT) model was used in the shop loor area instead. )etailed analysis of the results from applying diffe...

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.

Batch Scheduling for Hybrid Assembly Differentiation Flow Shop to Minimize Total Actual Flow Time

Science.gov (United States)

Maulidya, R.; Suprayogi; Wangsaputra, R.; Halim, A. H.

2018-03-01

A hybrid assembly differentiation flow shop is a three-stage flow shop consisting of Machining, Assembly and Differentiation Stages and producing different types of products. In the machining stage, parts are processed in batches on different (unrelated) machines. In the assembly stage, each part of the different parts is assembled into an assembly product. Finally, the assembled products will further be processed into different types of final products in the differentiation stage. In this paper, we develop a batch scheduling model for a hybrid assembly differentiation flow shop to minimize the total actual flow time defined as the total times part spent in the shop floor from the arrival times until its due date. We also proposed a heuristic algorithm for solving the problems. The proposed algorithm is tested using a set of hypothetic data. The solution shows that the algorithm can solve the problems effectively.

A review of scheduling problem and resolution methods in flexible flow shop

Directory of Open Access Journals (Sweden)

Tian-Soon Lee

2019-01-01

Full Text Available The Flexible flow shop (FFS is defined as a multi-stage flow shops with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. This review paper gives a comprehensive exploration review on the FFS scheduling problem and guides the reader by considering and understanding different environmental assumptions, system constraints and objective functions for future research works. The published papers are classified into two categories. First is the FFS system characteristics and constraints including the problem differences and limitation defined by different studies. Second, the scheduling performances evaluation are elaborated and categorized into time, job and multi related objectives. In addition, the resolution approaches that have been used to solve FFS scheduling problems are discussed. This paper gives a comprehensive guide for the reader with respect to future research work on the FFS scheduling problem.

Hybrid job shop scheduling

NARCIS (Netherlands)

Schutten, Johannes M.J.

1995-01-01

We consider the problem of scheduling jobs in a hybrid job shop. We use the term 'hybrid' to indicate that we consider a lot of extensions of the classic job shop, such as transportation times, multiple resources, and setup times. The Shifting Bottleneck procedure can be generalized to deal with

A hybrid job-shop scheduling system

Science.gov (United States)

Hellingrath, Bernd; Robbach, Peter; Bayat-Sarmadi, Fahid; Marx, Andreas

1992-01-01

The intention of the scheduling system developed at the Fraunhofer-Institute for Material Flow and Logistics is the support of a scheduler working in a job-shop. Due to the existing requirements for a job-shop scheduling system the usage of flexible knowledge representation and processing techniques is necessary. Within this system the attempt was made to combine the advantages of symbolic AI-techniques with those of neural networks.

Flow shop scheduling with heterogeneous workers

OpenAIRE

Benavides, Alexander J.; Ritt, Marcus; Miralles Insa, Cristóbal Javier

2014-01-01

We propose an extension to the flow shop scheduling problem named Heterogeneous Flow Shop Scheduling Problem (Het-FSSP), where two simultaneous issues have to be resolved: finding the best worker assignment to the workstations, and solving the corresponding scheduling problem. This problem is motivated by Sheltered Work centers for Disabled, whose main objective is the labor integration of persons with disabilities, an important aim not only for these centers but for any company d...

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.

Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

Science.gov (United States)

Buddala, Raviteja; Mahapatra, Siba Sankar

2017-11-01

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

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.

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.

Lower bounds for the head-body-tail problem on parallel machines: a computational study for the multiprocessor flow shop

NARCIS (Netherlands)

A. Vandevelde; J.A. Hoogeveen; C.A.J. Hurkens (Cor); J.K. Lenstra (Jan Karel)

2005-01-01

htmlabstractThe multiprocessor flow-shop is the generalization of the flow-shop in which each machine is replaced by a set of identical machines. As finding a minimum-length schedule is NP-hard, we set out to find good lower and upper bounds. The lower bounds are based on relaxation of the

Lower bounds for the head-body-tail problem on parallel machines : a computational study of the multiprocessor flow shop

NARCIS (Netherlands)

Vandevelde, A.; Hoogeveen, J.A.; Hurkens, C.A.J.; Lenstra, J.K.

2005-01-01

The multiprocessor flow-shop is the generalization of the flow-shop in which each machine is replaced by a set of identical machines. As finding a minimum-length schedule is NP-hard, we set out to find good lower and upper bounds. The lower bounds are based on relaxation of the capacities of all

Flexible Job Shop Scheduling Problem Using an Improved Ant Colony Optimization

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Lei Wang

2017-01-01

Full Text Available As an extension of the classical job shop scheduling problem, the flexible job shop scheduling problem (FJSP plays an important role in real production systems. In FJSP, an operation is allowed to be processed on more than one alternative machine. It has been proven to be a strongly NP-hard problem. Ant colony optimization (ACO has been proven to be an efficient approach for dealing with FJSP. However, the basic ACO has two main disadvantages including low computational efficiency and local optimum. In order to overcome these two disadvantages, an improved ant colony optimization (IACO is proposed to optimize the makespan for FJSP. The following aspects are done on our improved ant colony optimization algorithm: select machine rule problems, initialize uniform distributed mechanism for ants, change pheromone’s guiding mechanism, select node method, and update pheromone’s mechanism. An actual production instance and two sets of well-known benchmark instances are tested and comparisons with some other approaches verify the effectiveness of the proposed IACO. The results reveal that our proposed IACO can provide better solution in a reasonable computational time.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

Science.gov (United States)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

Energy Technology Data Exchange (ETDEWEB)

Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali

2017-07-01

Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

International Nuclear Information System (INIS)

Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali

2017-01-01

Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

Directory of Open Access Journals (Sweden)

Chandramouli Anandaraman

2011-10-01

Full Text Available Job Shop Scheduling Problem (JSSP and Flow Shop Scheduling Problem (FSSP are strong NP-complete combinatorial optimization problems among class of typical production scheduling problems. An improved Sheep Flock Heredity Algorithm (ISFHA is proposed in this paper to find a schedule of operations that can minimize makespan. In ISFHA, the pairwise mutation operation is replaced by a single point mutation process with a probabilistic property which guarantees the feasibility of the solutions in the local search domain. A Robust-Replace (R-R heuristic is introduced in place of chromosomal crossover to enhance the global search and to improve the convergence. The R-R heuristic is found to enhance the exploring potential of the algorithm and enrich the diversity of neighborhoods. Experimental results reveal the effectiveness of the proposed algorithm, whose optimization performance is markedly superior to that of genetic algorithms and is comparable to the best results reported in the literature.

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.

Algoritmo genético aplicado a la programación en talleres de maquinado//Genetic algorithm applied to scheduling in machine shops

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

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.

Machine Shop Fundamentals: Part I.

Science.gov (United States)

Kelly, Michael G.; And Others

These instructional materials were developed and designed for secondary and adult limited English proficient students enrolled in machine tool technology courses. Part 1 includes 24 lessons covering introduction, safety and shop rules, basic machine tools, basic machine operations, measurement, basic blueprint reading, layout, and bench tools.…

Machine Shop Grinding Machines.

Science.gov (United States)

Dunn, James

This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

Efficient bounding schemes for the two-center hybrid flow shop scheduling problem with removal times.

Science.gov (United States)

Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.

Performance comparison of some evolutionary algorithms on job shop scheduling problems

Science.gov (United States)

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.

Job shop scheduling with makespan objective: A heuristic approach

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Mohsen Ziaee

2014-04-01

Full Text Available Job shop has been considered as one of the most challenging scheduling problems and there are literally tremendous efforts on reducing the complexity of solution procedure for solving job shop problem. This paper presents a heuristic method to minimize makespan for different jobs in a job shop scheduling. The proposed model is based on a constructive procedure to obtain good quality schedules, very quickly. The performance of the proposed model of this paper is examined on standard benchmarks from the literature in order to evaluate its performance. Computational results show that, despite its simplicity, the proposed heuristic is computationally efficient and practical approach for the problem.

Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

Science.gov (United States)

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.

Flexible job shop scheduling problem in manufacturing

OpenAIRE

Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo

2013-01-01

This paper addresses a real assembly cell: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France. This system can be viewed as a Flexible Job Shop, leading to the formulation of a Flexible Job Shop Scheduling Problem (FJSSP).

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

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Laxmi A. Bewoor

2017-10-01

Full Text Available The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.

Time complexity and linear-time approximation of the ancient two-machine flow shop

NARCIS (Netherlands)

Rote, G.; Woeginger, G.J.

1998-01-01

We consider the scheduling problems F2¿Cmax and F2|no-wait|Cmax, i.e. makespan minimization in a two-machine flow shop, with and without no wait in process. For both problems solution algorithms based on sorting with O(n log n) running time are known, where n denotes the number of jobs. [1, 2]. We

Modeling the Hybrid Flow Shop Scheduling Problem Followed by an Assembly Stage Considering Aging Effects and Preventive Maintenance Activities

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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.

An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

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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.

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...

Near-Optimal Heuristics for Just-In-Time Jobs Maximization in Flow Shop Scheduling

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Helio Yochihiro Fuchigami

2018-04-01

Full Text Available The number of just-in-time jobs maximization in a permutation flow shop scheduling problem is considered. A mixed integer linear programming model to represent the problem as well as solution approaches based on enumeration and constructive heuristics were proposed and computationally implemented. Instances with up to 10 jobs and five machines are solved by the mathematical model in an acceptable running time (3.3 min on average while the enumeration method consumes, on average, 1.5 s. The 10 constructive heuristics proposed show they are practical especially for large-scale instances (up to 100 jobs and 20 machines, with very good-quality results and efficient running times. The best two heuristics obtain near-optimal solutions, with only 0.6% and 0.8% average relative deviations. They prove to be better than adaptations of the NEH heuristic (well-known for providing very good solutions for makespan minimization in flow shop for the considered problem.

Skipping Strategy (SS) for Initial Population of Job-Shop Scheduling Problem

Science.gov (United States)

Abdolrazzagh-Nezhad, M.; Nababan, E. B.; Sarim, H. M.

2018-03-01

Initial population in job-shop scheduling problem (JSSP) is an essential step to obtain near optimal solution. Techniques used to solve JSSP are computationally demanding. Skipping strategy (SS) is employed to acquire initial population after sequence of job on machine and sequence of operations (expressed in Plates-jobs and mPlates-jobs) are determined. The proposed technique is applied to benchmark datasets and the results are compared to that of other initialization techniques. It is shown that the initial population obtained from the SS approach could generate optimal solution.

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.

A Hybrid Metaheuristic Approach for Minimizing the Total Flow Time in A Flow Shop Sequence Dependent Group Scheduling Problem

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Antonio Costa

2014-07-01

Full Text Available Production processes in Cellular Manufacturing Systems (CMS often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs and Biased Random Sampling (BRS search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.

Machine shop basics

CERN Document Server

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

Metalworking Lathe; Machine Shop Work--Intermediate: 9555.03.

Science.gov (United States)

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor to plan systematically and to present meaningful lessons to provide the training needed by the machine shop student. This is the third course of instruction in a series of machine shop work courses. The six blocks of instruction contained in this outline are designed to…

An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem

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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.

Job shop scheduling by local search

NARCIS (Netherlands)

Aarts, E.H.L.; Lenstra, J.K.; Laarhoven, van P.J.M.; Ulder, N.L.J.

1992-01-01

We present a computational performance analysis of local search algorithms for job shop scheduling. The algorithms under investigation are iterative improvement, simulated annealing, threshold accepting and genetic local search. Our study shows that simulated annealing performs best in the sense

Relative performance of priority rules for hybrid flow shop scheduling with setup times

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Helio Yochihiro Fuchigami

2015-12-01

Full Text Available This paper focuses the hybrid flow shop scheduling problem with explicit and sequence-independent setup times. This production environment is a multistage system with unidirectional flow of jobs, wherein each stage may contain multiple machines available for processing. The optimized measure was the total time to complete the schedule (makespan. The aim was to propose new priority rules to support the schedule and to evaluate their relative performance at the production system considered by the percentage of success, relative deviation, standard deviation of relative deviation, and average CPU time. Computational experiments have indicated that the rules using ascending order of the sum of processing and setup times of the first stage (SPT1 and SPT1_ERD performed better, reaching together more than 56% of success.

Job shop scheduling by local search

NARCIS (Netherlands)

Vaessens, R.J.M.; Aarts, E.H.L.; Lenstra, J.K.

1994-01-01

We survey solution methods for the job shop scheduling problem with an emphasis on local search. We discuss both cleterministic and randomized local search methods as well as the applied neighborhoods. We compare the computational performance of the various methods in terms of their effectiveness

A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling

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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.

A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling.

Science.gov (United States)

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.

FLOWSHOP SCHEDULING USING A NETWORK APPROACH ...

African Journals Online (AJOL)

eobe

time when the last job completes on the last machine. The objective ... more jobs in a permutation flow shop scheduling problem ... processing time of a job on a machine is zero, it ..... hybrid flow shops with sequence dependent setup times ...

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.

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.

Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

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Yuzhen Yang

2014-01-01

Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm

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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.

Evaluating the performance of constructive heuristics for the blocking flow shop scheduling problem with setup times

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Mauricio Iwama Takano

2019-01-01

Full Text Available This paper addresses the minimization of makespan for the permutation flow shop scheduling problem with blocking and sequence and machine dependent setup times, a problem not yet studied in previous studies. The 14 best known heuristics for the permutation flow shop problem with blocking and no setup times are pre-sented and then adapted to the problem in two different ways; resulting in 28 different heuristics. The heuristics are then compared using the Taillard database. As there is no other work that addresses the problem with blocking and sequence and ma-chine dependent setup times, a database for the setup times was created. The setup time value was uniformly distributed between 1% and 10%, 50%, 100% and 125% of the processing time value. Computational tests are then presented for each of the 28 heuristics, comparing the mean relative deviation of the makespan, the computational time and the percentage of successes of each method. Results show that the heuristics were capable of providing interesting results.

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.

A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

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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.

Preventive maintenance optimization for a multi-component system under changing job shop schedule

International Nuclear Information System (INIS)

Zhou Xiaojun; Lu Zhiqiang; Xi Lifeng

2012-01-01

Variability and small lot size is a common feature for many discrete manufacturing processes designed to meet a wide array of customer needs. Because of this, job shop schedule often has to be continuously updated in reaction to changes in production plan. Generally, the aim of preventive maintenance is to ensure production effectiveness and therefore the preventive maintenance models must have the ability to be adaptive to changes in job shop schedule. In this paper, a dynamic opportunistic preventive maintenance model is developed for a multi-component system with considering changes in job shop schedule. Whenever a job is completed, preventive maintenance opportunities arise for all the components in the system. An optimal maintenance practice is dynamically determined by maximizing the short-term cumulative opportunistic maintenance cost savings for the system. The numerical example shows that the scheme obtained by the proposed model can effectively address the preventive maintenance scheduling problem caused by the changes in job shop schedule and is more efficient than the ones based on two other commonly used preventive maintenance models.

Genetic algorithm and neural network hybrid approach for job-shop scheduling

OpenAIRE

Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

1998-01-01

Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

A new genetic algorithm for flexible job-shop scheduling problems

International Nuclear Information System (INIS)

Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia

2015-01-01

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.

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.

Factors Affecting the Behavior of Engineering Students toward Safety Practices in the Machine Shop

Directory of Open Access Journals (Sweden)

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.

Research and Applications of Shop Scheduling Based on Genetic Algorithms

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Hang ZHAO

Full Text Available ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search process,aiming at mixed flow shop scheduling problem, an improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual, and the effectiveness of the algorithm is validated. Experimental results show that the improved algorithm can well avoid the emergency of local minimum and is rapid in convergence.

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

Science.gov (United States)

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.

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

Science.gov (United States)

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

Science.gov (United States)

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Flow-shop scheduling problem under uncertainties: Review and trends

OpenAIRE

Eliana María González-Neira; Jairo R. Montoya-Torres; David Barrera

2017-01-01

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 co...

Flow-shop scheduling problem under uncertainties: Review and trends

Directory of Open Access Journals (Sweden)

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.

An Improved Version of Discrete Particle Swarm Optimization for Flexible Job Shop Scheduling Problem with Fuzzy Processing Time

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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.

A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan

International Nuclear Information System (INIS)

Lian Zhigang; Gu Xingsheng; Jiao Bin

2008-01-01

It is well known that the flow-shop scheduling problem (FSSP) is a branch of production scheduling and is NP-hard. Now, many different approaches have been applied for permutation flow-shop scheduling to minimize makespan, but current algorithms even for moderate size problems cannot be solved to guarantee optimality. Some literatures searching PSO for continuous optimization problems are reported, but papers searching PSO for discrete scheduling problems are few. In this paper, according to the discrete characteristic of FSSP, a novel particle swarm optimization (NPSO) algorithm is presented and successfully applied to permutation flow-shop scheduling to minimize makespan. Computation experiments of seven representative instances (Taillard) based on practical data were made, and comparing the NPSO with standard GA, we obtain that the NPSO is clearly more efficacious than standard GA for FSSP to minimize makespan

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.

Scheduling by positional completion times: analysis of a two-stage flow shop problem with a batching machine

NARCIS (Netherlands)

Hoogeveen, J.A.; Velde, van de S.L.

1998-01-01

We consider a scheduling problem introduced by Ahmadi et al., Batching and scheduling jobs on batch and discrete processors, Operation Research 40 (1992) 750–763, in which each job has to be prepared before it can be processed. The preparation is performed by a batching machine; it can prepare at

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

OpenAIRE

Amjad, Muhammad Kamal; Butt, Shahid Ikramullah; Kousar, Rubeena; Ahmad, Riaz; Agha, Mujtaba Hassan; Faping, Zhang; Anjum, Naveed; Asgher, Umer

2018-01-01

Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in...

Machine Shop Suggested Job and Task Sheets. Part II. 21 Advanced Jobs.

Science.gov (United States)

Texas A and M Univ., College Station. Vocational Instructional Services.

This volume consists of advanced job and task sheets adaptable for use in the regular vocational industrial education programs for the training of machinists and machine shop operators. Twenty-one advanced machine shop job sheets are included. Some or all of this material is provided for each job: an introductory sheet with aim, checking…

Machine Shop Suggested Job and Task Sheets. Part I. 25 Elementary Jobs.

Science.gov (United States)

Texas A and M Univ., College Station. Vocational Instructional Services.

This volume consists of elementary job and task sheets adaptable for use in the regular vocational industrial education programs for the training of machinists and machine shop operators. Twenty-five simple machine shop job sheets are included. Some or all of this material is provided for each job sheet: an introductory sheet with aim, checking…

Nonstrict vector simulation in multi-operation scheduling

NARCIS (Netherlands)

Sevastianov, S.V.

1995-01-01

We consider several multi??operation scheduling problems with m machines and n jobs??, including fl??ow shop??, open shop,?? assembly line,?? and a few special cases of job shop with the makespan criterion. It is demonstrated that the problems in question can be effi??ciently solved by approximation

Abrasives and Grinding Machines; Machine Shop Work--Advanced: 9557.02.

Science.gov (United States)

Dade County Public Schools, Miami, FL.

The course outline has been prepared as a guide to assist the instructor in systematically planning and presenting a variety of meaningful lessons to facilitate the necessary training for the machine shop student. The material contained in the outline is designed to enable the student to learn the manipulative skills and related knowledge…

Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

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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.

The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

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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.

A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing

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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.

Machine Shop I. Learning Activity Packets (LAPs). Section A--Orientation.

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Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains two learning activity packets (LAPs) for the "orientation and safety" instructional area of a Machine Shop I course. The two LAPs cover the following topics: orientation and general shop safety. Each LAP contains a cover sheet that describes its purpose, an introduction, and the tasks included in the LAP; learning…

Comparison of Firefly algorithm and Artificial Immune System algorithm for lot streaming in -machine flow shop scheduling

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G. Vijay Chakaravarthy

2012-11-01

Full Text Available Lot streaming is a technique used to split the processing of lots into several sublots (transfer batches to allow the overlapping of operations in a multistage manufacturing systems thereby shortening the production time (makespan. The objective of this paper is to minimize the makespan and total flow time of -job, -machine lot streaming problem in a flow shop with equal and variable size sublots and also to determine the optimal sublot size. In recent times researchers are concentrating and applying intelligent heuristics to solve flow shop problems with lot streaming. In this research, Firefly Algorithm (FA and Artificial Immune System (AIS algorithms are used to solve the problem. The results obtained by the proposed algorithms are also compared with the performance of other worked out traditional heuristics. The computational results shows that the identified algorithms are more efficient, effective and better than the algorithms already tested for this problem.

Machine Shop I. Learning Activity Packets (LAPs). Section D--Power Saws and Drilling Machines.

Science.gov (United States)

Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains two learning activity packets (LAPs) for the "power saws and drilling machines" instructional area of a Machine Shop I course. The two LAPs cover the following topics: power saws and drill press. Each LAP contains a cover sheet that describes its purpose, an introduction, and the tasks included in the LAP; learning…

A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

Science.gov (United States)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

Sequencing for Batch Production in a Group Flowline Machine Shop ...

African Journals Online (AJOL)

The purpose of the paper is to develop a useful technique for sequencing batches of components through machine shops arranged under the group flowline production system. The approach is to apply a modified version of Petrov's group flowline technique for machining components which follow a unidirectional route.

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

Science.gov (United States)

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.

A neural network approach to job-shop scheduling.

Science.gov (United States)

Zhou, D N; Cherkassky, V; Baldwin, T R; Olson, D E

1991-01-01

A novel analog computational network is presented for solving NP-complete constraint satisfaction problems, i.e. job-shop scheduling. In contrast to most neural approaches to combinatorial optimization based on quadratic energy cost function, the authors propose to use linear cost functions. As a result, the network complexity (number of neurons and the number of resistive interconnections) grows only linearly with problem size, and large-scale implementations become possible. The proposed approach is related to the linear programming network described by D.W. Tank and J.J. Hopfield (1985), which also uses a linear cost function for a simple optimization problem. It is shown how to map a difficult constraint-satisfaction problem onto a simple neural net in which the number of neural processors equals the number of subjobs (operations) and the number of interconnections grows linearly with the total number of operations. Simulations show that the authors' approach produces better solutions than existing neural approaches to job-shop scheduling, i.e. the traveling salesman problem-type Hopfield approach and integer linear programming approach of J.P.S. Foo and Y. Takefuji (1988), in terms of the quality of the solution and the network complexity.

PERBANDINGAN KINERJA ALGORITMA GENETIKA DAN ALGORITMA HEURISTIK RAJENDRAN UNTUK PENJADUALAN PRODUKSI JENIS FLOW SHOP

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Tessa Vanina Soetanto

1999-01-01

Full Text Available Flow shop scheduling problem is to schedule a production process of n jobs that go through the same process sequence and the same m machines. Most researches are don to accomplish only one objective, i.e. minimizing makespan. The other objective, such as total flow time, or multiple objectives that is minimizing makespan, total flow time and machine idle time, will be more effective in reducing scheduling cost, as written in French (1982. Rajendran algorithm (1995 that solves flow shop problem with multiple objectives will be used to evaluate the proposed algorithm: Genetic Algorithm, developed by Sridhar & Rajendran (1996 on a problem that existed in a shoe factory. Abstract in Bahasa Indonesia : Masalah penjadualan flow shop adalah menjadualkan proses produksi dari masing-masing n job yang mempunyai urutan proses produksi dan melalui m mesin yang sama. Kebanyakan penelitian hanya mengacu pada satu tujuan saja yaitu meminimumkan makespan. Tujuan yang lain, seperti meminimumkan total flow time atau multiple objectives yang meminimumkan makespan, total flow time dan machine idle time akan lebih efektif dalam mengurangi biaya penjadualan, sebagaimana dikatakan oleh French (1982. Algoritma Rajendran (1995 yang menyelesaikan masalah flow shop dengan multiple objectives akan dipergunakan untuk mengevaluasi algoritma usulan: Algoritma Genetika, yang dikembangkan oleh Sridhar & Rajendran (1996 pada suatu masalah yang ditemui di suatu perusahaan sepatu. Kata kunci: flow shop, algoritma genetika, multiple objectives

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

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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.

Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

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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.

Minimizing tardiness for job shop scheduling under uncertainties

OpenAIRE

Yahouni , Zakaria; Mebarki , Nasser; Sari , Zaki

2016-01-01

International audience; —Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback , flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set...

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.

Proposta de classificação hierarquizada dos modelos de solução para o problema de job shop scheduling A proposition of hierarchical classification for solution models in the job shop scheduling 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.

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.

Review of job shop scheduling research and its new perspectives under Industry 4.0

OpenAIRE

Zhang, Jian; Ding, Guofu; Zou, Yisheng; Qin, Sheng-feng; Fu, Jianlin

2017-01-01

Traditional job shop scheduling is concentrated on centralized scheduling or semi-distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and distributed manufacturing system supported by novel and emerging manufacturing technologies such as mass customization, Cyber-Physics Systems, Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud). The scheduling research needs to shift its focus to smart distributed scheduling modeling and optimization. In order to t...

Integrating Preventive Maintenance Scheduling As Probability Machine Failure And Batch Production Scheduling

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Zahedi Zahedi

2016-06-01

Full Text Available This paper discusses integrated model of batch production scheduling and machine maintenance scheduling. Batch production scheduling uses minimize total actual flow time criteria and machine maintenance scheduling uses the probability of machine failure based on Weibull distribution. The model assumed no nonconforming parts in a planning horizon. The model shows an increase in the number of the batch (length of production run up to a certain limit will minimize the total actual flow time. Meanwhile, an increase in the length of production run will implicate an increase in the number of PM. An example was given to show how the model and algorithm work.

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.

A Generalized Ant Colony Algorithm for Job一shop Scheduling Problem

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ZHANG Hong-Guo

2017-02-01

Full Text Available Aiming at the problem of ant colony algorithm for solving Job一shop scheduling problem. Considering the complexity of the algorithm that uses disjunctive graph to describe the relationship between workpiece processing. To solve the problem of optimal solution，a generalized ant colony algorithm is proposed. Under the premise of considering constrained relationship between equipment and process，the pheromone update mechanism is applied to solve Job-shop scheduling problem，so as to improve the quality of the solution. In order to improve the search efficiency，according to the state transition rules of ant colony algorithm，this paper makes a detailed study on the selection and improvement of the parameters in the algorithm，and designs the pheromone update strategy. Experimental results show that a generalized ant colony algorithm is more feasible and more effective. Compared with other algorithms in the literature，the results prove that the algorithm improves in computing the optimal solution and convergence speed.

Multi-Objective Flexible Flow Shop Scheduling Problem Considering Variable Processing Time due to Renewable Energy

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Xiuli Wu

2018-03-01

Full Text Available Renewable energy is an alternative to non-renewable energy to reduce the carbon footprint of manufacturing systems. Finding out how to make an alternative energy-efficient scheduling solution when renewable and non-renewable energy drives production is of great importance. In this paper, a multi-objective flexible flow shop scheduling problem that considers variable processing time due to renewable energy (MFFSP-VPTRE is studied. First, the optimization model of the MFFSP-VPTRE is formulated considering the periodicity of renewable energy and the limitations of energy storage capacity. Then, a hybrid non-dominated sorting genetic algorithm with variable local search (HNSGA-II is proposed to solve the MFFSP-VPTRE. An operation and machine-based encoding method is employed. A low-carbon scheduling algorithm is presented. Besides the crossover and mutation, a variable local search is used to improve the offspring’s Pareto set. The offspring and the parents are combined and those that dominate more are selected to continue evolving. Finally, two groups of experiments are carried out. The results show that the low-carbon scheduling algorithm can effectively reduce the carbon footprint under the premise of makespan optimization and the HNSGA-II outperforms the traditional NSGA-II and can solve the MFFSP-VPTRE effectively and efficiently.

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.

Multiple-Machine Scheduling with Learning Effects and Cooperative Games

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Yiyuan Zhou

2015-01-01

Full Text Available Multiple-machine scheduling problems with position-based learning effects are studied in this paper. There is an initial schedule in this scheduling problem. The optimal schedule minimizes the sum of the weighted completion times; the difference between the initial total weighted completion time and the minimal total weighted completion time is the cost savings. A multiple-machine sequencing game is introduced to allocate the cost savings. The game is balanced if the normal processing times of jobs that are on the same machine are equal and an equal number of jobs are scheduled on each machine initially.

New Mathematical Model and Algorithm for Economic Lot Scheduling Problem in Flexible Flow Shop

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H. Zohali

2018-03-01

Full Text Available This paper addresses the lot sizing and scheduling problem for a number of products in flexible flow shop with identical parallel machines. The production stages are in series, while separated by finite intermediate buffers. The objective is to minimize the sum of setup and inventory holding costs per unit of time. The available mathematical model of this problem in the literature suffers from huge complexity in terms of size and computation. In this paper, a new mixed integer linear program is developed for delay with the huge dimentions of the problem. Also, a new meta heuristic algorithm is developed for the problem. The results of the numerical experiments represent a significant advantage of the proposed model and algorithm compared with the available models and algorithms in the literature.

Genetic Algorithm Combined with Gradient Information for Flexible Job-shop Scheduling Problem with Different Varieties and Small Batches

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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.

Stochastic scheduling on unrelated machines

NARCIS (Netherlands)

Skutella, Martin; Sviridenko, Maxim; Uetz, Marc Jochen

2013-01-01

Two important characteristics encountered in many real-world scheduling problems are heterogeneous machines/processors and a certain degree of uncertainty about the actual sizes of jobs. The first characteristic entails machine dependent processing times of jobs and is captured by the classical

JOB SHOP SCHEDULING BIOBJETIVO MEDIANTE ENFRIAMIENTO SIMULADO Y ENFOQUE DE PARETO JOB-SHOP SCHEDULING: BIO-OBJECTIVE THROUGH SIMULATED COOLING AND PARETO PRINCIPLE

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Juan Carlos Osorio

2012-12-01

Full Text Available El problema del scheduling es uno de los problemas más ampliamente tratados en la literatura; sin embargo, es un problema complejo NP hard. Cuando, además, se involucra más de un objetivo, este problema se convierte en uno de los más complejos en el campo de la investigación de operaciones. Se presenta entonces un modelo biobjetivo para el job shop scheduling que incluye el makespan y el tiempo de flujo medio. Para resolver el modelo se ha utilizado una propuesta que incluye el uso del meta-heurístico Recocido Simulado (SA y el enfoque de Pareto. Este modelo es evaluado en tres problemas presentados en la literatura de tamaños 6x6, 10x5 y 10x10. Los resultados del modelo se comparan con otros meta-heurísticos y se encuentra que este modelo presenta buenos resultados en los tres problemas evaluados.The scheduling problem is one of the most widely treated problems in literature; however, it is an NP hard complex problem. Also, when more than one objective is involved, this problem becomes one of the most complex ones in the field of operations research. A bio-objective model is then emerged for the Job-Shop Scheduling, including makespan and mean flow time. For solving the model a proposal which includes the use of Simulated Annealing (SA metaheuristic and Pareto Principle. This model is evaluated in three problems described in literature with the following sizes: 6x6, 10x5 and 10x10. Results of the model are compared to other metaheuristics and it has been found that this model shows good results in the three problems evaluated.

Using a vision cognitive algorithm to schedule virtual machines

OpenAIRE

Zhao Jiaqi; Mhedheb Yousri; Tao Jie; Jrad Foued; Liu Qinghuai; Streit Achim

2014-01-01

Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the...

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.

Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

Science.gov (United States)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness

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Rui Zhang

2013-04-01

Full Text Available A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

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Muhammad Kamal Amjad

2018-01-01

Full Text Available Flexible Job Shop Scheduling Problem (FJSSP is an extension of the classical Job Shop Scheduling Problem (JSSP. The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

A new Nawaz-Enscore-Ham-based heuristic for permutation flow-shop problems with bicriteria of makespan and machine idle time

Science.gov (United States)

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.

Duality-based algorithms for scheduling on unrelated parallel machines

NARCIS (Netherlands)

van de Velde, S.L.; van de Velde, S.L.

1993-01-01

We 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 assignment of

Generation of Look-Up Tables for Dynamic Job Shop Scheduling Decision Support Tool

Science.gov (United States)

Oktaviandri, Muchamad; Hassan, Adnan; Mohd Shaharoun, Awaluddin

2016-02-01

Majority of existing scheduling techniques are based on static demand and deterministic processing time, while most job shop scheduling problem are concerned with dynamic demand and stochastic processing time. As a consequence, the solutions obtained from the traditional scheduling technique are ineffective wherever changes occur to the system. Therefore, this research intends to develop a decision support tool (DST) based on promising artificial intelligent that is able to accommodate the dynamics that regularly occur in job shop scheduling problem. The DST was designed through three phases, i.e. (i) the look-up table generation, (ii) inverse model development and (iii) integration of DST components. This paper reports the generation of look-up tables for various scenarios as a part in development of the DST. A discrete event simulation model was used to compare the performance among SPT, EDD, FCFS, S/OPN and Slack rules; the best performances measures (mean flow time, mean tardiness and mean lateness) and the job order requirement (inter-arrival time, due dates tightness and setup time ratio) which were compiled into look-up tables. The well-known 6/6/J/Cmax Problem from Muth and Thompson (1963) was used as a case study. In the future, the performance measure of various scheduling scenarios and the job order requirement will be mapped using ANN inverse model.

Machine Shop Practice. Trade and Industrial Education Course of Study.

Science.gov (United States)

Emerly, Robert J.; And Others

Designed for secondary school students who are interested in becoming machinists, this beginning course guide in machine shop practice is organized into the following sections: (1) Introduction, (2) instructional plan, (3) educational philosophy, (4) specific course objectives, (5) course outline, (6) job sheets, and (7) operation sheets. The…

Cyclic machine scheduling with tool transportation - additional calculations

NARCIS (Netherlands)

Kuijpers, C.M.H.

2001-01-01

In the PhD Thesis of Kuijpers a cyclic machine scheduling problem with tool transportation is considered. For the problem with two machines, it is shown that there always exists an optimal schedule with a certain structure. This is done by means of an elaborate case study. For a number of cases some

Sequencing, lot sizing and scheduling in job shops: the common cycle approach

NARCIS (Netherlands)

Ouenniche, J.; Boctor, F.F.

1998-01-01

This paper deals with the multi-product, finite horizon, static demand, sequencing, lot sizing and scheduling problem in a job shop environment where the objective is to minimize the sum of setup and inventory holding costs while satisfying the demand with no backlogging. To solve this problem, we

Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

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.

Using a vision cognitive algorithm to schedule virtual machines

Directory of Open Access Journals (Sweden)

Zhao Jiaqi

2014-09-01

Full Text Available Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption

Production Machine Shop Employment Competencies. Part Three: The Engine Lathe.

Science.gov (United States)

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…

Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

Science.gov (United States)

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

A Hybrid Differential Evolution and Tree Search Algorithm for the Job Shop Scheduling Problem

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Rui Zhang

2011-01-01

Full Text Available The job shop scheduling problem (JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a hybrid differential evolution (DE algorithm is proposed for the problem. To enhance the overall search efficiency, a neighborhood property of the problem is discovered, and then a tree search procedure is designed and embedded into the DE framework. According to the extensive computational experiments, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness objective.

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

OpenAIRE

Bożek Andrzej; Wysocki Marian

2016-01-01

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 ...

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

Science.gov (United States)

Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled

2018-03-01

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 controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

Science.gov (United States)

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

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...

Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS

Directory of Open Access Journals (Sweden)

Arun Gupta

2016-07-01

Full Text Available The flow-shop scheduling problem (FSP has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM method known as techniques for order preference by similarity to an ideal solution (TOPSIS using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time. The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.

Minimizing makespan in a two-stage flow shop with parallel batch-processing machines and re-entrant jobs

Science.gov (United States)

Huang, J. D.; Liu, J. J.; Chen, Q. X.; Mao, N.

2017-06-01

Against a background of heat-treatment operations in mould manufacturing, a two-stage flow-shop scheduling problem is described for minimizing makespan with parallel batch-processing machines and re-entrant jobs. The weights and release dates of jobs are non-identical, but job processing times are equal. A mixed-integer linear programming model is developed and tested with small-scale scenarios. Given that the problem is NP hard, three heuristic construction methods with polynomial complexity are proposed. The worst case of the new constructive heuristic is analysed in detail. A method for computing lower bounds is proposed to test heuristic performance. Heuristic efficiency is tested with sets of scenarios. Compared with the two improved heuristics, the performance of the new constructive heuristic is superior.

A Comparison of the DISASTER (Trademark) Scheduling Software with a Simultaneous Scheduling Algorithm for Minimizing Maximum Tardiness in Job Shops

Science.gov (United States)

1993-09-01

goal ( Heizer , Render , and Stair, 1993:94). Integer Prgronmming. Integer programming is a general purpose approach used to optimally solve job shop...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations

Genetic programming for evolving due-date assignment models in job shop environments.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

Science.gov (United States)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.

M-machine SDST flow shop scheduling using modified heuristic ...

African Journals Online (AJOL)

A computational analysis has been made to evaluate the performance of the proposed MHGA for upto 200 jobs and 20 machines problems. Comparative analysis with the help of defined performance index known as relative percentage deviation (RPD) verifies that it is viable and effective approach when compared with ...

Un algoritmo genético para el problema de Job Shop Flexible A genetic algorithm for the Flexible Job Shop problem

Directory of Open Access Journals (Sweden)

Rosa Medina Durán

2011-06-01

Full Text Available En este estudio se propone e implementa computacionalmente un algoritmo genético secuencial para resolver el problema del Job Shop Flexible (existente en la Gestión de Operaciones, el cual es parte de la familia de los problemas de programación de tareas o trabajos (Scheduling en un taller que funciona a pedido. Surge como una generalización del problema del Job Shop y permite optimizar el uso de los recursos (máquinas con mayor flexibilidad, ya que cada máquina puede realizar más de una operación. Este problema ha sido estudiado por numerosos autores, los que han propuesto diversos modelos matemáticos y enfoques heurísticos. Debido a la naturaleza combinatoria, los métodos exactos que resuelven modelos matemáticos encuentran soluciones sólo para instancias pequeñas o simples del problema mencionado. Los resultados muestran la efectividad del algoritmo propuesto para entregar buenas soluciones en tiempos computacionales razonables en más de 130 instancias encontradas en la literatura.This study proposes and computationally implements a sequential genetic algorithm to solve the Flexible Job Shop problem (found in Operations Management, which is part of the family of job or task scheduling problems in a shop that works on demand. It is a generalization of the Job Shop problem, and allows optimizing the use of resources (machines in the shop, with greater flexibility, since each machine can perform more than one operation. This problem has been studied by many authors, who have proposed various mathematical models and heuristic approaches. Due to the combinatorial nature of the problem, the exact methods that solve the mathematical models are often solutions for small and simple instances of the problem. The results show the effectiveness of the proposed algorithm to provide good solutions in reasonable computational times in over 130 instances found in the literatura.

Extended precedence preservative crossover for job shop scheduling problems

Science.gov (United States)

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.

A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem

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Chun Wang

2017-01-01

Full Text Available A novel multiobjective memetic algorithm based on decomposition (MOMAD is proposed to solve multiobjective flexible job shop scheduling problem (MOFJSP, which simultaneously minimizes makespan, total workload, and critical workload. Firstly, a population is initialized by employing an integration of different machine assignment and operation sequencing strategies. Secondly, multiobjective memetic algorithm based on decomposition is presented by introducing a local search to MOEA/D. The Tchebycheff approach of MOEA/D converts the three-objective optimization problem to several single-objective optimization subproblems, and the weight vectors are grouped by K-means clustering. Some good individuals corresponding to different weight vectors are selected by the tournament mechanism of a local search. In the experiments, the influence of three different aggregation functions is first studied. Moreover, the effect of the proposed local search is investigated. Finally, MOMAD is compared with eight state-of-the-art algorithms on a series of well-known benchmark instances and the experimental results show that the proposed algorithm outperforms or at least has comparative performance to the other algorithms.

Joint optimization of production scheduling and machine group preventive maintenance

International Nuclear Information System (INIS)

Xiao, Lei; Song, Sanling; Chen, Xiaohui; Coit, David W.

2016-01-01

Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. - Highlights: • Group preventive maintenance (PM) planning and production scheduling are jointed. • Maintenance interval and assignment of jobs are decided by minimizing total cost. • Relationships among system age, PM, job processing time are quantified. • Random keys genetic algorithms (GA) are used to solve the NP-hard problem. • Random keys GA and Particle Swarm Optimization (PSO) are compared.

Effectiveness of Podcasts as Laboratory Instructional Support: Learner Perceptions of Machine Shop and Welding Students

Science.gov (United States)

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…

Production Scheduling in Complex Job Shops from an Industrie 4.0 Perspective: A Review and Challenges in the Semiconductor Industry

OpenAIRE

Waschneck, Bernd; Bauernhansl, Thomas; Altenmüller, Thomas; Kyek, Andreas

2017-01-01

On the one hand, Industrie 4.0 has recently emerged as the keyword for increasing productivity in the 21st century. On the other hand, production scheduling in a Complex Job Shop (CJS) environment, such as wafer fabrication facilities, has drawn interest of researchers dating back to the 1950s [65, 18]. Although both research areas overlap, there seems to be very little interchange of ideas. This review presents and assesses production scheduling techniques in complex job shops from an Indust...

REPAIR SHOP JOB SCHEDULING WITH PARALLEL OPERATORS AND MULTIPLE CONSTRAINTS USING SIMULATED ANNEALING

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N. Shivasankaran

2013-04-01

Full Text Available Scheduling problems are generally treated as NP andash; complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP andash; complete problem. For such problems, an efficient technique is required that explores a wide range of solution space. This paper deals with Simulated Annealing Technique, a Meta - heuristic to solve the complex Car Sequencing and Operator Allocation problem in a car repair shop. The algorithm is tested with several constraint settings and the solution quality exceeds the results reported in the literature with high convergence speed and accuracy. This algorithm could be considered as quite effective while other heuristic routine fails.

A Review On Job Shop Scheduling Using Non-Conventional Optimization Algorithm

OpenAIRE

K.Mallikarjuna; Venkatesh.G

2014-01-01

A great deal of research has been focused on solving job shop scheduling problem (∫J), over the last four decades, resulting in a wide variety of approaches. Recently much effort has been concentrated on hybrid methods to solve ∫J, as a single technique cannot solve this stubborn problem. As a result much effort has recently been concentrated on techniques that lead to combinatorial optimization methods and a meta-strategy which guides the search out of local optima. In this p...

Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

Science.gov (United States)

Kiran Kumar, Kalla; Nagaraju, Dega; Gayathri, S.; Narayanan, S.

2017-05-01

Priority Sequencing Rules provide the guidance for the order in which the jobs are to be processed at a workstation. The application of different priority rules in job shop scheduling gives different order of scheduling. More experimentation needs to be conducted before a final choice is made to know the best priority sequencing rule. Hence, a comprehensive method of selecting the right choice is essential in managerial decision making perspective. This paper considers seven different priority sequencing rules in job shop scheduling. For evaluation and selection of the best priority sequencing rule, a set of eight criteria are considered. The aim of this work is to demonstrate the methodology of evaluating and selecting the best priority sequencing rule by using hybrid multi criteria decision making technique (MCDM), i.e., analytical hierarchy process (AHP) with technique for order preference by similarity to ideal solution (TOPSIS). The criteria weights are calculated by using AHP whereas the relative closeness values of all priority sequencing rules are computed based on TOPSIS with the help of data acquired from the shop floor of a manufacturing firm. Finally, from the findings of this work, the priority sequencing rules are ranked from most important to least important. The comprehensive methodology presented in this paper is very much essential for the management of a workstation to choose the best priority sequencing rule among the available alternatives for processing the jobs with maximum benefit.

Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

Directory of Open Access Journals (Sweden)

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.

Prediction based proactive thermal virtual machine scheduling in green clouds.

Science.gov (United States)

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

Science.gov (United States)

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. PMID:24737962

DESIGN OF A HYPERHEURISTIC FOR PRODUCTION SCHEDULING IN JOB SHOP ENVIRONMENTS DISEÑO DE UNA HIPERHEURISTICA PARA LA PROGRAMACION DE LA PRODUCCIÓN EN AMBIENTES JOB SHOP

Directory of Open Access Journals (Sweden)

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%.

A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm

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.

Ant Foraging Behavior for Job Shop Problem

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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.

Car painting process scheduling with harmony search algorithm

Science.gov (United States)

Syahputra, M. F.; Maiyasya, A.; Purnamawati, S.; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.

2018-02-01

Automotive painting program in the process of painting the car body by using robot power, making efficiency in the production system. Production system will be more efficient if pay attention to scheduling of car order which will be done by considering painting body shape of car. Flow shop scheduling is a scheduling model in which the job-job to be processed entirely flows in the same product direction / path. Scheduling problems often arise if there are n jobs to be processed on the machine, which must be specified which must be done first and how to allocate jobs on the machine to obtain a scheduled production process. Harmony Search Algorithm is a metaheuristic optimization algorithm based on music. The algorithm is inspired by observations that lead to music in search of perfect harmony. This musical harmony is in line to find optimal in the optimization process. Based on the tests that have been done, obtained the optimal car sequence with minimum makespan value.

Technical Interoperability for Machine Connectivity on the Shop Floor

Directory of Open Access Journals (Sweden)

Magnus Åkerman

2018-06-01

Full Text Available This paper presents a generic technical solution that can increase Industry 4.0 maturity by collecting data from sensors and control systems on the shop floor. Within the research project “5G-Enabled Manufacturing”, an LTE (Long-Term Evolution network with 5G technologies was deployed on the shop floor to enable fast and scalable connectivity. This network was used to connect a grinding machine to a remote private cloud where data was stored and streamed to a data analytics center. This enabled visibility and transparency of the production data, which is the basis for Industry 4.0 and smart manufacturing. The solution is described with a focus on high-level communication technologies above wireless communication standards. These technologies are discussed regarding technical interoperability, focusing on the system layout, communication standards, and open systems. From the discussion, it can be derived that generic solutions such as this are possible, but manufacturing end-users must expand and further internalize knowledge of future information and communication technologies to reduce their dependency on equipment and technology providers.

A hybrid quantum-inspired genetic algorithm for multiobjective flow shop scheduling.

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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.

Integrating the sequence dependent setup time open shop problem and preventive maintenance policies

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K. Naboureh

2016-09-01

Full Text Available In most industrial environments, it is usually considered that machines are accessible throughout the planning horizon, but in real situation, machines may be unavailable due to a scheduled preventive maintenance where the periods of unavailability are known in advance. The main idea of this paper is to consider different preventive maintenance policies on machines regarding open shop scheduling problem (OSSP with sequence dependent setup times (SDST using immune algorithm. The preventive maintenance (PM policies are planned for maximizing availability of machines or keeping minimum level of reliability through the production horizon. The objective function of the paper is to minimize makespan. In total, the proposed algorithm extensively is compared with six adaptations of existing heuristic and meta-heuristic methods for the problem through data sets from benchmarks based on Taillard’s instances with some adjustments. The results show that the proposed algorithm outperforms other algorithms for this problem.

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

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Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

REDUCING LEAD TIME USING FUZZY LOGIC AT JOB SHOP

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EMİN GÜNDOĞAR

2000-06-01

Full Text Available One problem encountering at the job shop scheduling is minimum production size of machine is different from each another. This case increases lead time. A new approach was improved to reduce lead time. In this new approach, the parts, which materials are in stock and orders coming very frequently are assigned to machine to reduce lead time. Due the fact that there are a lot of machine and orders, it is possible to become so1ne probletns. In this paper, fuzzy logic is used to cope with this problem. New approach was simulated at the job sop that has owner 15 machinery and 50 orders. Simulation results showed that new approach reduced lead time between 27.89% and 32.36o/o

Machine Shop I. Learning Activity Packets (LAPs). Section C--Hand and Bench Work.

Science.gov (United States)

Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains two learning activity packets (LAPs) for the "hand and bench work" instructional area of a Machine Shop I course. The two LAPs cover the following topics: hand and bench work and pedestal grinder. Each LAP contains a cover sheet that describes its purpose, an introduction, and the tasks included in the LAP;…

Approximation algorithms for the parallel flow shop problem

NARCIS (Netherlands)

X. Zhang (Xiandong); S.L. van de Velde (Steef)

2012-01-01

textabstractWe consider the NP-hard problem of scheduling n jobs in m two-stage parallel flow shops so as to minimize the makespan. This problem decomposes into two subproblems: assigning the jobs to parallel flow shops; and scheduling the jobs assigned to the same flow shop by use of Johnson's

A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems

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Nader Ghaffari-Nasab

2010-07-01

Full Text Available During the past two decades, there have been increasing interests on permutation flow shop with different types of objective functions such as minimizing the makespan, the weighted mean flow-time etc. The permutation flow shop is formulated as a mixed integer programming and it is classified as NP-Hard problem. Therefore, a direct solution is not available and meta-heuristic approaches need to be used to find the near-optimal solutions. In this paper, we present a new discrete firefly meta-heuristic to minimize the makespan for the permutation flow shop scheduling problem. The results of implementation of the proposed method are compared with other existing ant colony optimization technique. The preliminary results indicate that the new proposed method performs better than the ant colony for some well known benchmark problems.

T & I--Machine Shop. Kit No. 83. Instructor's Manual [and] Student Learning Activity Guide.

Science.gov (United States)

White, Jim

An instructor's manual and student activity guide on the machine shop are provided in this set of prevocational education materials which focuses on the vocational area of trade and industry. (This set of materials is one of ninety-two prevocational education sets arranged around a cluster of seven vocational offerings: agriculture, home…

A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

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Tao Ren

2015-01-01

Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

Revisiting the NEH algorithm- the power of job insertion technique for optimizing the makespan in permutation flow shop scheduling

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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.

A Pareto archive floating search procedure for solving multi-objective flexible job shop scheduling problem

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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.

Automatic programming via iterated local search for dynamic job shop scheduling.

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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.

Parallel patterns determination in solving cyclic flow shop problem with setups

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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.

A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems

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Mostafa Khorramizadeh

2015-01-01

Full Text Available The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.

COMPARISON BETWEEN MIXED INTEGER PROGRAMMING WITH HEURISTIC METHOD FOR JOB SHOP SCHEDULING WITH SEPARABLE SEQUENCE-DEPENDENT SETUPS

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I Gede Agus Widyadana

2001-01-01

Full Text Available The decisions to choose appropriate tools for solving industrial problems are not just tools that achieve optimal solution only but it should consider computation time too. One of industrial problems that still difficult to achieve both criteria is scheduling problem. This paper discuss comparison between mixed integer programming which result optimal solution and heuristic method to solve job shop scheduling problem with separable sequence-dependent setup. The problems are generated and the result shows that the heuristic methods still cannot satisfy optimal solution.

A RELATIONAL DATABASE APPROACH TO THE JOB SHOP SCHEDULING PROBLEM

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P. Lindeque

2012-01-01

Full Text Available

ENGLISH ABSTRACT: This paper will attempt to illuminate the advantages of an approach to the job shop scheduling problem using priority based search algorithms and database technology. It will use as basis a system developed for and implemented at a large manufacturing plant. The paper will also attempt to make some predictions as to future developments in these techniques and look at the possibility of including new technologies such as expert systems.

AFRIKAANSE OPSOMMING: Die voordele en toepaslikheid van prioriteits-gebaseerde soek-algoritmes en databasisstelsels op die taakwerkswinkelprobleem sal in hierdie artikel uitgelig word. 'n Stelsel wat by 'n groot vervaardigingsonderneming geimplementeer is, sal as uitgangspunt gebruik word. Toekomstige ontwikkelings in bogenoemde tegnieke en die moontlike insluiting van ekspertstelsels sal ook ondersoek word.

The desktop muon detector: A simple, physics-motivated machine- and electronics-shop project for university students

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Axani, S. N.; Conrad, J. M.; Kirby, C.

2017-12-01

This paper describes the construction of a desktop muon detector, an undergraduate-level physics project that develops machine-shop and electronics-shop technical skills. The desktop muon detector is a self-contained apparatus that employs a plastic scintillator as the detection medium and a silicon photomultiplier for light collection. This detector can be battery powered and is used in conjunction with the provided software. The total cost per detector is approximately 100. We describe physics experiments we have performed, and then suggest several other interesting measurements that are possible, with one or more desktop muon detectors.

Flowshop Scheduling Problems with a Position-Dependent Exponential Learning Effect

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Mingbao Cheng

2013-01-01

Full Text Available We consider a permutation flowshop scheduling problem with a position-dependent exponential learning effect. The objective is to minimize the performance criteria of makespan and the total flow time. For the two-machine flow shop scheduling case, we show that Johnson’s rule is not an optimal algorithm for minimizing the makespan given the exponential learning effect. Furthermore, by using the shortest total processing times first (STPT rule, we construct the worst-case performance ratios for both criteria. Finally, a polynomial-time algorithm is proposed for special cases of the studied problem.

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

OpenAIRE

Rustogi, Kabir; Strusevich, Vitaly A.

2015-01-01

We study single machine scheduling problems with linear time-dependent deterioration effects and maintenance activities. Maintenance periods (MPs) are included into the schedule, so that the machine, that gets worse during the processing, can be restored to a better state. We deal with a job-independent version of the deterioration effects, that is, all jobs share a common deterioration rate. However, we introduce a novel extension to such models and allow the deterioration rates to change af...

Abbreviated machining schedule for fabricating beryllium parts free of surface damage

International Nuclear Information System (INIS)

Beitscher, S.; Capes, J.F.; Leslie, W.W.; Luckow, J.R.; Riegel, R.L.

1979-01-01

This study was performed to develop a more economical method of machining damage-free beryllium components at Rocky Flats. The present method involves a 9-pass schedule of lathe turning followed by a chemical etch. Prototype beryllium hemispherical shell parts and cylindrical tensile specimens machined to simulate the parts were utilized in this study. The main investigative methods used to evaluate the amount of machining damage were metallography and tensile tests. It was found that damage-free parts could be produced by carefully controlled machining if the number of machining passes was reduced to 4 or even 3, if followed by the standard etching treatment. These findings were made on Select S-65 grade beryllium, and probably apply to other common grades of powder source beryllium but not necessarily to ingot-source beryllium. It is recommended that the 4-pass schedule becomes the standard method to produce damage-free beryllium derived from powder. Significant savings in time, labor, and equipment can be realized by this change in method without decreasing the quality of the product

A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system

International Nuclear Information System (INIS)

Azadeh, A.; Maleki Shoja, B.; Ghanei, S.; Sheikhalishahi, M.

2015-01-01

This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimal/near optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimal/near optimal solution within a very reasonable time. - Highlights: • A redundancy-scheduling optimization problem for a multi-state series parallel system. • A flow shop with multi-state machines and warm standby redundancy. • Objectives are to optimize system purchasing cost, makespan and reliability. • Different test problems are generated and evaluated by a unique genetic algorithm. • It locates optimal/near optimal solution within a very reasonable time

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

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Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

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Ruochen Liu

2013-01-01

Full Text Available The permutation flow shop scheduling problem (PFSSP is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO based memetic algorithm (MPSOMA is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS and individual improvement scheme (IIS. Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA, on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

Science.gov (United States)

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.

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.

Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags

Science.gov (United States)

ZHAO, Ning; YE, Song; LI, Kaidian; CHEN, Siyu

2017-05-01

Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.

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.

Single-machine scheduling of proportionally deteriorating jobs by two agents

OpenAIRE

S Gawiejnowicz; W-C Lee; C-L Lin; C-C Wu

2011-01-01

We consider a problem of scheduling a set of independent jobs by two agents on a single machine. Every agent has its own subset of jobs to be scheduled and uses its own optimality criterion. The processing time of each job proportionally deteriorates with respect to the starting time of the job. The problem is to find a schedule that minimizes the total tardiness of the first agent, provided that no tardy job is allowed for the second agent. We prove basic properties of the problem and give a...

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.

Optimization of operating schedule of machines in granite industry using evolutionary algorithms

International Nuclear Information System (INIS)

Loganthurai, P.; Rajasekaran, V.; Gnanambal, K.

2014-01-01

Highlights: • Operating time of machines in granite industries was studied. • Operating time has been optimized using evolutionary algorithms such as PSO, DE. • The maximum demand has been reduced. • Hence the electricity cost of the industry and feeder stress have been reduced. - Abstract: Electrical energy consumption cost plays an important role in the production cost of any industry. The electrical energy consumption cost is calculated as two part tariff, the first part is maximum demand cost and the second part is energy consumption cost or unit cost (kW h). The maximum demand cost can be reduced without affecting the production. This paper focuses on the reduction of maximum demand by proper operating schedule of major equipments. For this analysis, various granite industries are considered. The major equipments in granite industries are cutting machine, polishing machine and compressor. To reduce the maximum demand, the operating time of polishing machine is rescheduled by optimization techniques such as Differential Evolution (DE) and particle swarm optimization (PSO). The maximum demand costs are calculated before and after rescheduling. The results show that if the machines are optimally operated, the cost is reduced. Both DE and PSO algorithms reduce the maximum demand cost at the same rate for all the granite industries. However, the optimum scheduling obtained by DE reduces the feeder power flow than the PSO scheduling

Minimizing total weighted completion time in a proportionate flow shop

NARCIS (Netherlands)

Shakhlevich, N.V.; Hoogeveen, J.A.; Pinedo, M.L.

1998-01-01

We study the special case of the m machine flow shop problem in which the processing time of each operation of job j is equal to pj; this variant of the flow shop problem is known as the proportionate flow shop problem. We show that for any number of machines and for any regular performance

Iterated greedy algorithms to minimize the total family flow time for job-shop scheduling with job families and sequence-dependent set-ups

Science.gov (United States)

Kim, Ji-Su; Park, Jung-Hyeon; Lee, Dong-Ho

2017-10-01

This study addresses a variant of job-shop scheduling in which jobs are grouped into job families, but they are processed individually. The problem can be found in various industrial systems, especially in reprocessing shops of remanufacturing systems. If the reprocessing shop is a job-shop type and has the component-matching requirements, it can be regarded as a job shop with job families since the components of a product constitute a job family. In particular, sequence-dependent set-ups in which set-up time depends on the job just completed and the next job to be processed are also considered. The objective is to minimize the total family flow time, i.e. the maximum among the completion times of the jobs within a job family. A mixed-integer programming model is developed and two iterated greedy algorithms with different local search methods are proposed. Computational experiments were conducted on modified benchmark instances and the results are reported.

Decentralization and mechanism design for online machine scheduling

NARCIS (Netherlands)

Arge, Lars; Heydenreich, Birgit; Müller, Rudolf; Freivalds, Rusins; Uetz, Marc Jochen

We study the online version of the classical parallel machine scheduling problem to minimize the total weighted completion time from a new perspective: We assume that the data of each job, namely its release date $r_j$, its processing time $p_j$ and its weight $w_j$ is only known to the job itself,

An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times

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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.

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.

Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

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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 methodology for a machining process scheduling in spot electricity markets

International Nuclear Information System (INIS)

Yusta, J.M.; Torres, F.; Khodr, H.M.

2010-01-01

Electricity spot markets have introduced hourly variations in the price of electricity. These variations allow the increase of the energy efficiency by the appropriate scheduling and adaptation of the industrial production to the hourly cost of electricity in order to obtain the maximum profit for the industry. In this article a mathematical optimization model simulates costs and the electricity demand of a machining process. The resultant problem is solved using the generalized reduced gradient approach, to find the optimum production schedule that maximizes the industry profit considering the hourly variations of the price of electricity in the spot market. Different price scenarios are studied to analyze the impact of the spot market prices for electricity on the optimal scheduling of the machining process and on the industry profit. The convenience of the application of the proposed model is shown especially in cases of very high electricity prices.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

Science.gov (United States)

Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

Job shop scheduling by simulated annealing

NARCIS (Netherlands)

Laarhoven, van P.J.M.; Aarts, E.H.L.; Lenstra, J.K.

1992-01-01

We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems. The generalization involves the acceptance of

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

Science.gov (United States)

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.

Machine en theater : ontwerpconcepten van winkelgebouwen

NARCIS (Netherlands)

Kooyman, D.

1999-01-01

Machine and Theater. Design Concepts for Shop Buildings Most retail trade takes place in shops. For retailers a shop is the physical context for their commercial activities. Consumers spend a substantial amount of their time there, making essential purchases and also window shopping. Machine and

Machine en theater : ontwerpconcepten van winkelgebouwen

OpenAIRE

Kooyman, D.

1999-01-01

Machine and Theater. Design Concepts for Shop Buildings Most retail trade takes place in shops. For retailers a shop is the physical context for their commercial activities. Consumers spend a substantial amount of their time there, making essential purchases and also window shopping. Machine and theatre, design concepts for shop buildings investigates the function and the significance of shop space. The arcade, the department store, the supermarket, the shopping centre, the big-box retail par...

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.

Perancangan Sistem Penjadwalan Mesin Hybrid Flow Shop dengan Algoritma Levyflight Discrete Firefly

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Andrew Verrayo Limas

2014-12-01

Full Text Available The main issues that have been encountered in PT Surya Toto Indonesia is companies do not know how to measure the performance of the production process so as the utilization of resources that will be used isn’t yet to be known with efficiently. The purpose of this case studies is creating a better production processes by proposing a better and systematic scheduling information system. An Object Oriented Analysis and Design method is used to determine system’s requirements and design of the system architecture. Metaheuristic methods such as Discrete algorithms Levy-flight Firefly is used to improve the performance of the Hybrid Flow Shop machine scheduling become more better. Indicators that are used to determine the performance of the scheduling is makespan and lateness. Results from this algorithm is makespan value of 305.27 hours with lateness value of 10.92 which determine that there is no delays in scheduling. Scheduling information system was designed three primary capabilities, which are integrated data management, inventory management and a systematic and accurate scheduling system.

One-machine job-scheduling with non-constant capacity - Minimizing weighted completion times

NARCIS (Netherlands)

Amaddeo, H.F.; Amaddeo, H.F.; Nawijn, W.M.; van Harten, Aart

1997-01-01

In this paper an n-job one-machine scheduling problem is considered, in which the machine capacity is time-dependent and jobs are characterized by their work content. The objective is to minimize the sum of weighted completion times. A necessary optimality condition is presented and we discuss some

Minimizing Total Busy Time with Application to Energy-efficient Scheduling of Virtual Machines in IaaS clouds

OpenAIRE

Quang-Hung, Nguyen; Thoai, Nam

2016-01-01

Infrastructure-as-a-Service (IaaS) clouds have become more popular enabling users to run applications under virtual machines. Energy efficiency for IaaS clouds is still challenge. This paper investigates the energy-efficient scheduling problems of virtual machines (VMs) onto physical machines (PMs) in IaaS clouds along characteristics: multiple resources, fixed intervals and non-preemption of virtual machines. The scheduling problems are NP-hard. Most of existing works on VM placement reduce ...

Proportionate Flow Shop Games

NARCIS (Netherlands)

Estevez Fernandez, M.A.; Mosquera, M.A.; Borm, P.E.M.; Hamers, H.J.M.

2006-01-01

In a proportionate flow shop problem several jobs have to be processed through a fixed sequence of machines and the processing time of each job is equal on all machines.By identifying jobs with agents, whose costs linearly depend on the completion time of their jobs, and assuming an initial

Parallel Machine Scheduling with Batch Delivery to Two Customers

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Xueling Zhong

2015-01-01

Full Text Available In some make-to-order supply chains, the manufacturer needs to process and deliver products for customers at different locations. To coordinate production and distribution operations at the detailed scheduling level, we study a parallel machine scheduling model with batch delivery to two customers by vehicle routing method. In this model, the supply chain consists of a processing facility with m parallel machines and two customers. A set of jobs containing n1 jobs from customer 1 and n2 jobs from customer 2 are first processed in the processing facility and then delivered to the customers directly without intermediate inventory. The problem is to find a joint schedule of production and distribution such that the tradeoff between maximum arrival time of the jobs and total distribution cost is minimized. 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. We provide polynomial time heuristics with worst-case performance analysis for the problem. If m=2 and (n1-b(n2-b<0, we propose a heuristic with worst-case ratio bound of 3/2, where b is the capacity of the delivery shipment. Otherwise, the worst-case ratio bound of the heuristic we propose is 2-2/(m+1.

Scheduling Agreeable Jobs On A Single Machine To Minimize ...

African Journals Online (AJOL)

Journal of Applied Science and Technology ... (NP) scheduling of number of jobs on a single machine to minimize weighted number of early and tardy jobs where the earliest start times and latest due date are agreeable (i.e. earliest start time must increase in the same sequence as latest due dates) has been considered.

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

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.

A modified genetic algorithm for time and cost optimization of an additive manufacturing single-machine scheduling

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M. Fera

2018-09-01

Full Text Available Additive Manufacturing (AM is a process of joining materials to make objects from 3D model data, usually layer by layer, as opposed to subtractive manufacturing methodologies. Selective Laser Melting, commercially known as Direct Metal Laser Sintering (DMLS®, is the most diffused additive process in today’s manufacturing industry. Introduction of a DMLS® machine in a production department has remarkable effects not only on industrial design but also on production planning, for example, on machine scheduling. Scheduling for a traditional single machine can employ consolidated models. Scheduling of an AM machine presents new issues because it must consider the capability of producing different geometries, simultaneously. The aim of this paper is to provide a mathematical model for an AM/SLM machine scheduling. The complexity of the model is NP-HARD, so possible solutions must be found by metaheuristic algorithms, e.g., Genetic Algorithms. Genetic Algorithms solve sequential optimization problems by handling vectors; in the present paper, we must modify them to handle a matrix. The effectiveness of the proposed algorithms will be tested on a test case formed by a 30 Part Number production plan with a high variability in complexity, distinct due dates and low production volumes.

Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates

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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.

Asymptotic analysis of SPTA-based algorithms for no-wait flow shop scheduling problem with release dates.

Science.gov (United States)

Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

2014-01-01

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.

Variable Neighbourhood Search and Mathematical Programming for Just-in-Time Job-Shop Scheduling Problem

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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.

Optimal and online preemptive scheduling on uniformly related machines

Czech Academy of Sciences Publication Activity Database

Ebenlendr, Tomáš; Sgall, J.

2009-01-01

Roč. 12, č. 5 (2009), s. 517-527 ISSN 1094-6136 R&D Projects: GA MŠk(CZ) 1M0545; GA AV ČR IAA100190902; GA AV ČR IAA1019401 Institutional research plan: CEZ:AV0Z10190503 Keywords : online scheduling * preemption * uniformly related machines Subject RIV: IN - Informatics, Computer Science Impact factor: 1.265, year: 2009

A Heuristic Scheduling Algorithm for Minimizing Makespan and Idle Time in a Nagare Cell

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M. Muthukumaran

2012-01-01

Full Text Available Adopting a focused factory is a powerful approach for today manufacturing enterprise. This paper introduces the basic manufacturing concept for a struggling manufacturer with limited conventional resources, providing an alternative solution to cell scheduling by implementing the technique of Nagare cell. Nagare cell is a Japanese concept with more objectives than cellular manufacturing system. It is a combination of manual and semiautomatic machine layout as cells, which gives maximum output flexibility for all kind of low-to-medium- and medium-to-high- volume productions. The solution adopted is to create a dedicated group of conventional machines, all but one of which are already available on the shop floor. This paper focuses on the development of heuristic scheduling algorithm in step-by-step method. The algorithm states that the summation of processing time of all products on each machine is calculated first and then the sum of processing time is sorted by the shortest processing time rule to get the assignment schedule. Based on the assignment schedule Nagare cell layout is arranged for processing the product. In addition, this algorithm provides steps to determine the product ready time, machine idle time, and product idle time. And also the Gantt chart, the experimental analysis, and the comparative results are illustrated with five (1×8 to 5×8 scheduling problems. Finally, the objective of minimizing makespan and idle time with greater customer satisfaction is studied through.

A Heuristic Approach for Determining Lot Sizes and Schedules Using Power-of-Two Policy

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Esra Ekinci

2007-01-01

Full Text Available We consider the problem of determining realistic and easy-to-schedule lot sizes in a multiproduct, multistage manufacturing environment. We concentrate on a specific type of production, namely, flow shop type production. The model developed consists of two parts, lot sizing problem and scheduling problem. In lot sizing problem, we employ binary integer programming and determine reorder intervals for each product using power-of-two policy. In the second part, using the results obtained of the lot sizing problem, we employ mixed integer programming to determine schedules for a multiproduct, multistage case with multiple machines in each stage. Finally, we provide a numerical example and compare the results with similar methods found in practice.

A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem

DEFF Research Database (Denmark)

Rahmati, Seyed Habib A.; Ahmadi, Abbas; Govindan, Kannan

2018-01-01

the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied......Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing...... production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing...

A New Approach to Solve Flowshop Scheduling Problems by Artificial Immune Systems = Akış Tipi Çizelgeleme Problemlerinin Yapay Bağışıklık Sistemleri ile Çözümünde Yeni Bir Yaklaşım

Directory of Open Access Journals (Sweden)

Alper DÖYEN

2007-01-01

Full Text Available The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the criteria of makespan minimization for the flow shop scheduling problem. Artificial Immune Systems (AIS are new intelligent problem solving techniques that are being used in scheduling problems. AIS can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. In this research, a computational method based on clonal selection principle and affinity maturation mechanisms of the immune response is used. The operation parameters of meta-heuristics have an important role on the quality of the solution. Thus, a generic systematic procedure which bases on a multi-step experimental design approach for determining the efficient system parameters for AIS is presented. Experimental results show that, the artificial immune system algorithm is more efficient than both the classical heuristic flow shop scheduling algorithms and simulated annealing.

Machine Maintenance Scheduling with Reliability Engineering Method and Maintenance Value Stream Mapping

Science.gov (United States)

Sembiring, N.; Nasution, A. H.

2018-02-01

Corrective maintenance i.e replacing or repairing the machine component after machine break down always done in a manufacturing company. It causes the production process must be stopped. Production time will decrease due to the maintenance team must replace or repair the damage machine component. This paper proposes a preventive maintenance’s schedule for a critical component of a critical machine of an crude palm oil and kernel company due to increase maintenance efficiency. The Reliability Engineering & Maintenance Value Stream Mapping is used as a method and a tool to analize the reliability of the component and reduce the wastage in any process by segregating value added and non value added activities.

A Mutualism Quantum Genetic Algorithm to Optimize the Flow Shop Scheduling with Pickup and Delivery Considerations

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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.

A proposal simulated annealing algorithm for proportional parallel flow shops with separated setup times

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Helio Yochihiro Fuchigami

2014-08-01

Full Text Available This article addresses the problem of minimizing makespan on two parallel flow shops with proportional processing and setup times. The setup times are separated and sequence-independent. The parallel flow shop scheduling problem is a specific case of well-known hybrid flow shop, characterized by a multistage production system with more than one machine working in parallel at each stage. This situation is very common in various kinds of companies like chemical, electronics, automotive, pharmaceutical and food industries. This work aimed to propose six Simulated Annealing algorithms, their perturbation schemes and an algorithm for initial sequence generation. This study can be classified as “applied research” regarding the nature, “exploratory” about the objectives and “experimental” as to procedures, besides the “quantitative” approach. The proposed algorithms were effective regarding the solution and computationally efficient. Results of Analysis of Variance (ANOVA revealed no significant difference between the schemes in terms of makespan. It’s suggested the use of PS4 scheme, which moves a subsequence of jobs, for providing the best percentage of success. It was also found that there is a significant difference between the results of the algorithms for each value of the proportionality factor of the processing and setup times of flow shops.

An corrigendum on the paper : Solving the job-shop scheduling problem optimally by dynamic programming (Computers and Operations Research 39(12) (2968–2977) (S0305054812000500) (10.1016/j.cor.2012.02.024))

NARCIS (Netherlands)

van Hoorn, Jelke J.; Nogueira, Agustín; Ojea, Ignacio; Gromicho Dos Santos, Joaquim Antonio

2017-01-01

In [1] an algorithm is proposed for solving the job-shop scheduling problem optimally using a dynamic programming strategy. This is, according to our knowledge, the first exact algorithm for the Job Shop problem which is not based on integer linear programming and branch and bound. Despite the

Single machine scheduling with slack due dates assignment

Science.gov (United States)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.

PENGEMBANGAN ALGORITMA PENJADUALAN PRODUKSI JOB SHOP UNTUK MEMINIMUMKAN TOTAL BIAYA EARLINESS DAN TARDINESS

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Dian Retno Sari Dewi

2005-12-01

Full Text Available This paper develops job shop production scheduling using Non Delay algorithm through forward and backward-forward algorithm to minimize total earliness and tardiness costs. Backward approach has some disadvantages, such as, if the job is scheduled in backward, there is a possibility that the infeasible situation occurs, in which the job is scheduled at t<0. This paper used hypothetic data generated randomly. This job shop scheduling algorithm development was validated using LINDO software to check the effectiveness heuristic method, compared with the optimation method. The validation proves that the result of backward-forward scheduling method is better than the result of forward scheduling method.

Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.

Science.gov (United States)

Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan

2016-01-01

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.

Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

Science.gov (United States)

Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

2018-03-01

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems

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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.

Forecasting of indirect consumables for a Job Shop

Science.gov (United States)

Shakeel, M.; Khan, S.; Khan, W. A.

2016-08-01

A job shop has an arrangement where similar machines (Direct consumables) are grouped together and use indirect consumables to produce a product. The indirect consumables include hack saw blades, emery paper, painting brush etc. The job shop is serving various orders at a particular time for the optimal operation of job shop. Forecasting is required to predict the demand of direct and indirect consumables in a job shop. Forecasting is also needed to manage lead time, optimize inventory cost and stock outs. The objective of this research is to obtain the forecast for indirect consumables. The paper shows how job shop can manage their indirect consumables more accurately by establishing a new technique of forecasting. This results in profitable use of job shop by multiple users.

Machine scheduling to minimize weighted completion times the use of the α-point

CERN Document Server

Gusmeroli, Nicoló

2018-01-01

This work reviews the most important results regarding the use of the α-point in Scheduling Theory. It provides a number of different LP-relaxations for scheduling problems and seeks to explain their polyhedral consequences. It also explains the concept of the α-point and how the conversion algorithm works, pointing out the relations to the sum of the weighted completion times. Lastly, the book explores the latest techniques used for many scheduling problems with different constraints, such as release dates, precedences, and parallel machines. This reference book is intended for advanced undergraduate and postgraduate students who are interested in scheduling theory. It is also inspiring for researchers wanting to learn about sophisticated techniques and open problems of the field.

Single-machine scheduling with release dates, due dates and family setup times

NARCIS (Netherlands)

Schutten, Johannes M.J.; van de Velde, S.L.; van de Velde, S.L.; Zijm, Willem H.M.

1996-01-01

We address the NP-hard problem of scheduling n independent jobs with release dates, due dates, and family setup times on a single machine to minimize the maximum lateness. This problem arises from the constant tug-of-war going on in manufacturing between efficient production and delivery

Parallel genetic algorithms with migration for the hybrid flow shop scheduling problem

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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.

Simulation as a planning tool for job-shop production environment

Science.gov (United States)

Maram, Venkataramana; Nawawi, Mohd Kamal Bin Mohd; Rahman, Syariza Abdul; Sultan, Sultan Juma

2015-12-01

In this paper, we made an attempt to use discrete event simulation software ARENA® as a planning tool for job shop production environment. We considered job shop produces three types of Jigs with different sequence of operations to study and improve shop floor performance. The sole purpose of the study is to identifying options to improve machines utilization, reducing job waiting times at bottleneck machines. First, the performance of the existing system was evaluated by using ARENA®. Then identified improvement opportunities by analyzing base system results. Second, updated the model with most economical options. The proposed new system outperforms with that of the current base system by 816% improvement in delay times at paint shop by increase 2 to 3 and Jig cycle time reduces by Jig1 92%, Jig2 65% and Jig3 41% and hence new proposal was recommended.

Dynamic scheduling and analysis of real time systems with multiprocessors

Directory of Open Access Journals (Sweden)

M.D. Nashid Anjum

2016-08-01

Full Text Available This research work considers a scenario of cloud computing job-shop scheduling problems. We consider m realtime jobs with various lengths and n machines with different computational speeds and costs. Each job has a deadline to be met, and the profit of processing a packet of a job differs from other jobs. Moreover, considered deadlines are either hard or soft and a penalty is applied if a deadline is missed where the penalty is considered as an exponential function of time. The scheduling problem has been formulated as a mixed integer non-linear programming problem whose objective is to maximize net-profit. The formulated problem is computationally hard and not solvable in deterministic polynomial time. This research work proposes an algorithm named the Tube-tap algorithm as a solution to this scheduling optimization problem. Extensive simulation shows that the proposed algorithm outperforms existing solutions in terms of maximizing net-profit and preserving deadlines.

A Three-Stage Optimization Algorithm for the Stochastic Parallel Machine Scheduling Problem with Adjustable Production Rates

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.

Single-machine scheduling with release dates, due dates, and family setup times

NARCIS (Netherlands)

J.M.J. Schutten (Marco); S.L. van de Velde (Steef); W.H.M. Zijm

1996-01-01

textabstractWe address the NP-hard problem of scheduling n independent jobs with release dates, due dates, and family setup times on a single machine to minimize the maximum lateness. This problem arises from the constant tug-of-war going on in manufacturing between efficient production and delivery

Expanding Options. A Model to Attract Secondary Students into Nontraditional Vocational Programs. For Emphasis in: Building Trades, Electronics, Health Services, Machine Shop, Welding.

Science.gov (United States)

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…

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.

Minimizing the Makespan for a Two-Stage Three-Machine Assembly Flow Shop Problem with the Sum-of-Processing-Time Based Learning Effect

Directory of Open Access Journals (Sweden)

Win-Chin Lin

2018-01-01

Full Text Available Two-stage production process and its applications appear in many production environments. Job processing times are usually assumed to be constant throughout the process. In fact, the learning effect accrued from repetitive work experiences, which leads to the reduction of actual job processing times, indeed exists in many production environments. However, the issue of learning effect is rarely addressed in solving a two-stage assembly scheduling problem. Motivated by this observation, the author studies a two-stage three-machine assembly flow shop problem with a learning effect based on sum of the processing times of already processed jobs to minimize the makespan criterion. Because this problem is proved to be NP-hard, a branch-and-bound method embedded with some developed dominance propositions and a lower bound is employed to search for optimal solutions. A cloud theory-based simulated annealing (CSA algorithm and an iterated greedy (IG algorithm with four different local search methods are used to find near-optimal solutions for small and large number of jobs. The performances of adopted algorithms are subsequently compared through computational experiments and nonparametric statistical analyses, including the Kruskal–Wallis test and a multiple comparison procedure.

Two parameter-tuned metaheuristic algorithms for the multi-level lot sizing and scheduling problem

Directory of Open Access Journals (Sweden)

S.M.T. Fatemi Ghomi

2012-10-01

Full Text Available This paper addresses the problem of lot sizing and scheduling problem for n-products and m-machines in flow shop environment where setups among machines are sequence-dependent and can be carried over. Many products must be produced under capacity constraints and allowing backorders. Since lot sizing and scheduling problems are well-known strongly NP-hard, much attention has been given to heuristics and metaheuristics methods. This paper presents two metaheuristics algorithms namely, Genetic Algorithm (GA and Imperialist Competitive Algorithm (ICA. Moreover, Taguchi robust design methodology is employed to calibrate the parameters of the algorithms for different size problems. In addition, the parameter-tuned algorithms are compared against a presented lower bound on randomly generated problems. At the end, comprehensive numerical examples are presented to demonstrate the effectiveness of the proposed algorithms. The results showed that the performance of both GA and ICA are very promising and ICA outperforms GA statistically.

PROMSYS, Plant Equipment Maintenance and Inspection Scheduling

International Nuclear Information System (INIS)

Morgan, D.L.; Srite, B.E.

1986-01-01

1 - Description of problem or function: PROMSYS is a computer system designed to automate the scheduling of routine maintenance and inspection of plant equipment. This 'programmed maintenance' provides the detailed planning and accomplishment of lubrication, inspection, and similar repetitive maintenance activities which can be scheduled at specified predetermined intervals throughout the year. The equipment items included are the typical pumps, blowers, motors, compressors, automotive equipment, refrigeration units, filtering systems, machine shop equipment, cranes, elevators, motor-generator sets, and electrical switchgear found throughout industry, as well as cell ventilation, shielding, containment, and material handling equipment unique to nuclear research and development facilities. Four related programs are used to produce sorted schedule lists, delinquent work lists, and optional master lists. Five additional programs are used to create and maintain records of all scheduled and unscheduled maintenance history. 2 - Method of solution: Service specifications and frequency are established and stored. The computer program reviews schedules weekly and prints, on schedule cards, instructions for service that is due the following week. The basic output from the computer program comes in two forms: programmed-maintenance schedule cards and programmed-maintenance data sheets. The data sheets can be issued in numerical building, route, and location number sequence as equipment lists, grouped for work assigned to a particular foreman as the foreman's equipment list, or grouped by work charged to a particular work order as the work-order list. Data sheets grouped by equipment classification are called the equipment classification list

Uma propriedade estrutural do problema de programação da produção flow shop permutacional com tempos de setup

Directory of Open Access Journals (Sweden)

João Vitor Moccellin

2007-01-01

Full Text Available Neste artigo apresenta-se uma propriedade estrutural do problema de programação da produção flow shop permutacional com tempos de setup das máquinas separados dos tempos de processamento das tarefas, a qual foi identificada a partir de investigações que foram realizadas sobre as características do problema. Tal propriedade fornece um limitante superior do tempo de máquina parada entre a sua preparação e o início de execução das tarefas. Utilizando a propriedade, o problema original de programação da produção com minimização do makespan pode ser resolvido de maneira heurística por meio de uma analogia com o problema assimétrico do caixeiro-viajante.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 a structural property is introduced. Such a property provides an upper bound on the idle time of the machines between the setup task and the job processing. As an application of this property, the original scheduling problem with the makespan criterion can be heuristically solved by an analogy with the asymmetric traveling salesman problem.

Apprenticeship Learning: Learning to Schedule from Human Experts

Science.gov (United States)

2016-06-09

identified by the heuristic . A spectrum of problems (i.e. traveling salesman, job-shop scheduling, multi-vehicle routing) was represented , as task locations...caus- ing the codification of this knowledge to become labori- ous. We propose a new approach for capturing domain- expert heuristics through a...demonstrate that this approach accu- rately learns multi-faceted heuristics on both a synthetic data set incorporating job-shop scheduling and vehicle

A Hybrid Genetic Algorithm to Minimize Total Tardiness for Unrelated Parallel Machine Scheduling with Precedence Constraints

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.

Holistic virtual machine scheduling in cloud datacenters towards minimizing total energy

OpenAIRE

Li, Xiang; Garraghan, Peter; Jiang, Xiaohong; Wu, Zhaohui; Xu, Jie

2018-01-01

Energy consumed by Cloud datacenters has dramatically increased, driven by rapid uptake of applications and services globally provisioned through virtualization. By applying energy-aware virtual machine scheduling, Cloud providers are able to achieve enhanced energy efficiency and reduced operation cost. Energy consumption of datacenters consists of computing energy and cooling energy. However, due to the complexity of energy and thermal modeling of realistic Cloud datacenter operation, tradi...

Online scheduling of jobs with fixed start times on related machines

Czech Academy of Sciences Publication Activity Database

Epstein, L.; Jeż, Łukasz; Sgall, J.; van Stee, R.

2016-01-01

Roč. 74, č. 1 (2016), s. 156-176 ISSN 0178-4617 R&D Projects: GA AV ČR IAA100190902; GA ČR GBP202/12/G061 Institutional support: RVO:67985840 Keywords : online scheduling * online algorithms * related machines Subject RIV: BA - General Mathematics Impact factor: 0.735, year: 2016 http://link.springer.com/article/10.1007%2Fs00453-014-9940-2

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem

Science.gov (United States)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2017-11-01

This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.

An Improved Particle Swarm Optimization for Selective Single Machine Scheduling with Sequence Dependent Setup Costs and Downstream Demands

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.

Interactive Anticipatory Scheduling for Two Military Applications

National Research Council Canada - National Science Library

Howe, Adele

2003-01-01

...; these models partially explain what makes some job shop scheduling problems difficult. For the second, several algorithms for Air Force Satellite Control Network scheduling have been compared on historical and recent data...

ROBUST-HYBRID GENETIC ALGORITHM FOR A FLOW-SHOP SCHEDULING PROBLEM (A Case Study at PT FSCM Manufacturing Indonesia

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

Estimation of distribution algorithm with path relinking for the blocking flow-shop scheduling problem

Science.gov (United States)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2018-05-01

This article presents an effective estimation of distribution algorithm, named P-EDA, to solve the blocking flow-shop scheduling problem (BFSP) with the makespan criterion. In the P-EDA, a Nawaz-Enscore-Ham (NEH)-based heuristic and the random method are combined to generate the initial population. Based on several superior individuals provided by a modified linear rank selection, a probabilistic model is constructed to describe the probabilistic distribution of the promising solution space. The path relinking technique is incorporated into EDA to avoid blindness of the search and improve the convergence property. A modified referenced local search is designed to enhance the local exploitation. Moreover, a diversity-maintaining scheme is introduced into EDA to avoid deterioration of the population. Finally, the parameters of the proposed P-EDA are calibrated using a design of experiments approach. Simulation results and comparisons with some well-performing algorithms demonstrate the effectiveness of the P-EDA for solving BFSP.

Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

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.

Preemptive scheduling of independent jobs on identical parallel machines subject to migration delays

NARCIS (Netherlands)

Fishkin, A.V.; Jansen, K.; Sevastyanov, S.V.; Sitters, R.A.; Leonardi, S.

2005-01-01

We present hardness and approximation results for the problem of scheduling n independent jobs on m identical parallel machines subject to a migration delay d so as to minimize the makespan. We give a sharp threshold on the value of d for which the complexity of the problem changes from polynomial

Preemptive scheduling of independent jobs on identical parallel machines subject to migration delays

NARCIS (Netherlands)

Sevastyanov, S. V.; Sitters, R. A.; Fishkin, A.V.

2010-01-01

We present hardness and approximation results for the problem of preemptive scheduling of n independent jobs on m identical parallel machines subject to a migration delay d with the objective to minimize the makespan. We give a sharp threshold on the value of d for which the complexity of the

Erratum to "Scheduling of a two-machine flowshop with availability constraints on the first machine" [International Journal of Production Economics 99 (2006)

OpenAIRE

Rapine , Christophe

2013-01-01

International audience; In Allaoui H., Artiba A., Elmaghraby S.E., Riane F. Scheduling of a two-machine flowshop with availability constraints on the first machine. International Journal of Production Economics 99 (2006) two conditions of optimality for the Johnson sequence are given. We establish in this note that these conditions are false, under the resumable and the non-resumable case. We also point out two incorrect proofs and give evidence that the time complexity of their dynamic appro...

Consumer Nutrition Environments of Hospitals: An Exploratory Analysis Using the Hospital Nutrition Environment Scan for Cafeterias, Vending Machines, and Gift Shops, 2012

Science.gov (United States)

Sallis, James F.; Swartz, Michael D.; Hoelscher, Deanna M.; Peskin, Melissa F.

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 consumer nutrition environments of 39 hospitals in Southern California. Data were collected by visiting each facility once from February 2012 through May 2012. Results On average, hospitals achieved only 29%, 33%, and less than 1% of the total possible points for their cafeteria, vending machines, and gift shops sections, respectively; overall, hospitals scored 25% of the total possible points. Large facility size and contracted food service operations were associated with some healthy practices in hospital cafeterias, but we found no association between these variables and the sectional or overall nutrition composite scores. Conclusion The average consumer nutrition environment of hospitals in this sample was minimally conducive to healthful eating. Nutrition-related interventions are warranted in hospital settings. PMID:23823699

Consumer nutrition environments of hospitals: an exploratory analysis using the Hospital Nutrition Environment Scan for Cafeterias, Vending Machines, and Gift Shops, 2012.

Science.gov (United States)

Winston, Courtney P; Sallis, James F; Swartz, Michael D; Hoelscher, Deanna M; Peskin, Melissa F

2013-07-03

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. This study used the Hospital Nutrition Environment Scan for Cafeterias, Vending Machines, and Gift Shops to quantitatively describe the consumer nutrition environments of 39 hospitals in Southern California. Data were collected by visiting each facility once from February 2012 through May 2012. On average, hospitals achieved only 29%, 33%, and less than 1% of the total possible points for their cafeteria, vending machines, and gift shops sections, respectively; overall, hospitals scored 25% of the total possible points. Large facility size and contracted food service operations were associated with some healthy practices in hospital cafeterias, but we found no association between these variables and the sectional or overall nutrition composite scores. The average consumer nutrition environment of hospitals in this sample was minimally conducive to healthful eating. Nutrition-related interventions are warranted in hospital settings.

On-line scheduling on a single machine : maximizing the number of early jobs

NARCIS (Netherlands)

Hoogeveen, J.A.; Potts, C.N.; Woeginger, G.J.

2000-01-01

This note deals with the scheduling problem of maximizing the number of early jobs on a single machine. We investigate the on-line version of this problem in the Preemption-Restart model. This means that jobs may be preempted, but preempting results in all the work done on this job so far being

Plans for miniature machining at LASL

International Nuclear Information System (INIS)

Rhorer, R.L.

1979-01-01

A special shop for making miniature or very small parts is being established within the LASL Shop Department, and one of the machine tools for this shop is a high precision lathe. The report describes a method based on scale modeling analysis which was used to define the specific requirements for this lathe

An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

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.

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

Science.gov (United States)

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.

Efficient Hybrid Genetic Based Multi Dimensional Host Load Aware Algorithm for Scheduling and Optimization of Virtual Machines

OpenAIRE

Thiruvenkadam, T; Karthikeyani, V

2014-01-01

Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...

Machining of uranium and uranium alloys

International Nuclear Information System (INIS)

Morris, T.O.

1981-01-01

Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

Learning Dispatching Rules for Scheduling: A Synergistic View Comprising Decision Trees, Tabu Search and Simulation

Directory of Open Access Journals (Sweden)

Atif Shahzad

2016-02-01

Full Text Available A promising approach for an effective shop scheduling that synergizes the benefits of the combinatorial optimization, supervised learning and discrete-event simulation is presented. Though dispatching rules are in widely used by shop scheduling practitioners, only ordinary performance rules are known; hence, dynamic generation of dispatching rules is desired to make them more effective in changing shop conditions. Meta-heuristics are able to perform quite well and carry more knowledge of the problem domain, however at the cost of prohibitive computational effort in real-time. The primary purpose of this research lies in an offline extraction of this domain knowledge using decision trees to generate simple if-then rules that subsequently act as dispatching rules for scheduling in an online manner. We used similarity index to identify parametric and structural similarity in problem instances in order to implicitly support the learning algorithm for effective rule generation and quality index for relative ranking of the dispatching decisions. Maximum lateness is used as the scheduling objective in a job shop scheduling environment.

Broadcast scheduling for mobile advertising

OpenAIRE

De Reyck, B.; Degraeve, Z.

2003-01-01

We describe a broadcast scheduling system developed for a precision marketing firm specialized in location-sensitive permission-based mobile advertising using SMS (Short Message Service) text messaging. Text messages containing advertisements were sent to registered customers when they were shopping in one of two shopping centers in the vicinity of London. The ads typically contained a limited-time promotional offer. The company's problem was deciding which ads to send out to which customers ...

Modification of structural graphite machining

International Nuclear Information System (INIS)

Lavrenev, M.M.

1979-01-01

Studied are machining procedures for structural graphites (GMZ, MG, MG-1, PPG) most widely used in industry, of the article mass being about 50 kg. Presented are dependences necessary for the calculation of cross sections of chip suction tappers and duster pipelines in machine shops for structural graphite machining

Unit-time scheduling problems with time dependent resources

NARCIS (Netherlands)

Tautenhahn, T.; Woeginger, G.

1997-01-01

We investigate the computational complexity of scheduling problems, where the operations consume certain amounts of renewable resources which are available in time-dependent quantities. In particular, we consider unit-time open shop problems and unit-time scheduling problems with identical parallel

A note on resource allocation scheduling with group technology and learning effects on a single machine

Science.gov (United States)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

Science.gov (United States)

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. PMID:24977204

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

Science.gov (United States)

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.

Machine en Theater. Ontwerpconcepten van winkelgebouwen

NARCIS (Netherlands)

Kooijman, D.C.

1999-01-01

Machine and Theater, Design Concepts for Shop Buildings is a richly illustrated study of the architectural and urban development of retail buildings, focusing on six essential shop types: the passage and the department store in particular in Germany and France in the nineteenth century; supermarkets

An evaluation of retrofit engineering control interventions to reduce perchloroethylene exposures in commercial dry-cleaning shops.

Science.gov (United States)

Earnest, G Scott; Ewers, Lynda M; Ruder, Avima M; Petersen, Martin R; Kovein, Ronald J

2002-02-01

Real-time monitoring was used to evaluate the ability of engineering control devices retrofitted on two existing dry-cleaning machines to reduce worker exposures to perchloroethylene. In one dry-cleaning shop, a refrigerated condenser was installed on a machine that had a water-cooled condenser to reduce the air temperature, improve vapor recovery, and lower exposures. In a second shop, a carbon adsorber was retrofitted on a machine to adsorb residual perchloroethylene not collected by the existing refrigerated condenser to improve vapor recovery and reduce exposures. Both controls were successful at reducing the perchloroethylene exposures of the dry-cleaning machine operator. Real-time monitoring was performed to evaluate how the engineering controls affected exposures during loading and unloading the dry-cleaning machine, a task generally considered to account for the highest exposures. The real-time monitoring showed that dramatic reductions occurred in exposures during loading and unloading of the dry-cleaning machine due to the engineering controls. Peak operator exposures during loading and unloading were reduced by 60 percent in the shop that had a refrigerated condenser installed on the dry-cleaning machine and 92 percent in the shop that had a carbon adsorber installed. Although loading and unloading exposures were dramatically reduced, drops in full-shift time-weighted average (TWA) exposures were less dramatic. TWA exposures to perchloroethylene, as measured by conventional air sampling, showed smaller reductions in operator exposures of 28 percent or less. Differences between exposure results from real-time and conventional air sampling very likely resulted from other uncontrolled sources of exposure, differences in shop general ventilation before and after the control was installed, relatively small sample sizes, and experimental variability inherent in field research. Although there were some difficulties and complications with installation and

JOB SHOP METHODOLOGY BASED ON AN ANT COLONY

Directory of Open Access Journals (Sweden)

OMAR CASTRILLON

2009-01-01

Full Text Available The purpose of this study is to reduce the total process time (Makespan and to increase the machines working time, in a job shop environment, using a heuristic based on ant colony optimization. This work is developed in two phases: The first stage describes the identification and definition of heuristics for the sequential processes in the job shop. The second stage shows the effectiveness of the system in the traditional programming of production. A good solution, with 99% efficiency is found using this technique.

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Directory of Open Access Journals (Sweden)

Weidong Lei

2017-01-01

Full Text Available We aim at solving the cyclic scheduling problem with a single robot and flexible processing times in a robotic flow shop, which is a well-known optimization problem in advanced manufacturing systems. The objective of the problem is to find an optimal robot move sequence such that the throughput rate is maximized. We propose a hybrid algorithm based on the Quantum-Inspired Evolutionary Algorithm (QEA and genetic operators for solving the problem. The algorithm integrates three different decoding strategies to convert quantum individuals into robot move sequences. The Q-gate is applied to update the states of Q-bits in each individual. Besides, crossover and mutation operators with adaptive probabilities are used to increase the population diversity. A repairing procedure is proposed to deal with infeasible individuals. Comparison results on both benchmark and randomly generated instances demonstrate that the proposed algorithm is more effective in solving the studied problem in terms of solution quality and computational time.

MODELING AND IMPLEMENTATION OF A DISTRIBUTED SHOP FLOOR MANAGEMENT AND CONTROL SYSTEM

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

Adopting distributed control architecture is the important development direction for shop floor management and control system,is also the requirement of making it agile,intelligent and concurrent. Some key problems in achieving distributed control architecture are researched. An activity model of shop floor is presented as the requirement definition of the prototype system. The multi-agent based software architecture is constructed. How the core part in shop floor management and control system,production plan and scheduling is achieved. The cooperation of different agents is illustrated. Finally,the implementation of the prototype system is narrated.

An effective PSO-based memetic algorithm for flow shop scheduling.

Science.gov (United States)

Liu, Bo; Wang, Ling; Jin, Yi-Hui

2007-02-01

This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic polynomial-time (NP) hard combinatorial optimization problem. In the proposed PSO-based MA (PSOMA), both PSO-based searching operators and some special local searching operators are designed to balance the exploration and exploitation abilities. In particular, the PSOMA applies the evolutionary searching mechanism of PSO, which is characterized by individual improvement, population cooperation, and competition to effectively perform exploration. On the other hand, the PSOMA utilizes several adaptive local searches to perform exploitation. First, to make PSO suitable for solving PFSSP, a ranked-order value rule based on random key representation is presented to convert the continuous position values of particles to job permutations. Second, to generate an initial swarm with certain quality and diversity, the famous Nawaz-Enscore-Ham (NEH) heuristic is incorporated into the initialization of population. Third, to balance the exploration and exploitation abilities, after the standard PSO-based searching operation, a new local search technique named NEH_1 insertion is probabilistically applied to some good particles selected by using a roulette wheel mechanism with a specified probability. Fourth, to enrich the searching behaviors and to avoid premature convergence, a simulated annealing (SA)-based local search with multiple different neighborhoods is designed and incorporated into the PSOMA. Meanwhile, an effective adaptive meta-Lamarckian learning strategy is employed to decide which neighborhood to be used in SA-based local search. Finally, to further enhance the exploitation ability, a pairwise-based local search is applied after the SA-based search. Simulation results based on benchmarks demonstrate the effectiveness

ProteinShop: A tool for interactive protein manipulation and steering

Energy Technology Data Exchange (ETDEWEB)

Crivelli, Silvia; Kreylos, Oliver; Max, Nelson; Hamann, Bernd; Bethel, Wes

2004-05-25

We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShop's use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.

Exploiting the ALICE HLT for PROOF by scheduling of Virtual Machines

International Nuclear Information System (INIS)

Meoni, Marco; Boettger, Stefan; Zelnicek, Pierre; Kebschull, Udo; Lindenstruth, Volker

2011-01-01

The HLT (High-Level Trigger) group of the ALICE experiment at the LHC has prepared a virtual Parallel ROOT Facility (PROOF) enabled cluster (HAF - HLT Analysis Facility) for fast physics analysis, detector calibration and reconstruction of data samples. The HLT-Cluster currently consists of 2860 CPU cores and 175TB of storage. Its purpose is the online filtering of the relevant part of data produced by the particle detector. However, data taking is not running continuously and exploiting unused cluster resources for other applications is highly desirable and improves the usage-cost ratio of the HLT cluster. As such, unused computing resources are dedicated to a PROOF-enabled virtual cluster available to the entire collaboration. This setup is especially aimed at the prototyping phase of analyses that need a high number of development iterations and a short response time, e.g. tuning of analysis cuts, calibration and alignment. HAF machines are enabled and disabled upon user request to start or complete analysis tasks. This is achieved by a virtual machine scheduling framework which dynamically assigns and migrates virtual machines running PROOF workers to unused physical resources. Using this approach we extend the HLT usage scheme to running both online and offline computing, thereby optimizing the resource usage.

JIT single machine scheduling problem with periodic preventive maintenance

Science.gov (United States)

Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani

2016-09-01

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.

Innovation prize for air-conditioned assembly shop - Constant temperature allows the assembly of high-precision machining centres; Innovationspreis fuer klimatisierte Montagehalle

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.

Hygiene of work in main shops of modern coking by-product industry. [USSR

Energy Technology Data Exchange (ETDEWEB)

Kapitul' skii, V B

1984-07-01

The hygiene of working conditions is evaluated and compared for coking by-product industry shops using modern technology and machines with those using obsolete equipment and methods. Most basic factors in contamination of atmosphere of coking, pitch-coking and metal-refining shops are coal and coke dust, carbon monoxide and polycyclic aromatic hydrocarbons, especially carcinogenic benzpyrene. Contamination of air of working zone is determined by details of technology: periodicity or continuity of industrial processes, use of improved equipment for smokeless injection of charge into stoves and of hermetic pipes to remove gas with hydraulically operated caps, position of machines in shops and in coal tar distillation removal of carcinogenic benzpyrene by sulfonation and aeration. In modernized shops of coking by-product industry, illness and loss of work capacity are significantly lower than in plants using obsolete methods and equipment. Measures are presented for hygienic improvement of working conditions; both methods to further increase efficiency of technological processes and methods to protect individual worker on job such as use of respirators, protective clothing, plexiglass shields, shampoos and skin creams. 14 references.

Staff Scheduling within the Retail Business in Denmark

DEFF Research Database (Denmark)

Leedgaard, Jesper; Mortensen, Kim H.; Larsen, Allan

2002-01-01

Staff Scheduling within the retail business deals with the assignment of employees such as shop assistants to work tasks so that the right number of employees are available at any given times and the total staff costs are minimized. In this paper the retail staff scheduling problem is formulated...... as a Mixed Integer Problem. The retail staff scheduling problem is solved using the metaheuristic {\\$\\backslash\\$it Simulated Annealing}. The heuristic is implemented by modifying the original MIP model. Some of the constraints defined in the MIP are relaxed, entered into the objective function and weighted...... according to their relative importance. The problem is then formulated as minimizing the overall constraint violation. A thorough parameter test has been applied to the developed heuristics. The developed system has successfully been implemented in a number of shops and stores in Denmark....

Integrated Job Scheduling and Network Routing

DEFF Research Database (Denmark)

Gamst, Mette; Pisinger, David

2013-01-01

We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number of resou...... indicate that the algorithm can be used as an actual scheduling algorithm in the Grid or as a tool for analyzing Grid performance when adding extra machines or jobs. © 2012 Wiley Periodicals, Inc.......We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...

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.

A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems

Directory of Open Access Journals (Sweden)

Cengiz Kahraman

2009-12-01

Full Text Available In this paper a new artificial immune system (AIS algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.

Doctor and pharmacy shopping for controlled substances.

Science.gov (United States)

Peirce, Gretchen L; Smith, Michael J; Abate, Marie A; Halverson, Joel

2012-06-01

Prescription drug abuse is a major health concern nationwide, with West Virginia having one of the highest prescription drug death rates in the United States. Studies are lacking that compare living subjects with persons who died from drug overdose for evidence of doctor and pharmacy shopping for controlled substances. The study objectives were to compare deceased and living subjects in West Virginia for evidence of prior doctor and pharmacy shopping for controlled substances and to identify factors associated with drug-related death. A secondary data study was conducted using controlled substance, Schedule II-IV, prescription data from the West Virginia Controlled Substance Monitoring Program and drug-related death data compiled by the Forensic Drug Database between July 2005 and December 2007. A case-control design compared deceased subjects 18 years and older whose death was drug related with living subjects for prior doctor and pharmacy shopping. Logistic regression identified factors related to the odds of drug-related death. A significantly greater proportion of deceased subjects were doctor shoppers (25.21% vs. 3.58%) and pharmacy shoppers (17.48% vs. 1.30%) than living subjects. Approximately 20.23% of doctor shoppers were also pharmacy shoppers, and 55.60% of pharmacy shoppers were doctor shoppers. Younger age, greater number of prescriptions dispensed, exposure to opioids and benzodiazepines, and doctor and pharmacy shopping were factors with greater odds of drug-related death. Doctor and pharmacy shopping involving controlled substances were identified, and shopping behavior was associated with drug-related death. Prescription monitoring programs may be useful in identifying potential shoppers at the point of care.

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times

Science.gov (United States)

Sharma, Pankaj; Jain, Ajai

2014-12-01

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.

Mechanisms for scheduling games with selfish players

NARCIS (Netherlands)

Hoeksma, R.P.

2015-01-01

Many challenges in operations research involve optimization. In particular, scheduling treats the optimal planning of tasks. This thesis focuses on machine scheduling models, where a number of tasks, called jobs, need to be scheduled on one or more machines. The outcome is determined by which job is

Aesthetic quality inference for online fashion shopping

Science.gov (United States)

Chen, Ming; Allebach, Jan

2014-03-01

On-line fashion communities in which participants post photos of personal fashion items for viewing and possible purchase by others are becoming increasingly popular. Generally, these photos are taken by individuals who have no training in photography with low-cost mobile phone cameras. It is desired that photos of the products have high aesthetic quality to improve the users' online shopping experience. In this work, we design features for aesthetic quality inference in the context of online fashion shopping. Psychophysical experiments are conducted to construct a database of the photos' aesthetic evaluation, specifically for photos from an online fashion shopping website. We then extract both generic low-level features and high-level image attributes to represent the aesthetic quality. Using a support vector machine framework, we train a predictor of the aesthetic quality rating based on the feature vector. Experimental results validate the efficacy of our approach. Metadata such as the product type are also used to further improve the result.

KASS v.2.2. scheduling software for construction

OpenAIRE

Krzemiński Michał

2016-01-01

The paper presents fourth version of specialist useful software in scheduling KASS v.2.2 (Algorithm Scheduling Krzeminski System). KASS software is designed for construction scheduling, specially form flow shop models. The program is being dedicated closely for the purposes of the construction. In distinguishing to other used programs in tasks of this type operational research criteria were designed closely with the thought about construction works and about the specificity of the building pr...

Opioid shopping behavior: how often, how soon, which drugs, and what payment method.

Science.gov (United States)

Cepeda, M Soledad; Fife, Daniel; Chow, Wing; Mastrogiovanni, Gregory; Henderson, Scott C

2013-01-01

Doctor shopping (obtaining opioid prescriptions from multiple prescribers) is one example of opioid abuse and diversion. The authors assessed how soon shopping behavior was observed after opioid exposure, number of events per shopper, preferred opioids, and method of payment. This was a cohort study. Individuals with ≤1 dispensing for any opioid in 2008 were followed for 18 months. Shopping behavior was defined as ≤2 prescriptions by different prescribers with ≤1 day of overlap and filled at ≤3 pharmacies. Of 25,161,024 subjects, 0.30% exhibited shopping behavior. Opioid-experienced subjects were 13.7 times more likely to exhibit shopping behavior and had more shopping episodes than opioid-naive subjects. Time to first shopping event was 246.90 ± 163.61 days. Number of episodes was 2.74 ± 4.66. Most subjects with shopping behavior (55.27%) had 1 shopping episode, whereas 9.52% had ≤6 episodes; 88.99% had ≤4 prescribers. Subjects with shopping behavior filled schedule II opioids more often than subjects without shopping behavior (19.51% vs 10.89%) and more often paid in cash (44.85% vs 18.54%). Three of 1000 people exposed to opioids exhibit shopping behavior, on average, 8 months after exposure. Opioid shoppers seek strong opioids, avoid combination products, often pay cash, and obtain prescriptions from few prescribers. © 2012 The Author(s).

Multi-objective problem of the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints

Science.gov (United States)

Amallynda, I.; Santosa, B.

2017-11-01

This paper proposes a new generalization of the distributed parallel machine and assembly scheduling problem (DPMASP) with eligibility constraints referred to as the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints. Within this generalization, we assume that there are a set non-identical factories or production lines, each one with a set unrelated parallel machine with different speeds in processing them disposed to a single assembly machine in series. A set of different products that are manufactured through an assembly program of a set of components (jobs) according to the requested demand. Each product requires several kinds of jobs with different sizes. Beside that we also consider to the multi-objective problem (MOP) of minimizing mean flow time and the number of tardy products simultaneously. This is known to be NP-Hard problem, is important to practice, as the former criterions to reflect the customer's demand and manufacturer's perspective. This is a realistic and complex problem with wide range of possible solutions, we propose four simple heuristics and two metaheuristics to solve it. Various parameters of the proposed metaheuristic algorithms are discussed and calibrated by means of Taguchi technique. All proposed algorithms are tested by Matlab software. Our computational experiments indicate that the proposed problem and fourth proposed algorithms are able to be implemented and can be used to solve moderately-sized instances, and giving efficient solutions, which are close to optimum in most cases.

Identical parallel machine scheduling with nonlinear deterioration and multiple rate modifying activities

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

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.

Construction schedules slack time minimizing

Science.gov (United States)

Krzemiński, Michał

2017-07-01

The article presents two copyright models for minimizing downtime working brigades. Models have been developed for construction schedules performed using the method of work uniform. Application of flow shop models is possible and useful for the implementation of large objects, which can be divided into plots. The article also presents a condition describing gives which model should be used, as well as a brief example of optimization schedule. The optimization results confirm the legitimacy of the work on the newly-developed models.

Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

Science.gov (United States)

Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping

2012-05-01

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

Project orie:nta.teci pla.:n:ni:ng, scheduling a.:nci controlling technique

African Journals Online (AJOL)

Review Technique. By October 1958 it ... (CPM) to schedule and control a very large project. and during the ... objectives are identified and the total job is broken down into ..... jobs in a single shop or shops in the plant, to scheduf- ing plants ...

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.

Reliability of the hospital nutrition environment scan for cafeterias, vending machines, and gift shops.

Science.gov (United States)

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. Copyright © 2013 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

A genetic algorithm for preemptive scheduling of a single machine

Directory of Open Access Journals (Sweden)

Amir-Mohammad Golmohammadi

2016-09-01

Full Text Available This paper presents a mathematical model for scheduling of a single machine when there are preemptions in jobs. The primary objective of the study is to minimize different objectives such as earliness, tardiness and work in process. The proposed mathematical problem is considered as NP-Hard and the optimal solution is available for small scale problems. Therefore, a genetic algorithm (GA is developed to solve the problem for large-scale problems. The implementation of the proposed model is compared with GA for problems with up to 50 jobs using three methods of roulette wheel sampling, random sampling and competition sampling. The results have indicated that competition sampling has reached optimal solutions for small scale problems and it could obtain better near-optimal solutions in relatively lower running time compared with other sampling methods.

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2014-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2016-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, H.; Skutella, M.; Woeginger, Gerhard

2003-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, J.A.; Skutella, M.; Woeginger, G.J.; Paterson, M.

2000-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

PENJADWALAN FLOWSHOP MENGGUNAKAN ALGORITMA NAWAZ ENSCORE HAM

Directory of Open Access Journals (Sweden)

Ilyas Masudin

2014-06-01

Full Text Available This article attempts to schedule flow shop production using Nawaz Enscore Ham (NEH to schedule jobs machining. The objective of this paper is to minimize total makespan which could reduce total production costs. This paper is based on the case study where NEH is applied in scheduling jobs in machines and then compared with the existing machine’s scheduling. The algorithm of NEH is also used to reduce idle time of machines so that the utility or performances of the machine are maintained.  The results of NEH simulation indicate that by applying NEH algorithm to scheduling machines for 10 jobs and 5 machines can reduce 2.5 per cent or 118 minutes of completing time of jobs. It also decreases total idle time of machines about 582 minutes compared with the existing scheduling.

PENJADWALAN FLOWSHOP MENGGUNAKAN ALGORITMA NAWAZ ENSCORE HAM

Directory of Open Access Journals (Sweden)

Ilyas Masudin

2014-06-01

Full Text Available This article attempts to schedule flow shop production using Nawaz Enscore Ham (NEH to schedule jobs machining. The objective of this paper is to minimize total makespan which could reduce total production costs. This paper is based on the case study where NEH is applied in scheduling jobs in machines and then compared with the existing machine’s scheduling. The algorithm of NEH is also used to reduce idle time of machines so that the utility or performances of the machine are maintained. The results of NEH simulation indicate that by applying NEH algorithm to scheduling machines for 10 jobs and 5 machines can reduce 2.5 per cent or 118 minutes of completing time of jobs. It also decreases total idle time of machines about 582 minutes compared with the existing scheduling.

A combined experimental and numerical study on upper airway dosimetry of inhaled nanoparticles from an electrical discharge machine shop.

Science.gov (United States)

Tian, Lin; Shang, Yidan; Chen, Rui; Bai, Ru; Chen, Chunying; Inthavong, Kiao; Tu, Jiyuan

2017-07-12

Exposure to nanoparticles in the workplace is a health concern to occupational workers with increased risk of developing respiratory, cardiovascular, and neurological disorders. Based on animal inhalation study and human lung tumor risk extrapolation, current authoritative recommendations on exposure limits are either on total mass or number concentrations. Effects of particle size distribution and the implication to regional airway dosages are not elaborated. Real time production of particle concentration and size distribution in the range from 5.52 to 98.2 nm were recorded in a wire-cut electrical discharge machine shop (WEDM) during a typical working day. Under the realistic exposure condition, human inhalation simulations were performed in a physiologically realistic nasal and upper airway replica. The combined experimental and numerical study is the first to establish a realistic exposure condition, and under which, detailed dose metric studies can be performed. In addition to mass concentration guided exposure limit, inhalation risks to nano-pollutant were reexamined accounting for the actual particle size distribution and deposition statistics. Detailed dosimetries of the inhaled nano-pollutants in human nasal and upper airways with respect to particle number, mass and surface area were discussed, and empirical equations were developed. An astonishing enhancement of human airway dosages were detected by current combined experimental and numerical study in the WEDM machine shop. Up to 33 folds in mass, 27 folds in surface area and 8 folds in number dosages were detected during working hours in comparison to the background dosimetry measured at midnight. The real time particle concentration measurement showed substantial emission of nano-pollutants by WEDM machining activity, and the combined experimental and numerical study provided extraordinary details on human inhalation dosimetry. It was found out that human inhalation dosimetry was extremely sensitive

31. Introduction with adjacent production of foundry and rolling department of electrolysis shop

International Nuclear Information System (INIS)

Ivanov, A.V.

1993-01-01

The introduction with adjacent production of foundry and rolling department of electrolysis shop was conducted. The foundry machine was described. The chemical properties of aluminium for ferrous alloy production were defined.

Science Shops

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....

Trustable Virtual Machine Scheduling in a Cloud

OpenAIRE

Hermenier , Fabien; Henrio , Ludovic

2017-01-01

International audience; In an Infrastructure As A Service (IaaS) cloud, the scheduler deploys VMs to servers according to service level objectives (SLOs). Clients and service providers must both trust the infrastructure. In particular they must be sure that the VM scheduler takes decisions that are consistent with its advertised behaviour. The difficulties to master every theoretical and practical aspects of a VM scheduler implementation leads however to faulty behaviours that break SLOs and ...

An efficient genetic algorithm for a hybrid flow shop scheduling problem with time lags and sequence-dependent setup time

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.

Avaliação de regras de sequenciamento da produção em ambientes Job shop e Flow shop por meio de simulação computacional

Directory of Open Access Journals (Sweden)

Edna Barbosa da Silva

2012-01-01

Full Text Available In this work, the computational simulation is employed to study the effects of production sequencing rules in the performance of Job shop and Flow shop manufacturing environments. Eight sequencing rules were considered: SIPT (Shortest Imminent Processing Time, EDD (Earliest Due Date, DLS (Dynamic Least Slack, LWQ (Least Work in next Queue, FIFO (First In First Out, LIFO (Last In Last Out, CR (Critical Ratio and LS (Least Slack. These different sequencing rules were evaluated in relation to the makespan, total tardiness and number of tardy jobs, considering an experimental scenario which includes two configurations with eight machines (processes and ten different types of orders. A simulation model was developed with Arena software, incorporating randomness of order arrivals and the production times in such environments. The results show that the EDD and SIPT rules presented the best performances in the Job shop and in the Flow shop environments, respectively.

Marriage in Honey Bees Optimization Algorithm for Flow-shop Problems

Directory of Open Access Journals (Sweden)

Pedro PALOMINOS

2012-01-01

Full Text Available The objective of this work is to make a comparative study of the Marriage in Honeybees Op-timization (MBO metaheuristic for flow-shop scheduling problems. This paper is focused on the design possibilities of the mating flight space shared by queens and drones. The proposed algorithm uses a 2-dimensional torus as an explicit mating space instead of the simulated an-nealing one in the original MBO. After testing different alternatives with benchmark datasets, the results show that the modeled and implemented metaheuristic is effective to solve flow-shop type problems, providing a new approach to solve other NP-Hard problems.

Eyes Wide Shopped: Shopping Situations Trigger Arousal in Impulsive Buyers

Science.gov (United States)

Serfas, Benjamin G.; Büttner, Oliver B.; Florack, Arnd

2014-01-01

The present study proposes arousal as an important mechanism driving buying impulsiveness. We examined the effect of buying impulsiveness on arousal in non-shopping and shopping contexts. In an eye-tracking experiment, we measured pupil dilation while participants viewed and rated pictures of shopping scenes and non-shopping scenes. The results demonstrated that buying impulsiveness is closely associated with arousal as response to viewing pictures of shopping scenes. This pertained for hedonic shopping situations as well as for utilitarian shopping situations. Importantly, the effect did not emerge for non-shopping scenes. Furthermore, we demonstrated that arousal of impulsive buyers is independent from cognitive evaluation of scenes in the pictures. PMID:25489955

Eyes wide shopped: shopping situations trigger arousal in impulsive buyers.

Science.gov (United States)

Serfas, Benjamin G; Büttner, Oliver B; Florack, Arnd

2014-01-01

The present study proposes arousal as an important mechanism driving buying impulsiveness. We examined the effect of buying impulsiveness on arousal in non-shopping and shopping contexts. In an eye-tracking experiment, we measured pupil dilation while participants viewed and rated pictures of shopping scenes and non-shopping scenes. The results demonstrated that buying impulsiveness is closely associated with arousal as response to viewing pictures of shopping scenes. This pertained for hedonic shopping situations as well as for utilitarian shopping situations. Importantly, the effect did not emerge for non-shopping scenes. Furthermore, we demonstrated that arousal of impulsive buyers is independent from cognitive evaluation of scenes in the pictures.

Meta-heuristic algorithms for parallel identical machines scheduling problem with weighted late work criterion and common due date.

Science.gov (United States)

Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie

2015-01-01

To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA.

Analysis of performance measures to handle medical E-commerce shopping cart abandonment in cloud

Directory of Open Access Journals (Sweden)

Vedhanayagam Priya

Full Text Available The E-commerce zone is crowded with many Internet users. Medical E-commerce has had significant growth in part because of a great deal of growth in the Indian E-commerce field. Medical E-commerce sites use cloud computing to guarantee a high quality of service anywhere and anytime in the world. For online access, the customer's expectations are very high. Medical E-commerce retailers are directed towards cloud service providers based on their quality of service. During online shopping, impatient customers may abandon a specific medical E-commerce shopping cart due to slow response. This is quite difficult to endure for a medical E-commerce firm. The research described herein observed the effect of shopping cart abandonment on medical E-commerce websites deployed in cloud computing. The impact of the idle virtual machine on customer impatience during medical E-commerce shopping was also studied. The ultimate aim of this study was to propose a stochastic queueing model and to yield results through probability generating functions. The results of the model may be highly useful for a medical E-commerce firm facing customer impatience, so as to design its service system to offer satisfactory quality of service. Keywords: Cloud computing, Queueing, Virtual machine, E-commerce, Cart abandonment, Quality of Service

Eyes wide shopped: shopping situations trigger arousal in impulsive buyers.

Directory of Open Access Journals (Sweden)

Benjamin G Serfas

Full Text Available The present study proposes arousal as an important mechanism driving buying impulsiveness. We examined the effect of buying impulsiveness on arousal in non-shopping and shopping contexts. In an eye-tracking experiment, we measured pupil dilation while participants viewed and rated pictures of shopping scenes and non-shopping scenes. The results demonstrated that buying impulsiveness is closely associated with arousal as response to viewing pictures of shopping scenes. This pertained for hedonic shopping situations as well as for utilitarian shopping situations. Importantly, the effect did not emerge for non-shopping scenes. Furthermore, we demonstrated that arousal of impulsive buyers is independent from cognitive evaluation of scenes in the pictures.

Machine en Theater. Ontwerpconcepten van winkelgebouwen

OpenAIRE

Kooijman, D.C.

1999-01-01

Machine and Theater, Design Concepts for Shop Buildings is a richly illustrated study of the architectural and urban development of retail buildings, focusing on six essential shop types: the passage and the department store in particular in Germany and France in the nineteenth century; supermarkets and malls and their relation to the suburbanisation and the emerging car use; and the peripheral retail park and location-free virtual store as the most recent developments. On the basis of a larg...

Shopping intention prediction using decision trees

Directory of Open Access Journals (Sweden)

Dario Šebalj

2017-09-01

Full Text Available Introduction: The price is considered to be neglected marketing mix element due to the complexity of price management and sensitivity of customers on price changes. It pulls the fastest customer reactions to that change. Accordingly, the process of making shopping decisions can be very challenging for customer. Objective: The aim of this paper is to create a model that is able to predict shopping intention and classify respondents into one of the two categories, depending on whether they intend to shop or not. Methods: Data sample consists of 305 respondents, who are persons older than 18 years involved in buying groceries for their household. The research was conducted in February 2017. In order to create a model, the decision trees method was used with its several classification algorithms. Results: All models, except the one that used RandomTree algorithm, achieved relatively high classification rate (over the 80%. The highest classification accuracy of 84.75% gave J48 and RandomForest algorithms. Since there is no statistically significant difference between those two algorithms, authors decided to choose J48 algorithm and build a decision tree. Conclusions: The value for money and price level in the store were the most significant variables for classification of shopping intention. Future study plans to compare this model with some other data mining techniques, such as neural networks or support vector machines since these techniques achieved very good accuracy in some previous research in this field.

Simulation models generator. Applications in scheduling

Directory of Open Access Journals (Sweden)

Omar Danilo Castrillón

2013-08-01

Rev.Mate.Teor.Aplic. (ISSN 1409-2433 Vol. 20(2: 231–241, July 2013 generador de modelos de simulacion 233 will, in order to have an approach to reality to evaluate decisions in order to take more assertive. To test prototype was used as the modeling example of a production system with 9 machines and 5 works as a job shop configuration, testing stops processing times and stochastic machine to measure rates of use of machines and time average jobs in the system, as measures of system performance. This test shows the goodness of the prototype, to save the user the simulation model building

M-machine SDST flow shop scheduling using modified heuristic ...

African Journals Online (AJOL)

AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners · Terms and Conditions of Use · Contact AJOL · News. OTHER RESOURCES... for Researchers · for Journals · for Authors · for Policy Makers · about Open Access · Journal Quality.

A review of lot streaming in a flow shop environment with makespan criteria

Directory of Open Access Journals (Sweden)

Pedro Gómez-Gasquet

2013-07-01

Full Text Available Purpose: This paper reviews current literature and contributes a set of findings that capture the current state-of-the-art of the topic of lot streaming in a flow-shop. Design/methodology/approach: A literature review to capture, classify and summarize the main body of knowledge on lot streaming in a flow-shop with makespan criteria and, translate this into a form that is readily accessible to researchers and practitioners in the more mainstream production scheduling community. Findings and Originality/value: The existing knowledge base is somewhat fragmented. This is a relatively unexplored topic within mainstream operations management research and one which could provide rich opportunities for further exploration. Originality/value: This paper sets out to review current literature, from an advanced production scheduling perspective, and contributes a set of findings that capture the current state-of-the-art of this topic.

An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

Science.gov (United States)

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%.

An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

International Nuclear Information System (INIS)

Yusriski, R; Sukoyo; Samadhi, T M A A; Halim, A H

2016-01-01

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%. (paper)

Finding Worst-Case Flexible Schedules using Coevolution

DEFF Research Database (Denmark)

Jensen, Mikkel Thomas

2001-01-01

Finding flexible schedules is important to industry, since in many environments changes such as machine breakdowns or the appearance of new jobs can happen at short notice.......Finding flexible schedules is important to industry, since in many environments changes such as machine breakdowns or the appearance of new jobs can happen at short notice....

Online Scheduling in Manufacturing A Cumulative Delay Approach

CERN Document Server

Suwa, Haruhiko

2013-01-01

Online scheduling is recognized as the crucial decision-making process of production control at a phase of “being in production" according to the released shop floor schedule. Online scheduling can be also considered as one of key enablers to realize prompt capable-to-promise as well as available-to-promise to customers along with reducing production lead times under recent globalized competitive markets. Online Scheduling in Manufacturing introduces new approaches to online scheduling based on a concept of cumulative delay. The cumulative delay is regarded as consolidated information of uncertainties under a dynamic environment in manufacturing and can be collected constantly without much effort at any points in time during a schedule execution. In this approach, the cumulative delay of the schedule has the important role of a criterion for making a decision whether or not a schedule revision is carried out. The cumulative delay approach to trigger schedule revisions has the following capabilities for the ...

A Distributed Particle Swarm Optimization Zlgorithmfor Flexible Job-hop Scheduling Problem

Directory of Open Access Journals (Sweden)

LIU Sheng--hui

2017-06-01

Full Text Available According to the characteristics of the Flexible job shop scheduling problem the minimum makespan as measures we proposed a distributed particle swarm optimization algorithm aiming to solve flexible job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi agent particle swarm optimization model in this algorithm it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the FJSP and it also verified the reasonableness of the multi}gent particle swarm optimization model.

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.

Gold-decorated shopping centre; Golddekoriertes Shopping Center

Energy Technology Data Exchange (ETDEWEB)

Altmannshofer, Robert

2010-11-15

In the autumn 2009, the German quality seal sustainable construction for commercial new buildings was introduced. Thus, owners and operators of retail real estate and shopping centres can make clear their commitment in the matter of sustainability. The Ernst-August-Galerie (Hanover, Federal Republic of Germany) developed and operated by ECE Projektmanagement GmbH and Co. KG (Hamburg, Federal Republic of Germany) was a pilot project and also the first gold in one. With its around 150 shops, the Ernst-August-Galerie offers a supermarket, fashion outlets, a food court, service outlets and restaurants/cafes. The spacious and elegantly designed shopping mall with its piazzas and light-flooded rotundas exudes a Mediterranean air, making it a high-quality venue for shopping, strolling and leisure activities.

Doctor shopping: a concept analysis.

Science.gov (United States)

Worley, Julie; Hall, Joanne M

2012-01-01

Prescription drug abuse is a significant problem in the United States that poses a serious health risk to Americans and is therefore significant to the field of nursing. The prescription drugs that are designated in the United States as having abuse potential are called controlled or scheduled drugs. The most common types of abused prescription drugs are benzodiazepines prescribed for anxiety, opioids prescribed for pain, and stimulants prescribed for attention deficit disorder. These prescription drugs are abused by taking larger doses than prescribed for nonmedical use to achieve a high or euphoric feeling, or are sold illicitly for profit. In 2009, there were 2.4 million nonmedical users of prescription opioids in the United States. These prescription drugs are often obtained by seeing multiple prescribers, often under false pretenses or with complicity from the prescribers that leads to abuse and illicit sales. The term doctor shopping has been used not only to refer to this phenomenon but has also had other meanings throughout the past decades. Thus, concept analysis is the focus of this article for clarification using the Walker and Avant method. Health implications and suggestions for minimizing doctor shopping are included.

Comparison Shopping Agents and Czech Online Customers’ Shopping Behaviour

Directory of Open Access Journals (Sweden)

Pilik Michal

2016-12-01

Full Text Available The internet has changed the lifestyles and shopping behaviours of customers. Online purchasing enables people to obtain information about products and services provided more effectively and easily, with the result that home shopping has become ordinary and usual. This paper presents part of a research focusing on online shopping customers’ behaviour in the Czech Republic. The article pertains to comparison shopping agents (CPAs, a tool which provides information to customers and helps find the best offer. The research was conducted on the basis of an online questionnaire available on an internet web page. The main results confirmed a dependency between online purchasing and the use of shopping agents, which are very popular in the Czech Republic. Almost two-thirds of online shoppers use CPAs when they engage in internet shopping. The final part of the paper addresses references and customers’ reviews as an important factor for the selection of online retailer.

QUALITY THROUGH INTEGRATION OF PRODUCTION AND SHOP FLOOR MANAGEMENT BY DISCRETE EVENT SIMULATION

Directory of Open Access Journals (Sweden)

Zoran Mirović

2007-06-01

Full Text Available With the intention to integrate strategic and tactical decision making and develop the capability of plans and schedules reconfiguration and synchronization in a very short cycle time many firms have proceeded to the adoption of ERP and Advanced Planning and Scheduling (APS technologies. The final goal is a purposeful scheduling system that guide in the right direction the current, high priority needs of the shop floor while remaining consistent with long-term production plans. The difference, and the power, of Discrete-Event Simulation (DES is its ability to mimic dynamic manufacturing systems, consisting of complex structures, and many heterogeneous interacting components. This paper describes such an integrated system (ERP/APS/DES and draw attention to the essential role of simulation based scheduling within it.

Approximating Preemptive Stochastic Scheduling

OpenAIRE

Megow Nicole; Vredeveld Tjark

2009-01-01

We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

Shopping Centres and Selected Aspects of Shopping Behaviour (Brno, the Czech Republic)

Czech Academy of Sciences Publication Activity Database

Kunc, J.; Tonev, P.; Szczyrba, Z.; Frantál, Bohumil

2012-01-01

Roč. 7, č. 2 (2012), s. 39-51 ISSN 2065-4421 Institutional support: RVO:68145535 Keywords : shopping centres * shopping habits * commuting to retail shops Subject RIV: AO - Sociology, Demography http://technicalgeography.org/pdf/2_2012/05_josef_kunc_petr_tonev_zdenek_szczyrba_bohumil_frantal_shopping_centres_and_selected_aspects_of_shopping_behaviour.pdf

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

Science.gov (United States)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

How useful are preemptive schedules?

NARCIS (Netherlands)

Brucker, P.; Heitmann, S.; Hurink, J.L.

2001-01-01

Machine scheduling admits two options to process jobs. In a preemptive mode processing may be interrupted and resumed later even on a different machine. In a nonpreemptive mode interruptions are not allowed. Usually, the possibility to preempt jobs leads to better performance values. However, also

Two-MILP models for scheduling elective surgeries within a private healthcare facility.

Science.gov (United States)

Khlif Hachicha, Hejer; Zeghal Mansour, Farah

2016-11-05

This paper deals with an Integrated Elective Surgery-Scheduling Problem (IESSP) that arises in a privately operated healthcare facility. It aims to optimize the resource utilization of the entire surgery process including pre-operative, per-operative and post-operative activities. Moreover, it addresses a specific feature of private facilities where surgeons are independent service providers and may conduct their surgeries in different private healthcare facilities. Thus, the problem requires the assignment of surgery patients to hospital beds, operating rooms and recovery beds as well as their sequencing over a 1-day period while taking into account surgeons' availability constraints. We present two Mixed Integer Linear Programs (MILP) that model the IESSP as a three-stage hybrid flow-shop scheduling problem with recirculation, resource synchronization, dedicated machines, and blocking constraints. To assess the empirical performance of the proposed models, we conducted experiments on real-world data of a Tunisian private clinic: Clinique Ennasr and on randomly generated instances. Two criteria were minimised: the patients' average length of stay and the number of patients' overnight stays. The computational results show that the proposed models can solve instances with up to 44 surgical cases in a reasonable CPU time using a general-purpose MILP solver.

The finite horizon economic lot sizing problem in job shops : the multiple cycle approach

NARCIS (Netherlands)

Ouenniche, J.; Bertrand, J.W.M.

2001-01-01

This paper addresses the multi-product, finite horizon, static demand, sequencing, lot sizing and scheduling problem in a job shop environment where the planning horizon length is finite and fixed by management. The objective pursued is to minimize the sum of setup costs, and work-in-process and

ShopComm: Community-Supported Online Shopping for Older Adults.

Science.gov (United States)

Gorkovenko, Katerina; Tigwell, Garreth W; Norrie, Christopher S; Waite, Miriam; Herron, Daniel

2017-01-01

The United Kingdom has an ageing population whose members experience significant life transitions as they grow older, for example, losing mobility due to deteriorating health. For these adults, digital technology has the potential to sustain their independence and improve their quality of life. However older adults can be reluctant to use digital solutions. In this paper, we review a local charity providing a grocery shopping service for older adults who are unable to go themselves. We explore how older adults perceive the benefits and drawbacks of both physical and digital shopping. Using these insights, we designed ShopComm to enable and support older adults with mobility impairments to shop online.

Split Scheduling with Uniform Setup Times

NARCIS (Netherlands)

Schalekamp, F.; Sitters, R.A.; van der Ster, S.L.; Stougie, L.; Verdugo, V.; van Zuylen, A.

2015-01-01

We study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a machine cannot process or

An Evaluation of Parallel Job Scheduling for ASCI Blue-Pacific

International Nuclear Information System (INIS)

Franke, H.; Jann, J.; Moreira, J.; Pattnaik, P.; Jette, M.

1999-01-01

In this paper we analyze the behavior of a gang-scheduling strategy that we are developing for the ASCI Blue-Pacific machines. Using actual job logs for one of the ASCI machines we generate a statistical model of the current workload with hyper Erlang distributions. We then vary the parameters of those distributions to generate various workloads, representative of different operating points of the machine. Through simulation we obtain performance parameters for three different scheduling strategies: (i) first-come first-serve, (ii) gang-scheduling, and (iii) backfilling. Our results show that backfilling, can be very effective for the common operating points in the 60-70% utilization range. However, for higher utilization rates, time-sharing techniques such as gang-scheduling offer much better performance

WUppaal:

DEFF Research Database (Denmark)

Fogh, Peter; Cano Hald, Thomas; Nielsen, Brian

2016-01-01

that provides formal verification of timed automata using the Uppaal model-checker. WUppaal provides easy access to a large amount of resources through a RESTful API. Through a machine-to-machine use case on a job shop scheduling application, we show the practical use of WUPPAAL. Our benchmark shows...

Machine Shop. Module 8: CNC (Computerized Numerical Control). Instructor's Guide.

Science.gov (United States)

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…

Omni channel fashion shopping

NARCIS (Netherlands)

Kemperman, A.D.A.M.; van Delft, L.; Borgers, A.W.J.; Pantano, E.

2015-01-01

This chapter gives insight into consumers' online and offline fashion shopping behavior, consumers' omni-channel usage during the shopping process, and consumer fashion shopper segments. Based on a literature review, omni-channel shopping behavior during the shopping process was operationalized.

Interval selection with machine-dependent intervals

OpenAIRE

Bohmova K.; Disser Y.; Mihalak M.; Widmayer P.

2013-01-01

We study an offline interval scheduling problem where every job has exactly one associated interval on every machine. To schedule a set of jobs, exactly one of the intervals associated with each job must be selected, and the intervals selected on the same machine must not intersect.We show that deciding whether all jobs can be scheduled is NP-complete already in various simple cases. In particular, by showing the NP-completeness for the case when all the intervals associated with the same job...

A fine-grained parallel algorithm for the cyclic flexible job shop problem

Directory of Open Access Journals (Sweden)

Bożejko Wojciech

2017-06-01

Full Text Available In this paper there is considered a flexible job shop problem of operations scheduling. The new, very fast method of determination of cycle time is presented. In the design of heuristic algorithm there was the neighborhood inspired by the game of golf applied. Lower bound of the criterion function was used in the search of the neighborhood.

The power of reordering for online minimum makespan scheduling

OpenAIRE

Englert, Matthias; Özmen, Deniz; Westermann, Matthias

2014-01-01

In the classic minimum makespan scheduling problem, we are given an input sequence of jobs with processing times. A scheduling algorithm has to assign the jobs to m parallel machines. The objective is to minimize the makespan, which is the time it takes until all jobs are processed. In this paper, we consider online scheduling algorithms without preemption. However, we do not require that each arriving job has to be assigned immediately to one of the machines. A reordering buffer with limited...

Environment-Aware Production Schedulingfor Paint Shops in Automobile Manufacturing: A Multi-Objective Optimization Approach.

Science.gov (United States)

Zhang, Rui

2017-12-25

The traditional way of scheduling production processes often focuses on profit-driven goals (such as cycle time or material cost) while tending to overlook the negative impacts of manufacturing activities on the environment in the form of carbon emissions and other undesirable by-products. To bridge the gap, this paper investigates an environment-aware production scheduling problem that arises from a typical paint shop in the automobile manufacturing industry. In the studied problem, an objective function is defined to minimize the emission of chemical pollutants caused by the cleaning of painting devices which must be performed each time before a color change occurs. Meanwhile, minimization of due date violations in the downstream assembly shop is also considered because the two shops are interrelated and connected by a limited-capacity buffer. First, we have developed a mixed-integer programming formulation to describe this bi-objective optimization problem. Then, to solve problems of practical size, we have proposed a novel multi-objective particle swarm optimization (MOPSO) algorithm characterized by problem-specific improvement strategies. A branch-and-bound algorithm is designed for accurately assessing the most promising solutions. Finally, extensive computational experiments have shown that the proposed MOPSO is able to match the solution quality of an exact solver on small instances and outperform two state-of-the-art multi-objective optimizers in literature on large instances with up to 200 cars.

ATTITUDES TOWARD ONLINE SHOPPING FROM THE ASPECTS OF PERSONAL CHARACTERISTICS AND SHOPPING MOTIVE THROUGH A DEVELOPING CONCEPT: PRIVATE SHOPPING

OpenAIRE

BAYBARS, Miray; USTUNDAGLI, Elif

2011-01-01

Private shopping is one of the concepts that serve as a members-only online shopping platform with deep discounts and well-known brands. The aim of this paper is to determine whether consumers’ need for uniqueness and innovativeness as a personal trait and price discount orientation affect consumer attitudes toward private shopping and their purchase decision or not. Research results revealed that need for uniqueness and innovativeness affect positive attitudes towards private shopping positi...

Cyclic delivery scheduling to customers with different priorities

Directory of Open Access Journals (Sweden)

Katarzyna Zofia Gdowska

2013-12-01

Full Text Available Background: In this paper a cyclic delivery scheduling problem for customers with different priorities is presented. Shops, which are provided with deliveries, are occasionally located in places which are crucial for the proper flow of traffic. In such places coordination of deliveries is crucial; therefore it allows to completely eliminate the phenomenon of the simultaneous arrivals of suppliers. Methods: In this paper the cyclic delivery scheduling problem for customers with different priorities was presented. To this theoretical problem a mix integer programming model was developed. Specific approach to the cyclic delivery scheduling problem is inspired by timetabling problem for urban public transport. Results: Mixed integer programming model was employed for solving four cases of cyclic delivery scheduling problem for customers with different priorities. When the value of the synchronization priority assigned to a single customer raised then the total number of synchronizations in the whole network decreased. In order to compare solutions a synchronization rate was utilized. A simple factor was utilized - the proportion of number of synchronizations of deliveries to a given customer to the total number of synchronizations obtained for the whole network. When the value of synchronization priority raised then the value of synchronization rate of this customer improved significantly. Conclusions: The mixed integer programming model for the cyclic delivery scheduling problem for customers with different priorities presented in this paper can be utilized for generating schedules of serving customers located in places where only one delivery can be received and unloaded at one go and where there is no space for other suppliers to wait in a queue. Such a schedule can be very useful for organizing deliveries to small shops united in a franchising network, since they operate in a way that is very similar to the network presented in this paper

An Extended Flexible Job Shop Scheduling Model for Flight Deck Scheduling with Priority, Parallel Operations, and Sequence Flexibility

Directory of Open Access Journals (Sweden)

Lianfei Yu

2017-01-01

Full Text Available Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.

MANUFACTURING PROCESS FUNCTIONS--I. AN ALTERNATIVE MODEL AND ITS COMPARISON WITH EXISTING FUNCTIONS (AND)II. SELECTION OF TRAINEES AND CONTROL OF THEIR PROGRESS.

Science.gov (United States)

GLOVER, J.H.

THE CHIEF OBJECTIVE OF THIS STUDY OF SPEED-SKILL ACQUISITION WAS TO FIND A MATHEMATICAL MODEL CAPABLE OF SIMPLE GRAPHIC INTERPRETATION FOR INDUSTRIAL TRAINING AND PRODUCTION SCHEDULING AT THE SHOP FLOOR LEVEL. STUDIES OF MIDDLE SKILL DEVELOPMENT IN MACHINE AND VEHICLE ASSEMBLY, AIRCRAFT PRODUCTION, SPOOLMAKING AND THE MACHINING OF PARTS CONFIRMED…

A synergetic combination of small and large neighborhood schemes in developing an effective procedure for solving the job shop scheduling problem.

Science.gov (United States)

Amirghasemi, Mehrdad; Zamani, Reza

2014-01-01

This paper presents an effective procedure for solving the job shop problem. Synergistically combining small and large neighborhood schemes, the procedure consists of four components, namely (i) a construction method for generating semi-active schedules by a forward-backward mechanism, (ii) a local search for manipulating a small neighborhood structure guided by a tabu list, (iii) a feedback-based mechanism for perturbing the solutions generated, and (iv) a very large-neighborhood local search guided by a forward-backward shifting bottleneck method. The combination of shifting bottleneck mechanism and tabu list is used as a means of the manipulation of neighborhood structures, and the perturbation mechanism employed diversifies the search. A feedback mechanism, called repeat-check, detects consequent repeats and ignites a perturbation when the total number of consecutive repeats for two identical makespan values reaches a given threshold. The results of extensive computational experiments on the benchmark instances indicate that the combination of these four components is synergetic, in the sense that they collectively make the procedure fast and robust.

Supporting the Supermarket Shopping Experience through a Context-Aware Shopping Trolley

DEFF Research Database (Denmark)

Black, Darren; Clemmensen, Nils Jakob; Skov, Mikael B.

2009-01-01

Shopping in the real world is becoming an increasingly interactive experience as stores integrate various technologies to support shoppers. Based on an empirical study of supermarket shoppers, we designed a mobile context-aware system called the Context- Aware Shopping Trolley (CAST). The aim...... of the system is to support shopping in supermarkets through context-awareness and acquiring user attention. Thus, the interactive trolley guides and directs shoppers in the handling and finding of groceries. An empirical evaluation showed that shoppers using CAST adapted in different shopping behavior than...... traditional trolley shoppers by exhibiting a more uniform behavior in terms of product sequence collection and ease of finding products and thus, CAST supported the shopping experience....

29 CFR 1910.218 - Forging machines.

Science.gov (United States)

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Forging machines. 1910.218 Section 1910.218 Labor... OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.218 Forging machines. (a... other identifier, for the forging machine which was inspected. (ii) Scheduling and recording the...

A New Method Based on Simulation-Optimization Approach to Find Optimal Solution in Dynamic Job-shop Scheduling Problem with Breakdown and Rework

Directory of Open Access Journals (Sweden)

Farzad Amirkhani

2017-03-01

The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.

Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping

OpenAIRE

Farag, Sendy; Schwanen, Tim; Dijst, Martin

2005-01-01

Searching product information or buying goods online is becoming increasingly popular and could affect shopping trips. However, the relationship between e-shopping and in-store shopping is currently unclear. The aim of this study is to investigate empirically how the frequencies of online searching, online buying, and non-daily shopping trips relate to each other, after controlling for sociodemographic, land use, behavioral, and attitudinal characteristics. Data were collected from 826 respon...

Modularity Design Approach for Preventive Machine Maintenance

Science.gov (United States)

Ernawati, D.; Pudji, E.; Ngatilah, Y.; Handoyo, R.

2018-01-01

In a company, machine maintenance system will be very influential in production process activity. The company should have a scheduled engine maintenance system that does not require high costs when repairing and replacing machine parts. Modularity Design method is able to provide solutions to the engine maintenance scheduling system and can prevent fatal damage to the engine components. It can minimize the cost of repair and replacement of these machine components.The paper provides a solution to machine maintenance problems. The paper is also completed with case study of milling machines. That case studies can give us a real description about impact implementation of modularity design to prevent fatal damage to components and minimize the cost of repair and replacement of components of the machine.

Implementation of Real-Time Machining Process Control Based on Fuzzy Logic in a New STEP-NC Compatible System

Directory of Open Access Journals (Sweden)

Po Hu

2016-01-01

Full Text Available Implementing real-time machining process control at shop floor has great significance on raising the efficiency and quality of product manufacturing. A framework and implementation methods of real-time machining process control based on STEP-NC are presented in this paper. Data model compatible with ISO 14649 standard is built to transfer high-level real-time machining process control information between CAPP systems and CNC systems, in which EXPRESS language is used to define new STEP-NC entities. Methods for implementing real-time machining process control at shop floor are studied and realized on an open STEP-NC controller, which is developed using object-oriented, multithread, and shared memory technologies conjunctively. Cutting force at specific direction of machining feature in side mill is chosen to be controlled object, and a fuzzy control algorithm with self-adjusting factor is designed and embedded in the software CNC kernel of STEP-NC controller. Experiments are carried out to verify the proposed framework, STEP-NC data model, and implementation methods for real-time machining process control. The results of experiments prove that real-time machining process control tasks can be interpreted and executed correctly by the STEP-NC controller at shop floor, in which actual cutting force is kept around ideal value, whether axial cutting depth changes suddenly or continuously.

An iPad™-based picture and video activity schedule increases community shopping skills of a young adult with autism spectrum disorder and intellectual disability.

Science.gov (United States)

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.

Internet Shopping

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.

THE INFLUENCE OF HEDONIC SHOPPING MOTIVATION TO THE IMPULSE BUYING OF ONLINE-SHOPPING CONSUMER ON INSTAGRAM

Directory of Open Access Journals (Sweden)

Asnawati

2018-02-01

Full Text Available This research aims to know the influence of Adventure Shopping, Relaxation Shopping, Value Shopping, Social Shopping and Idea Shopping variables to the variable of Impulse Buying of Online-Shopping Consumer on Instagram. The type of the research is explanatory research. The result of F-test showed that Fcount (12.829 > Ftable (2.669 which meant that research variables had influences to the Impulse Buying. With partial correlation value of 0.548, Idea Shopping variable became the dominant factor influencing Impulse Buying on the online-shopping purchase on Instagram.

Evolutionary heuristic for makespan minimization in no-idle flow shop production systems - doi: 10.4025/actascitechnol.v35i2.12534

Directory of Open Access Journals (Sweden)

Marcelo Seido Nagano

2013-04-01

Full Text Available This paper deals with no-idle flow shop scheduling problem with the objective of minimizing makespan. A new hybrid metaheuristic is proposed for the scheduling problem solution. The proposed method is compared with the best method reported in the literature. Experimental results show that the new method provides better solutions regarding the solution quality to set of problems evaluated.  

Heuristics for batching and sequencing in batch processing machines

Directory of Open Access Journals (Sweden)

Chuda Basnet

2016-12-01

Full Text Available In this paper, we discuss the “batch processing” problem, where there are multiple jobs to be processed in flow shops. These jobs can however be formed into batches and the number of jobs in a batch is limited by the capacity of the processing machines to accommodate the jobs. The processing time required by a batch in a machine is determined by the greatest processing time of the jobs included in the batch. Thus, the batch processing problem is a mix of batching and sequencing – the jobs need to be grouped into distinct batches, the batches then need to be sequenced through the flow shop. We apply certain newly developed heuristics to the problem and present computational results. The contributions of this paper are deriving a lower bound, and the heuristics developed and tested in this paper.

THE INFLUENCE OF HEDONIC SHOPPING MOTIVATION TO THE IMPULSE BUYING OF ONLINE-SHOPPING CONSUMER ON INSTAGRAM

OpenAIRE

Asnawati; Wahyuni S.

2018-01-01

This research aims to know the influence of Adventure Shopping, Relaxation Shopping, Value Shopping, Social Shopping and Idea Shopping variables to the variable of Impulse Buying of Online-Shopping Consumer on Instagram. The type of the research is explanatory research. The result of F-test showed that Fcount (12.829) > Ftable (2.669) which meant that research variables had influences to the Impulse Buying. With partial correlation value of 0.548, Idea Shopping variable became the dominant fa...

Shopping Malls - ShoppingCenters

Data.gov (United States)

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...

Integrated network design and scheduling problems :

Energy Technology Data Exchange (ETDEWEB)

Nurre, Sarah G.; Carlson, Jeffrey J.

2014-01-01

We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

Minimizing total weighted tardiness for the single machine scheduling problem with dependent setup time and precedence constraints

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.

Shop Floor Scheduling for Program Depot Maintenance Considering Stochastic Repair Needs

National Research Council Canada - National Science Library

Gemmill, Douglas

2000-01-01

.... The research resulted in the development of a new method to identify the critical path within resource-constrained project scheduling problems, heuristic search methods that improved overall project...

Female Consumers Recreational Shopping Experiences

Directory of Open Access Journals (Sweden)

Sarbjot Singh

2013-04-01

Full Text Available The study examines the core meaning of intrinsic shopping to understand their experimental aspects of recreational and leisure shopping. The study focus only on female shoppers of age group ranging from 25-30, and understand their mall experiences because this segment is newly transform into self dependent segment which have less social and familial liabilities and have enough enthusiasm to explore the world or their boundaries. The Grounded theory use for identification of recreational shopping themes which are (a seeking experiences and (b experimental shopping and each have respective sub themes. The themes are connected to the key idea that shoppers are motivated by their expectations and desires. The study uses social constructivism to find and understand the shopper meanings in real terms rather than imposing and judgment on them. The findings described the way people do recreational shopping and how shopping malls use as leisure space and become facilitators of recreational shopping activities. Females use malls to fulfill their recreational and leisure shopping experiences as this is the great way of enjoying shopping for females of small towns. In malls females not only enjoy product experiences but services experiences also which makes their shopping interesting. The way the female of this age category use malls help the marketers and retailers to understand this segment shopping patterns.

The Virtual Shopping Experience: using virtual presence to motivate online shopping

Directory of Open Access Journals (Sweden)

Carolyn Chin

2005-11-01

Full Text Available Online shopping has thus far tended to be a niche business – highly successful in selling digital products such as shares, software and, increasingly, music and films, it has been less successful in persuading the purchasers of ‘traditional’ goods such as cars, clothes, toiletries, or household appliances to forsake their physical retailers and move into cyberspace. In this wide-ranging review paper we investigate the issue of the virtual experience – endeavouring to understand what is needed for a successful ‘shopping experience’ online and what the possible obstacles or pitfalls along the way might be. We initially introduce the concepts of virtual presence (the sense of ‘being there’ and virtual reality, discussing the possible roles both can play in providing a solution to the problem of effective online shopping. We then consider the Experience Economy, a concept which encapsulates many of the issues related to the problem of online shopping and which suggests ways in which online retailers can enhance the effectiveness of their sites by means of a virtual ‘experience’. Having set the scene for online shopping, we discuss eTailing today in terms of direct product experience and the opportunities which cyber-shopping offers to replicate this process. Finally, we identify some of the possibilities and problems of online shopping today, illustrating the current status of virtual presence in retailing with two micro-cases of success and failure.

Split scheduling with uniform setup times.

NARCIS (Netherlands)

F. Schalekamp; R.A. Sitters (René); S.L. van der Ster; L. Stougie (Leen); V. Verdugo; A. van Zuylen

2015-01-01

htmlabstractWe study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a

Online Shopping Behavior

OpenAIRE

Shahzad, Hashim

2015-01-01

Online shopping is a very much developed phenomena in Scandinavian countries. Different online factors impact online consumers’ behavior differently depending on the environment of different regions. Sweden is one of the developed and technologically advanced countries. To see the impact of different factors on consumers’ online shopping behavior, the purpose of this study is to analyse the factors that influence consumers’ online shopping behavior in Sweden’s context. One of the objectives o...

Traitement d'un problème de type FJSP (Flexible Job Shop ...

African Journals Online (AJOL)

Dans cet article, nous avons étudié le problème d'optimisation d'une cellule de production flexible de type FJSP (flexible job-shop scheduling problem), dont le contrôle est très complexe. Parmi les multiples techniques et méthodes utilisées pour l‟étude de ce type de problème, il y a celles qui relèvent de la recherche ...

Secure Autonomous Automated Scheduling (SAAS). Rev. 1.1

Science.gov (United States)

Walke, Jon G.; Dikeman, Larry; Sage, Stephen P.; Miller, Eric M.

2010-01-01

This report describes network-centric operations, where a virtual mission operations center autonomously receives sensor triggers, and schedules space and ground assets using Internet-based technologies and service-oriented architectures. For proof-of-concept purposes, sensor triggers are received from the United States Geological Survey (USGS) to determine targets for space-based sensors. The Surrey Satellite Technology Limited (SSTL) Disaster Monitoring Constellation satellite, the UK-DMC, is used as the space-based sensor. The UK-DMC's availability is determined via machine-to-machine communications using SSTL's mission planning system. Access to/from the UK-DMC for tasking and sensor data is via SSTL's and Universal Space Network's (USN) ground assets. The availability and scheduling of USN's assets can also be performed autonomously via machine-to-machine communications. All communication, both on the ground and between ground and space, uses open Internet standards

Sleep Management on Multiple Machines for Energy and Flow Time

DEFF Research Database (Denmark)

Chan, Sze-Hang; Lam, Tak-Wah; Lee, Lap Kei

2011-01-01

In large data centers, determining the right number of operating machines is often non-trivial, especially when the workload is unpredictable. Using too many machines would waste energy, while using too few would affect the performance. This paper extends the traditional study of online flow-time...... scheduling on multiple machines to take sleep management and energy into consideration. Specifically, we study online algorithms that can determine dynamically when and which subset of machines should wake up (or sleep), and how jobs are dispatched and scheduled. We consider schedules whose objective...... is to minimize the sum of flow time and energy, and obtain O(1)-competitive algorithms for two settings: one assumes machines running at a fixed speed, and the other allows dynamic speed scaling to further optimize energy usage. Like the previous work on the tradeoff between flow time and energy, the analysis...

Customer experience with online shopping : what are the unique experiences customers seek from online shopping?

OpenAIRE

Jin, Daoyan

2013-01-01

Over the last decade, there has been a great change in consumers' shopping behavior along with technological change. Online shopping is the use of computer technology for better shopping performance. Retailers are busy in studying consumers' behavior to see their attitudes toward online shopping and to meet the demand of online shoppers. Due to my interest in online business, I have also decided to study about customers' attitudes toward online shopping and specifically regarding factors that...

GENDER AND SHOPPING BEHAVIOR OUTCOMES IN THE CONTEXT OF SHOPPING CENTERS

Directory of Open Access Journals (Sweden)

Ioana Nicoleta ABRUDAN

2016-09-01

Full Text Available Understanding consumer behavior can be divided into three parts: before visiting the stores or shopping centers, during the visit, and after. From the point of view of the final result intended by retailers, satisfying customers in terms of profitability, all three components are equally important. A relevant segmentation criterion for most products and stores is gender. Previous research suggests that gender influences shopping motivations, the way people shop and shopping behavior outcomes. The purpose of this article is to investigate if there are, indeed, differences between shopping behavior outputs of women and men (affective loyalty (satisfaction and conative loyalty, as found by certain researchers, and also in terms of the factors that influence the formation of conative loyalty. The results confirm that there are few significant differences in the satisfaction level, although for women all values are slightly higher, and none in the repurchase and recommendation intentions between the two genders. Conative loyalty formation (defined as intent to repurchase and recommend takes place differently between the two genders.

Handbook of machine soldering SMT and TH

CERN Document Server

Woodgate, Ralph W

1996-01-01

A shop-floor guide to the machine soldering of electronics Sound electrical connections are the operational backbone of every piece of electronic equipment-and the key to success in electronics manufacturing. The Handbook of Machine Soldering is dedicated to excellence in the machine soldering of electrical connections. Self-contained, comprehensive, and down-to-earth, it cuts through jargon, peels away outdated notions, and presents all the information needed to select, install, and operate machine soldering equipment. This fully updated and revised volume covers all of the new technologies and processes that have emerged in recent years, most notably the use of surface mount technology (SMT). Supplemented with 200 illustrations, this thoroughly accessible text Describes reflow and wave soldering in detail, including reflow soldering of SMT boards and the use of nitrogen blankets * Explains the setup, operation, and maintenance of a variety of soldering machines * Discusses theory, selection, and control met...

A Markov chain analysis of the effectiveness of drum-buffer-rope material flow management in job shop environment

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2015-09-01

Full Text Available The theory of constraints is an approach for production planning and control, which emphasizes on the constraints in the system to increase throughput. The theory of constraints is often referred to as Drum-Buffer-Rope developed originally by Goldratt. Drum-Buffer-Rope uses the drum or constraint to create a schedule based on the finite capacity of the first bottleneck. Because of complexity of the job shop environment, Drum-Buffer-Rope material flow management has very little attention to job shop environment. The objective of this paper is to apply the Drum-Buffer-Rope technique in the job shop environment using a Markov chain analysis to compare traditional method with Drum-Buffer-Rope. Four measurement parameters were considered and the result showed the advantage of Drum-Buffer-Rope approach compared with traditional one.

Online shopping hesitation.

Science.gov (United States)

Cho, Chang-Hoan; Kang, Jaewon; Cheon, Hongsik John

2006-06-01

This study was designed to understand which factors influence consumer hesitation or delay in online product purchases. The study examined four groups of variables (i.e., consumer characteristics, contextual factors perceived uncertainty factors, and medium/channel innovation factors) that predict three types of online shopping hesitation (i.e., overall hesitation, shopping cart abandonment, and hesitation at the final payment stage). We found that different sets of delay factors are related to different aspects of online shopping hesitation. The study concludes with suggestion for various delay-reduction devices to help consumers close their online decision hesitation.

The influences of social e-shopping in enhancing young women’s online shopping behaviour

OpenAIRE

Dennis, C; Morgan, A; Wright, LT; Jayawardhena, C

2010-01-01

Copyright @ 2010 Westburn Publishers Ltd The background to this paper is that shoppers, particularly women, are motivated by a variety of different reasons, including socialising and enjoyment. Despite the growth of Internet retailing (e-retailing), these social needs are largely unmet in e-shopping. In the high street, women do most of the shopping but online shopping (e-shopping) tends to be dominated by male shoppers. At the same time, social networking is growing fast and is especially...

Post LS1 schedule

CERN Document Server

Lamont, M

2014-01-01

The scheduling limits for a typical long year taking into account technical stops, machine development, spe- cial physics runs are presented. An attempt is then made to outline a ten year post LS1 schedule taking into account the disparate requirements outlined in the previous talks in this session. The demands on the planned long shutdowns and the impact of these demands on their proposed length will be discussed. The option of using ion running as a pre-shutdown cool-down period will be addressed.

Supporting shop floor intelligence

DEFF Research Database (Denmark)

Carstensen, Peter; Schmidt, Kjeld; Wiil, Uffe Kock

1999-01-01

Many manufacturing enterprises are now trying to introduce various forms of flexible work organizations on the shop floor. However, existing computer-based production planning and control systems pose severe obstacles for autonomous working groups and other kinds of shop floor control to become r......-to-day production planning by supporting intelligent and responsible workers in their situated coordination activities on the shop floor....

Neural nets for job-shop scheduling, will they do the job?

NARCIS (Netherlands)

Rooda, J.E.; Willems, T.M.; Goodwin, G.C.; Evans, R.J.

1993-01-01

A neural net structure has been developed which is capable of solving deterministic jobshop scheduling problems, part of the large class of np-complete problems. The problem was translated in an integer linear-programming format which facilitated translation in an adequate neural net structure. Use

Shopping Problems among High School Students

Science.gov (United States)

Grant, Jon E.; Potenza, Marc N.; Krishnan-Sarin, Suchitra; Cavallo, Dana A.; Desai, Rani A.

2010-01-01

Background Although shopping behavior among adolescents is normal, for some the shopping becomes problematic. An assessment of adolescent shopping behavior along a continuum of severity and its relationship to other behaviors and health issues is incompletely understood. Methods A large sample of high school students (n=3999) was examined using a self-report survey with 153 questions concerning demographic characteristics, shopping behaviors, other health behaviors including substance use, and functioning variables such as grades and violent behavior. Results The overall prevalence of problem shopping was 3.5% (95%CI: 2.93–4.07). Regular smoking, marijuana and other drug use, sadness and hopelessness, and antisocial behaviors (e.g., fighting, carrying weapons) were associated with problem shopping behavior in both boys and girls. Heavy alcohol use was significantly associated with problem shopping only in girls. Conclusion Problem shopping appears fairly common among high school students and is associated with symptoms of depression and a range of potentially addictive and antisocial behaviors. Significant distress and diminished behavioral control suggest that excessive shopping may often have significant associated morbidity. Additional research is needed to develop specific prevention and treatment strategies for adolescents who report problems with shopping. PMID:21497217

Shopping problems among high school students.

Science.gov (United States)

Grant, Jon E; Potenza, Marc N; Krishnan-Sarin, Suchitra; Cavallo, Dana A; Desai, Rani A

2011-01-01

Although shopping behavior among adolescents is normal, for some, the shopping becomes problematic. An assessment of adolescent shopping behavior along a continuum of severity and its relationship to other behaviors and health issues is incompletely understood. A large sample of high school students (n = 3999) was examined using a self-report survey with 153 questions concerning demographic characteristics, shopping behaviors, other health behaviors including substance use, and functioning variables such as grades and violent behavior. The overall prevalence of problem shopping was 3.5% (95% CI, 2.93-4.07). Regular smoking, marijuana and other drug use, sadness and hopelessness, and antisocial behaviors (e.g., fighting, carrying weapons) were associated with problem shopping behavior in both boys and girls. Heavy alcohol use was significantly associated with problem shopping only in girls. Problem shopping appears fairly common among high school students and is associated with symptoms of depression and a range of potentially addictive and antisocial behaviors. Significant distress and diminished behavioral control suggest that excessive shopping may often have significant associated morbidity. Additional research is needed to develop specific prevention and treatment strategies for adolescents who report problems with shopping. Copyright © 2011 Elsevier Inc. All rights reserved.

Robust and Flexible Scheduling with Evolutionary Computation

DEFF Research Database (Denmark)

Jensen, Mikkel T.

Over the last ten years, there have been numerous applications of evolutionary algorithms to a variety of scheduling problems. Like most other research on heuristic scheduling, the primary aim of the research has been on deterministic formulations of the problems. This is in contrast to real world...... scheduling problems which are usually not deterministic. Usually at the time the schedule is made some information about the problem and processing environment is available, but this information is uncertain and likely to change during schedule execution. Changes frequently encountered in scheduling...... 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...

Machine for Shopping: American Postwar Malls, Culture, and the Consumption of Commercial Urbanism

OpenAIRE

Siegel, Robyn Schwartz

2011-01-01

This thesis presents three case studies: a modern mall, NorthPark Center, and two contemporary shopping malls, The Americana at Brand and Crystals at CityCenter. These examples problematize aspects of American culture and consumption. Each mall is analyzed in the context of its retail history, the intention of the architecture, the art, the references to other buildings, places, or times, and, lastly, how the commercial mall purports to embody positive forms of urbanity in an idealized city ...

Zero waste machine coolant management strategy at Los Alamos National Laboratory

International Nuclear Information System (INIS)

Carlson, B.; Algarra, F.; Wilburn, D.

1998-01-01

Machine coolants are used in machining equipment including lathes, grinders, saws and drills. The purpose of coolants is to wash away machinery debris in the form of metal fines, lubricate, and disperse heat between the part and the machine tool. An effective coolant prolongs tool life and protects against part rejection, commonly due to scoring or scorching. Traditionally, coolants have a very short effective life in the machine, often times being disposed of as frequently as once per week. The cause of coolant degradation is primarily due to the effects of bacteria, which thrive in the organic rich coolant environment. Bacteria in this environment reproduce at a logarithmic rate, destroying the coolant desirable aspects and causing potential worker health risks associated with the use of biocides to control the bacteria. The strategy described in this paper has effectively controlled bacterial activity without the use of biocides, avoided disposal of a hazardous waste, and has extended coolant life indefinitely. The Machine Coolant Management Strategy employed a combination of filtration, heavy lubricating oil removal, and aeration, which maintained the coolant peak performance without the use of biocides. In FY96, the Laboratory generated and disposed of 19,880 kg of coolants from 9 separate sites at a cost of $145K. The single largest generator was the main machine shop producing an average 14,000 kg annually. However, in FY97, the waste generation for the main machine shop dropped to 4,000 kg after the implementation of the zero waste strategy. It is expected that this value will be further reduced in FY98

An integer batch scheduling model considering learning, forgetting, and deterioration effects for a single machine to minimize total inventory holding cost

Science.gov (United States)

Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.

2018-03-01

This research deals with a single machine batch scheduling model considering the influenced of learning, forgetting, and machine deterioration effects. The objective of the model is to minimize total inventory holding cost, and the decision variables are the number of batches (N), batch sizes (Q[i], i = 1, 2, .., N) and the sequence of processing the resulting batches. The parts to be processed are received at the right time and the right quantities, and all completed parts must be delivered at a common due date. We propose a heuristic procedure based on the Lagrange method to solve the problem. The effectiveness of the procedure is evaluated by comparing the resulting solution to the optimal solution obtained from the enumeration procedure using the integer composition technique and shows that the average effectiveness is 94%.

Binjai Shopping Mall : Arsitektur Metafora

OpenAIRE

Abadsyah, Haris

2014-01-01

City of Binjai have a potential to increase economic growth, especially in the field of trade and services.It can be seen from appearance of the commercial building like the shopping center ( Binjai Super Mall, Ramayana and Suzuya ) Construction of Binjai Shopping Mall intended for planning new shopping centers that provide public kebuthan in Binjai and well planned shopping center with optimal processing space and create a comfortable and pleasant atmosphere. In addition, the ...

Consumers’ Attitude towards Online Shopping : Factors influencing Gotland consumers to shop online

OpenAIRE

Sultan, Muhammad Umar; Uddin, Md. Nasir

2011-01-01

In the era of globalization electronic marketing is a great revolution.  Over the last decade maximum business organizations are running with technological change.  Online shopping or marketing is the use of technology (i.e., computer) for better marketing performance. And retailers are devising strategies to meet the demand of online shoppers; they are busy in studying consumer behavior in the field of online shopping, to see the consumer attitudes towards online shopping. Therefore we have ...

The local–global conjecture for scheduling with non-linear cost

NARCIS (Netherlands)

Bansal, N.; Dürr, C.; Thang, N.K.K.; Vásquez, Ó.C.

2017-01-01

We consider the classical scheduling problem on a single machine, on which we need to schedule sequentially n given jobs. Every job j has a processing time pj and a priority weight wj, and for a given schedule a completion time Cj. In this paper, we consider the problem of minimizing the objective

Shopping in discount stores

DEFF Research Database (Denmark)

Zielke, Stephan

2014-01-01

quarters of intentions to shop in discount stores. Value perception has the strongest total effect, which is partly mediated by enjoyment, shame and guilt. Attributions influence the shopping intention indirectly via value perception and emotions. The inferior quality attribution has the strongest total......This paper analyzes the impact of price-related attributions, emotions and value perception on the intention to shop at grocery discounters in an integrated framework. Moderating effects of price consciousness are also analyzed. The results show that the proposed model explains almost three...... effect, followed by the efficiency of the business model attribution. The unfairness to stakeholders and the tricks in price communication attribution mostly influence the shopping intention for less price-conscious customers....

UN ALGORITMO GENÉTICO HÍBRIDO Y UN ENFRIAMIENTO SIMULADO PARA SOLUCIONAR EL PROBLEMA DE PROGRAMACIÓN DE PEDIDOS JOB SHOP UM ALGORITMO GENÉTICO HÍBRIDO E UM ESFRIAMENTO SIMULADO PARA SOLUCIONAR O PROBLEMA DE PROGRAMAÇÃO DE PEDIDOS JOB SHOP A HYBRID GENETIC ALGORITHM AND A SIMULATED ANNEALING FOR SOLVING THE JOB SHOP SCHEDULING PROBLEM

Directory of Open Access Journals (Sweden)

José David Meisel

2010-07-01

mostraram que os algoritmos propostos arrojam bons resultados, com desvios ao redor dos melhores valores achados que não superam 5 % para os problemas mais complexos.Job Shop Scheduling Problem (JSP, classified as NP-Hard, has been a challenge for the scientific community because achieving an optimal solution to this problem is complicated as it grows in number of machines and jobs. Numerous techniques, including metaheuristics, have been used for its solution; however, the efficiency of the techniques, in terms of computational time, has not been very satisfactory. Because of this and for contributing to the solution of this problem, a simulated annealing (SA and an improved genetic algorithm (IGA have been proposed. The latter, by implementing a strategy of simulated annealing in the mutation phase, allows the algorithm to enhance and diversify the solutions at the same time, in order not to converge prematurely to a local optimum. The results showed that the proposed algorithms yield good results with deviations around the best values found not exceeding 5 % for more complex problems.

Vape Shop Employees: Public Health Advocates?

OpenAIRE

Hart, Joy L; Walker, Kandi L; Sears, Clara G; Lee, Alexander S; Smith, Courteney; Siu, Allison; Keith, Rachel; Ridner, S. Lee

2017-01-01

INTRODUCTION E-cigarettes have increased in popularity and given rise to a new type of sales outlet?the vape shop. Expanding on work examining vape shop employee e-cigarette and tobacco attitudes and behaviors 1 , this study examined key messages that vape shop employees communicate to customers. METHODS Using informal interviews, observations, and a cross-sectional survey, we examined vape shop employees? (n=16) perceptions and e-cigarette use. Data were collected in nine vape shops in Louis...

Scheduling permutation flowshops with initial availability constraint: Analysis of solutions and constructive heuristics

OpenAIRE

Pérez González, Paz; Framiñán Torres, José Manuel

2009-01-01

In this paper, we address the problem of scheduling a set of jobs in a flowshop with makespan objective. In contrast to the usual assumption of machine availability presented in most research, we consider that machines may not be available at the beginning of the planning period, due to processing of previously scheduled jobs. We first formulate the problem, analyse the structure of solutions depending on a number of factors (such as machines, jobs, structure of the processing times, availabi...

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Directory of Open Access Journals (Sweden)

Jianbo Qian

2013-01-01

Full Text Available We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them in O(n4 time. For some important special cases, the time complexity can be improved to be O(n2 using dynamic programming techniques.

The Effects of Shopping Orientations, Consumer Innovativeness, Purchase Experience, and Gender on Intention to Shop for Fashion Products Online

Directory of Open Access Journals (Sweden)

Ratih Puspa Nirmala

2011-02-01

Full Text Available Nowadays, many fashion retailers or marketers use the power of internet to promote and sell their products. This research examines the effects of consumers’ shopping orientations (brand/fashion consciousness, shopping enjoyment, price consciousness, convenience/time consciousness, shopping confidence, in-home shopping tendency, consumer innovativeness, online purchase experience for fashion products, and gender on consumers’ intention to shop for fashion products online. Data were collected through online surveys from the population of internet users in Indonesia, aged between 15 and 30 years old (generation Y, who had bought or browsed fashion products through the internet (N=210. This research is a quantitative research which uses purposive sampling and multiple regression analysis. Results show that the effects of several shopping orientations (shopping enjoyment, price consciousness, in-home shopping tendency, consumer innovativeness, online purchase experience for fashion products, and gender, are significant on consumers’ intention to shop for fashion products online. Furthermore, gender is marginally significant related to consumers’ intention to shop for fashion products online. Surprisingly, women tend to have lower intentions to shop for fashion products online compared to men.

Online Shopping: Advantages over the Offline Alternative

OpenAIRE

Dr Joshua Chang

2003-01-01

The advent of the Internet as a shopping medium has enabled shoppers to gain shopping benefits such as convenience and time-saving, better information, and price savings. This paper aims to provide a better understanding of the benefits of Internet shopping by identifying and discussing the advantages of Internet shopping over traditional storefront shopping.

PENGARUH ATMOSFER PUSAT BELANJA PADA SHOPPING VALUE

Directory of Open Access Journals (Sweden)

Astrid Kusumowidagdo

2015-11-01

Full Text Available AbstractAt the moment, the creation of shopping environment design that provides certain sensation and experience become strategy of the shopping center. This research aims to find out about the influence of shopping center’s atmosphere towards shopping value. The formative factors of shopping centre’s atmosphere are architectural features, interior features and support facilities. The research begins with a focus group to adjust the indicators of the previous research to the present research’s object. The next stage of research is done with a multiple regression analysis. The research object is the atmosphere condition of Senayan City shopping center in Jakarta and the subjects are samples totaling to sixty people. The samples are visitors from the middle-class segment between the age of 18-35.The research finds that architectural features, interior features and support facilities collectively bring an influence towards shopping value in Senayan City Pusat belanja, wether partially, only interior features show the significant influence towards shopping value.Keywords: design, atmosphere, shopping centre, shopping value.AbstrakSaat ini penciptaan lingkungan belanja dengan yang memberikan sensasi dan pengalaman telah menjadi bagian dari strategi bisnis pusat belanja. Penelitian ini bertujuan untuk menelusuri pengaruh atmosfer pusat belanja terhadap shopping value. Atmosfer pusat belanja dibentuk oleh faktor-faktor yaitu fitur arsitektur, fitur interior dan fasilitas penunjang. Penelitian ini diawali dengan focus group untuk penentuan indikator yang tepat dan dilanjutkan dengan survey pada 60 orang dengan usia 18-35 tahun yang bersegmen menengah. Obyek penelitian adalahatmosfer dari pusat belanja Senayan City. Hasil penelitian menunjukkan terdapat hubungan dari faktor-faktor atmosfer pusat belanja secara serempak pada shopping value, sedangkan secara parsial hanya fitur interior yang memberikan pengaruh signifikan pada shopping value

A New Evolutionary Algorithm Based on Bacterial Evolution and Its Application for Scheduling A Flexible Manufacturing System

Directory of Open Access Journals (Sweden)

Chandramouli Anandaraman

2012-01-01

Full Text Available A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs. AGVs are used for carrying jobs between the Load/Unload (L/U station and the machines. Experimental results indicate the efficiency of the proposed algorithm in its optimization performance in scheduling is noticeably superior to other evolutionary algorithms when compared to the best results reported in the literature for FMS Scheduling.

Performance comparison of plastic shopping bags in modern and traditional retail

Science.gov (United States)

Radini, F. A.; Wulandari, R.; Nasiri, S. J. A.; Winarto, D. A.

2017-07-01

Followed by implementation of paid plastic bag policy in Indonesia’s modern and traditional retail, community question related to plastic shopping bag performance arise. But, there is limited information about it. Therefore, the assessment of the performance to compare between plastic shopping bags in modern retail and traditional retail should be interesting. The observation performance of plastic shopping bag were weight holding capacity, tear resistant and elongation. This performance were tested using Universal Testing Machine. Physical and physico-chemical properties also identified to determine factor affecting the performance of plastic shopping bag. The physical properties were analysed using visual and thickness gauge to see the colour and measure the thickness. The analysis of physico-chemical properties were carried out using DSC (Differential Scanning Calorimetry), TGA (Thermal Gravimetry Analysis), Furnace and FTIR (Fourier Transform Infra Red Spectroscopy) to identify the materials, also its melting and decomposition temperature. The result showed that the performance difference between modern retail plastic bag with traditional retail plastic bag appears only in the performance of elongation. The elongation of modern retail plastic bag is 121 - 413%, while traditional has 170 - 609%. According to physico-chemical test result, modern retail and traditional retail plastic bag contain polyethylene as main material and has melting temperature in the range of High Density Polyethylene (HDPE) melting temperature. However, modern retail plastic bag has 18.31 - 33.87% of inorganic filler percentage, whereas the traditional retail plastic bag has 0.35 - 9.85%. This inorganic filler percentage probably a contributing factor in the elongation performance difference between modern retail plastic bag with traditional retail plastic bag.

Buying cannabis in 'coffee shops'.

Science.gov (United States)

Monshouwer, Karin; Van Laar, Margriet; Vollebergh, Wilma A

2011-03-01

The key objective of Dutch cannabis policy is to prevent and limit the risks of cannabis consumption for users, their direct environment and society ('harm reduction'). This paper will focus on the tolerated sale of cannabis in 'coffee shops'. We give a brief overview of Dutch policy on coffee shops, its history and recent developments. Furthermore, we present epidemiological data that may be indicative of the effects of the coffee shop policy on cannabis and other drug use. Dutch coffee shop policy has become more restrictive in recent years and the number of coffee shops has decreased. Cannabis prevalence rates in the adult population are somewhat below the European average; the rate is relatively high among adolescents; and age of first use appears to be low. On a European level, the use of hard drugs in both the Dutch adult and adolescent population is average to low (except for ecstasy among adults). International comparisons do not suggest a strong, upward effect of the coffee shop system on levels of cannabis use, although prevalence rates among Dutch adolescents give rise to concern. Furthermore, the coffee shop system appears to be successful in separating the hard and soft drugs markets. Nevertheless, in recent years, issues concerning the involvement of organised crime and the public nuisance related to drug tourism have given rise to several restrictive measures on the local level and have sparked a political debate on the reform of Dutch drug policy. © 2011 Trimbos Institute.

Comparative Simulation Study of Production Scheduling in the Hybrid and the Parallel Flow

Directory of Open Access Journals (Sweden)

Varela Maria L.R.

2017-06-01

Full Text Available Scheduling is one of the most important decisions in production control. An approach is proposed for supporting users to solve scheduling problems, by choosing the combination of physical manufacturing system configuration and the material handling system settings. The approach considers two alternative manufacturing scheduling configurations in a two stage product oriented manufacturing system, exploring the hybrid flow shop (HFS and the parallel flow shop (PFS environments. For illustrating the application of the proposed approach an industrial case from the automotive components industry is studied. The main aim of this research to compare results of study of production scheduling in the hybrid and the parallel flow, taking into account the makespan minimization criterion. Thus the HFS and the PFS performance is compared and analyzed, mainly in terms of the makespan, as the transportation times vary. The study shows that the performance HFS is clearly better when the work stations’ processing times are unbalanced, either in nature or as a consequence of the addition of transport times just to one of the work station processing time but loses advantage, becoming worse than the performance of the PFS configuration when the work stations’ processing times are balanced, either in nature or as a consequence of the addition of transport times added on the work stations’ processing times. This means that physical layout configurations along with the way transport time are including the work stations’ processing times should be carefully taken into consideration due to its influence on the performance reached by both HFS and PFS configurations.

Kinect sensing of shopping related actions

NARCIS (Netherlands)

Popa, M.; Koc, A.K.; Rothkrantz, L.J.M.; Shan, C.; Wiggers, P.

2011-01-01

Surveillance systems in shopping malls or supermarkets are usually used for detecting abnormal behavior. We used the distributed video cameras system to design digital shopping assistants which assess the behavior of customers while shopping, detect when they need assistance, and offer their support

Social Sustainability of Shopping Streets in Ankara

Directory of Open Access Journals (Sweden)

Özge YALÇINER ERCOŞKUN

2013-02-01

Full Text Available Shopping streets are integral parts of public spaces in traditional shopping areas of Central Business Districts (CBD. Furthermore, as modern shopping venues, shopping centers offer advantages for modern lifestyles with spacious shopping areas, variety of commercial and social activities, and economic value of their investments. These advantages act in favor of shopping centers and improve the level of shopping street social sustainability and its relevant concepts. The aim of this study is to analyze the main shopping streets of Ankara, using the concepts of social sustainability. In this study, these concepts, such as locality, identity, vitality, viability, sense of place, conviviality, meaning and local characteristics of the shopping streets are investigated. For the first time, the retail unit locations in Ankara, their brands and their business types, are illustrated on thematic land use maps using Geographical Information Systems (GIS software. Next, population activities and consumer spatial behavior are observed and marked on maps that are also referred to as social sustainability maps. The results of the study can be useful in formulating strategies within the framework of social sustainability, which is a relatively new concept.

Large Neighborhood Search and Adaptive Randomized Decompositions for Flexible Jobshop Scheduling

DEFF Research Database (Denmark)

Pacino, Dario; Van Hentenryck, Pascal

2011-01-01

This paper considers a constraint-based scheduling approach to the flexible jobshop, a generalization of the traditional jobshop scheduling where activities have a choice of machines. It studies both large neighborhood (LNS) and adaptive randomized de- composition (ARD) schemes, using random...

Scheduling with target start times

NARCIS (Netherlands)

Hoogeveen, J.A.; Velde, van de S.L.; Klein Haneveld, W.K.; Vrieze, O.J.; Kallenberg, L.C.M.

1997-01-01

We address the single-machine problem of scheduling n independent jobs subject to target start times. Target start times are essentially release times that may be violated at a certain cost. The goal is to minimize an objective function that is composed of total completion time and maximum

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

Science.gov (United States)

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

Science Shops - a concept for community based learning

DEFF Research Database (Denmark)

Jørgensen, Michael Søgaard; Hende, Merete

2001-01-01

Experience from science shops show that besides assisting citizen groups, science shops can also contribute to the development of university curricula and research. The paper is based on an investigation of the impact of science shops on university curricula and research through a questionnaire...... sent out to science shops and through follow-up interviews with employees from nine different university based science shops. These science shops had in the questionnaire indicated that the science shop in one way or the other has had impact on university curricula and/or research. This paper focuses...... on the impact on university curricula. The case studies have been supplemented with articles and reports. The analysis has focused on the kind of impact, which the science shops have reported, and has tried to relate the impact to the local history of the science shop. One direct impact on the curricula...

Why Shops Close Again : An Evolutionary Perspective on the Deregulation of Shopping Hours

NARCIS (Netherlands)

Kosfeld, M.

1999-01-01

This paper introduces a new perspective on the deregulation of shopping hours based on ideas from evolutionary game theory. We study a retail economy where shopping hours have been deregulated recently. It is argued that first, the deregulation leads to a coordination problem between store owners

RingSys-Scheduler User`s manual. Information terminal for town monitoring; Brukermanual for RingSys-Scheduler. Informasjonsterminal for byovervaaking

Energy Technology Data Exchange (ETDEWEB)

Marsteen, L.

1996-02-01

This report is a User`s manual. It describes RingSys Scheduler, a computer system for continuous display of time series, public information and static pictures. The computer is connected to a host machine via modem and time series, and public information are automatically updated once an hour. RingSys-Scheduler is PC based. It is developed using Excel`s macro language as well as the asynchronous communication program Dynacomm`s script language. 12 figs.

An FMS Dynamic Production Scheduling Algorithm Considering Cutting Tool Failure and Cutting Tool Life

International Nuclear Information System (INIS)

Setiawan, A; Wangsaputra, R; Halim, A H; Martawirya, Y Y

2016-01-01

This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule. (paper)

Online Shopping In The UK

OpenAIRE

K. K. Ramachandran; K. K. Karthick; M. Saravana Kumar

2011-01-01

This paper will contribute to current academic literature in the area of online retailing and consumer behaviour. Our research outlines a survey conducted with respondents from the UK to ascertain their attitudes to grocery shopping both off and online. The findings indicate that, whilst the vast majority of our sample has experience of online shopping, few actively engage in online grocery shopping. Some of the reasons for this are highlighted and the key issues relate to consumer trust and ...

Shopping Online Sebagai Gaya Hidup

OpenAIRE

Lestari, Sri Budi

2015-01-01

The use of internet communication technology can make the world as if in one hand makes electronicbusiness with the concept of Online Shopping at its peak in recent years along with the development ofcommunication technologies over theInternet.How to shop online by using the internet through computers andmobile devices is increasingly popular smartphone can even be said to have become a trend today.Variousconvenience of shopping be the main thing to offer, with enough gadgets available in the...

PLANNING VESSEL BODY SECTION PRODUCTION

Directory of Open Access Journals (Sweden)

A. G. Grivachevsky

2015-01-01

Full Text Available A problem of planning production of a vessel body section is considered. The problem is reduced to the classic Johnson’s tree-machine flow-shop scheduling problem. A genetic algorithm and computer experiment to compare efficiency of this algorithm and the algorithm of full enumeration are described.

The Shopping Mall: A Teenager Hangout.

Science.gov (United States)

Anthony, Kathryn H.

1985-01-01

Investigated teenagers' use of the shopping mall as a "hangout" through interviews with 51 adolescents using the mall, and 10 hours of behavioral observations. Results indicated that many teenagers visit the shopping center regularly to watch members of the opposite sex, play video games, see friends, shop, and people-watch. (Author/NRB)

An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction

Directory of Open Access Journals (Sweden)

Zhi Yang

2016-01-01

Full Text Available Uncertainty is common in ship construction. However, few studies have focused on scheduling problems under uncertainty in shipbuilding. This paper formulates the scheduling problem of panel block construction as a multiobjective fuzzy flow shop scheduling problem (FSSP with a fuzzy processing time, a fuzzy due date, and the just-in-time (JIT concept. An improved multiobjective particle swarm optimization called MOPSO-M is developed to solve the scheduling problem. MOPSO-M utilizes a ranked-order-value rule to convert the continuous position of particles into the discrete permutations of jobs, and an available mapping is employed to obtain the precedence-based permutation of the jobs. In addition, to improve the performance of MOPSO-M, archive maintenance is combined with global best position selection, and mutation and a velocity constriction mechanism are introduced into the algorithm. The feasibility and effectiveness of MOPSO-M are assessed in comparison with general MOPSO and nondominated sorting genetic algorithm-II (NSGA-II.

Cross-border shopping and tourism destination marketing

DEFF Research Database (Denmark)

Makkonen, Teemu

2016-01-01

This article addresses the economic impact that cross-border shopping has on the local tourism industry and the ways that cross-border shopping is taken advantage of in tourism destination marketing. Southern Jutland–situated in Denmark just north of the German border, where border shops situated......-border shopping into tourism destination marketing strategies. The results have wider relevance for other border regions.......This article addresses the economic impact that cross-border shopping has on the local tourism industry and the ways that cross-border shopping is taken advantage of in tourism destination marketing. Southern Jutland–situated in Denmark just north of the German border, where border shops situated...... just south of the same border enable Danes to capitalize on the lower value added tax levels in Germany–is utilized as an illustrative case example. The data was collected by analysing the relevant tourism destination marketing material and via interviews with local destination marketing organizations...

Cbs (Contrastrain Based Schedulling Adalah Faktor Penentu Keberhasilan Perusahanan Printing

Directory of Open Access Journals (Sweden)

Hendra Achmadi

2010-06-01

Full Text Available In a highly competitive industry faces today ranging from small or home-based printing to using machine that can print offset a hundred thousand copies per hour. But, the increasing competition resulted in requiring a faster production time from order entry, print proff until the production process to delivery to customers. Often times in case of orders which will result in the concurrent PPIC will experience vertigo in the setting of production schedules which have concurrent delivery time. Often will end up with no receipt of orders due to difficulties in the production schedule, especially if the orders require the same offset machine and cylinder wear the same length, while the number of cylinders is limited. Therefore, the printing company should be able to do so in the conduct of a penetration timing of production can easily be simulated and implemented on the ground. CBS (Base Constraint scheduling is a technique to do the scheduling of production so that production can be carried out smoothly and quickly that fulfill the promise made to customers. In scheduling, there are several techniques that can be used are: FCFS (First Came First Serve, EDD (Earliest Date, and LCLS (Last Came Last Serve. So, it is required to be able to do way better scheduling to get results quickly in this fast changing schedules.

Integrated batch production and maintenance scheduling for multiple items processed on a deteriorating machine to minimize total production and maintenance costs with due date constraint

Directory of Open Access Journals (Sweden)

Zahedi Zahedi

2016-04-01

Full Text Available This paper discusses an integrated model of batch production and maintenance scheduling on a deteriorating machine producing multiple items to be delivered at a common due date. The model describes the trade-off between total inventory cost and maintenance cost as the increase of production run length. The production run length is a time bucket between two consecutive preventive maintenance activities. The objective function of the model is to minimize total cost consisting of in process and completed part inventory costs, setup cost, preventive and corrective maintenance costs and rework cost. The problem is to determine the optimal production run length and to schedule the batches obtained from determining the production run length in order to minimize total cost.

Dynamic Support of Government in Online Shopping

OpenAIRE

Hai, Le Chi; Alam Kazmi, Syed Hasnain

2015-01-01

Advancements in online shopping for consumers requires consistent government support policies and the introduction of substantial government laws and regulations. In order to establish innovative developments in online shopping market environment that makes online shopping faster and stable, the government perspective is vital with the Technology Acceptance Model (TAM) for research and development in online shopping behavior for consumer’s confidence and their purchase intention. The proposed...

SHOPPING ONLINE SEBAGAI GAYA HIDUP

OpenAIRE

Sri Budi Lestari

2016-01-01

The use of internet communication technology can make the world as if in one hand makes electronic business with the concept of Online Shopping at its peak in recent years along with the development of communication technologies over theInternet.How to shop online by using the internet through computers and mobile devices is increasingly popular smartphone can even be said to have become a trend today.Various convenience of shopping be the main thing to offer, with enough gadgets ...

On the Integrated Job Scheduling and Constrained Network Routing Problem

DEFF Research Database (Denmark)

Gamst, Mette

This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...

Solving multi-objective job shop problem using nature-based algorithms: new Pareto approximation features

Directory of Open Access Journals (Sweden)

Jarosław Rudy

2015-01-01

Full Text Available In this paper the job shop scheduling problem (JSP with minimizing two criteria simultaneously is considered. JSP is frequently used model in real world applications of combinatorial optimization. Multi-objective job shop problems (MOJSP were rarely studied. We implement and compare two multi-agent nature-based methods, namely ant colony optimization (ACO and genetic algorithm (GA for MOJSP. Both of those methods employ certain technique, taken from the multi-criteria decision analysis in order to establish ranking of solutions. ACO and GA differ in a method of keeping information about previously found solutions and their quality, which affects the course of the search. In result, new features of Pareto approximations provided by said algorithms are observed: aside from the slight superiority of the ACO method the Pareto frontier approximations provided by both methods are disjoint sets. Thus, both methods can be used to search mutually exclusive areas of the Pareto frontier.

Process Waste Assessment - Paint Shop

International Nuclear Information System (INIS)

Phillips, N.M.

1993-06-01

This Process Waste Assessment was conducted to evaluate hazardous wastes generated in the Paint Shop, Building 913, Room 130. Special attention is given to waste streams generated by the spray painting process because it requires a number of steps for preparing, priming, and painting an object. Also, the spray paint booth covers the largest area in R-130. The largest and most costly waste stream to dispose of is open-quote Paint Shop wasteclose quotes -- a combination of paint cans, rags, sticks, filters, and paper containers. These items are compacted in 55-gallon drums and disposed of as solid hazardous waste. Recommendations are made for minimizing waste in the Paint Shop. Paint Shop personnel are very aware of the need to minimize hazardous wastes and are continuously looking for opportunities to do so

A Scheduling Model for the Re-entrant Manufacturing System and Its Optimization by NSGA-II

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2016-11-01

Full Text Available In this study, a two-objective mixed-integer linear programming model (MILP for multi-product re-entrant flow shop scheduling problem has been designed. As a result, two objectives are considered. One of them is maximization of the production rate and the other is the minimization of processing time. The system has m stations and can process several products in a moment. The re-entrant flow shop scheduling problem is well known as NP-hard problem and its complexity has been discussed by several researchers. Given that NSGA-II algorithm is one of the strongest and most applicable algorithm in solving multi-objective optimization problems, it is used to solve this problem. To increase algorithm performance, Taguchi technique is used to design experiments for algorithm’s parameters. Numerical experiments are proposed to show the efficiency and effectiveness of the model. Finally, the results of NSGA-II are compared with SPEA2 algorithm (Strength Pareto Evolutionary Algorithm 2. The experimental results show that the proposed algorithm performs significantly better than the SPEA2.

A Single-Machine Two-Agent Scheduling Problem by a Branch-and-Bound and Three Simulated Annealing Algorithms

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.

Exact and heuristic solution approaches for the Integrated Job Scheduling and Constrained Network Routing Problem

DEFF Research Database (Denmark)

Gamst, M.

2014-01-01

problem. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results show that solving the integrated job scheduling and constrained network routing problem to optimality is very difficult. The exact solution approach performs......This paper examines the problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job has a certain demand, which must be sent to the executing machine via constrained paths. A job cannot start before all its demands have...... arrived at the machine. Furthermore, two resource demand transmissions cannot use the same edge in the same time period. The problem has application in grid computing, where a number of geographically distributed machines work together for solving large problems. The machines are connected through...

Youth Clothes-Shopping Behavior: An Analysis by Gender.

Science.gov (United States)

Peters, John F.

1989-01-01

Explored possible gender differences in clothes-shopping behavior among adolescents. Findings from 387 college students revealed that: parents financially assisted sons and daughters equally; there was no gender difference in shopping frequency; mothers more frequently shopped with sons than with daughters; fathers rarely shopped with any…

College Students Understanding of Production Management and Master Production Schedule through Using a Real World Tool, Complimented with Company Tours and In- Class Visits, Provides an Excellent Learning Experience at Farmingdale State College

Directory of Open Access Journals (Sweden)

Jill Anne O'Sullivan

2015-08-01

goods through the entire manufacturing cycle from the requisitioning of raw material to the delivery of finished products. (APICS Dictionary 13th Edition The Master Production Schedule is often a major component of Sales and Operations Management. The purpose of the Master Schedule is to translate the Sales forecast into a Production Plan that must be executed by the organization. The Master Schedule is the demand side of the equation and must represent the customers' needs. In this way the Master Scheduler can give manufacturing its best chance for success. Master Production Schedule (MPS: The MPS should be closely aligned with the Sales Forecast. Students enter a Sales Forecast into the system similar to what they have seen at the companies. Students see how it is the liaison between the Sales Forecast and a production work order. Its function is to translate the Sales Forecast into a viable production schedule that supports the customer requirements, while taking into account shop floor constraints. The MPS must support the Sales Forecast and customer demand. Students learn the importance of this in their lab assignments. They identify and enter shop floor resources. Students learn that companies should never chase supply they should chase demand and manage supply. Supply can mean, purchased parts, and externally produced parts, internally made items, internal machine or labor constraints. The student's comprehension of this topic, concept and knowledge is significantly enhanced due to the tours to local manufacturers and the individuals that come into the class to discuss these functional areas and the processes they perform in their organizations. [1] J. O'Sullivan and G. Caiola, Enterprise Resource Planning a Transitional Approach from the Classroom to the Business World, The McGraw-Hill Companies, 2008.

Consumers preferences of shopping centers in Bratislava (Slovakia

Directory of Open Access Journals (Sweden)

Kristína Bilková

2016-05-01

Full Text Available There have been changes in the shopping behavior and preferences of consumers in the post-communist countries caused by political changes after 1989. Slovakia is not an exception, and it has been observed a change not only at the consumers’ level but also in retail stores. A notable bearer of such changes was the construction of big shopping centers that were a new phenomenon in shopping. They quickly became popular and changed spatial and shopping patterns of consumers. The main aim of this study is to analyze and evaluate the shopping preferences of consumers based on the example of the capital city – Bratislava (at the level of urban districts. The database consists of results of a questionnaire survey carried out in 2011. Respondents were interviewed inside the shopping center. The partial aims focus on the analysis of consumers’ perceptions, the frequency of their shopping and the mode of transport used for shopping. One of the goals of this study is also to evaluate the perception of consumers in terms of the catchment areas of the chosen shopping center, as well as the perceptional classification of retail in the given area and the accessibility of stores.

Scheduling preemptable jobs on identical processors under varying availability of an additional continuous resource

Directory of Open Access Journals (Sweden)

Różycki Rafał

2016-09-01

Full Text Available In this work we consider a problem of scheduling preemptable, independent jobs, characterized by the fact that their processing speeds depend on the amounts of a continuous, renewable resource allocated to jobs at a time. Jobs are scheduled on parallel, identical machines, with the criterion of minimization of the schedule length. Since two categories of resources occur in the problem: discrete (set of machines and continuous, it is generally called a discrete-continuous scheduling problem. The model studied in this paper allows the total available amount of the continuous resource to vary over time, which is a practically important generalization that has not been considered yet for discrete-continuous scheduling problems. For this model we give some properties of optimal schedules on a basis of which we propose a general methodology for solving the considered class of problems. The methodology uses a two-phase approach in which, firstly, an assignment of machines to jobs is defined and, secondly, for this assignment an optimal continuous resource allocation is found by solving an appropriate mathematical programming problem. In the approach various cases are considered, following from assumptions made on the form of the processing speed functions of jobs. For each case an iterative algorithm is designed, leading to an optimal solution in a finite number of steps.

Strategy of image management in retail shops

Directory of Open Access Journals (Sweden)

Sandra Soče Kraljević

2007-12-01

Full Text Available A sound positioning in consumers’ mind, along with strong promotion support, brought many retail shops to the top. This is mostly thanks to the image created in the consumers’ mind. A retail shop’s image may but need not conform to reality. Image often looks like a cliché. It overstates certain elements of the shop while simply omitting others. That is exactly why image is of great importance and often crucial to consumer behavior. This paper aims at determining the impact of image on customer behavior in the course of decision making about shopping and choosing a particular retail shop. Image is a significant factor of success of every company, hence also of a retail shops. It is a relatively strong value and a component of creating competitive advantage. But if we do not pay sufficient attention to image, it can become counterproductive. Instead to, like an additional value helps creating and maintaining the advantage in competition and realization of business aims, transforms into a limiting factor. Therefore, it is imperative to identify the elements of image that are of greatest importance to customers. Research has shown that customers choose the retail shop first and after that products and brands within this shop. When it comes to the supermarket, as a kind of retail shop, research has shown that two out of three shopping decisions are made by the customer on the spot, that is, without previous planning. That practically means that we can influence customers with different sales techniques. The paper suggests different strategies of image management for supermarkets and conventional shops. For supermarkets it is the “widest assortment” strategy, while for conventional shops the strategy is that of a “selected group of products“. Improvements to research methods will enable getting more information about customer behavior, while pressures of increased competition in the business environment will force retailers to get

Automated Planning and Scheduling for Space Mission Operations

Science.gov (United States)

Chien, Steve; Jonsson, Ari; Knight, Russell

2005-01-01

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

CERN Shop - Christmas Sale in Bldg. 33

CERN Multimedia

PH Department

2010-01-01

Looking for Christmas present ideas? The CERN Shop will give CERN card holders a special reduction of 10 % on all CERN Shop articles from Monday 13.12.2010 to Saturday 18.12.2010. Come and visit the CERN Shop in the Reception Building 33.

Hybrid Discrete Differential Evolution Algorithm for Lot Splitting with Capacity Constraints in Flexible Job Scheduling