Minimizing makespan for a no-wait flowshop using genetic algorithm

Indian Academy of Sciences (India)

This paper explains minimization of makespan or total completion time .... lead to a natural reduction of the no-wait flow shop problem to the travelling sales- ... FCH can also be applied in real time scheduling and rescheduling for no-wait flow.

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

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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.

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.

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.

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

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Behnam Barzegar

2012-01-01

Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Study on multi-objective flexible job-shop scheduling problem considering energy consumption

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Zengqiang Jiang

2014-06-01

Full Text Available Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II based on blood variation for above scheduling model.Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model.Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption.Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.

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

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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.

Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems

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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.

Approximation algorithms for the parallel flow shop problem

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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

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.

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

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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.

Job shop scheduling by simulated annealing

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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

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

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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.

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 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.

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

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.

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.

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

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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

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.

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.

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.

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

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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.

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.

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.

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.

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

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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.

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

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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.

Outsourcing and scheduling for a two-machine flow shop with release times

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Ahmadizar, Fardin; Amiri, Zeinab

2018-03-01

This article addresses a two-machine flow shop scheduling problem where jobs are released intermittently and outsourcing is allowed. The first operations of outsourced jobs are processed by the first subcontractor, they are transported in batches to the second subcontractor for processing their second operations, and finally they are transported back to the manufacturer. The objective is to select a subset of jobs to be outsourced, to schedule both the in-house and the outsourced jobs, and to determine a transportation plan for the outsourced jobs so as to minimize the sum of the makespan and the outsourcing and transportation costs. Two mathematical models of the problem and several necessary optimality conditions are presented. A solution approach is then proposed by incorporating the dominance properties with an ant colony algorithm. Finally, computational experiments are conducted to evaluate the performance of the models and solution approach.

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

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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.

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.

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

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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

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

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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.

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.

On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling

DEFF Research Database (Denmark)

Neumann, Frank; Witt, Carsten

2015-01-01

combinatorial optimization problem, namely makespan scheduling. We study the model of a strong adversary which is allowed to change one job at regular intervals. Furthermore, we investigate the setting of random changes. Our results show that randomized local search and a simple evolutionary algorithm are very...

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.

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.

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.

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.

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.

Parallel-Batch Scheduling with Two Models of Deterioration to Minimize the Makespan

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Cuixia Miao

2014-01-01

Full Text Available We consider the bounded parallel-batch scheduling with two models of deterioration, in which the processing time of the first model is pj=aj+αt and of the second model is pj=a+αjt. The objective is to minimize the makespan. We present O(n log n time algorithms for the single-machine problems, respectively. And we propose fully polynomial time approximation schemes to solve the identical-parallel-machine problem and uniform-parallel-machine problem, respectively.

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

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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.

Practical job shop scheduling

NARCIS (Netherlands)

Schutten, Johannes M.J.

1998-01-01

The Shifting Bottleneck procedure is an intuitive and reasonably good approximation algorithm for the notoriously difficult classical job shop scheduling problem. The principle of decomposing a classical job shop problem into a series of single-machine problems can also easily be applied to job shop

PENJADWALAN JOB SHOP STATIK DENGAN METODE SIMULATED ANNEALING UNTUK MEMINIMASI WAKTU MAKESPAN

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Moh.Husen

2015-10-01

Full Text Available Penjadwalan bagi perusahaan adalah aspek yang sangat penting, karena penjadwalan merupakan salah satu elemen perencanaan dan pengendalian produksi, sehingga perusahaan dapat mengirim barang sesuai dengan waktu yang telah ditentukan, agar diperoleh waktu total penyelesaian yang minimum. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA dengan bantuan Matlab diharapkan dapat menghasilkan waktu total penyelesaian (makespan lebih cepat dari penjadwalan yang ada pada perusahaan. Metode SA mensimulasikan proses annealing pada pembuatan materi yang terdiri dari butiran Kristal atau logam. Tujuan dari proses ini adalah menghasilkan struktur kristal yang baik dengan menggunakan energi seminimal mungkin. Permasalahan yang dihadapi oleh perusahaan adalah perusahaan belum mempertimbangkan makespan dalam penyelesaian produk dan penjadwalan produksi untuk produk paket satu rumah kos-kosan. Hal ini berdasarkan data produksi yang terjadi keterlambatan dilihat dari waktu penyelesaian (makespan produksi, sehingga perusahaan harus menambah 2-5 hari lagi untuk bisa menyelesaikan keseluruhan produk. Dengan menggunakan metode SA menghasilkan makespan 23 jam, lebih cepat 2 jam dari pada penjadwalan awal.

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.

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

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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

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

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Omar Danilo Castrillón

2010-08-01

Full Text Available The objective of the present work is to diminish the total process time (Makespan and to increase the machine process time, by diminishing the idle time in a job-shop environment. Through the design of a hyper-heuristic based on an ant colony and genetic algorithms. This work is developed in two phases: in the first phase, a hyper-heuristic identification and definition is carried out for sequencing processes in job shop environments. In the second phase, the system effectiveness in the traditional production programming is shown. In the investigation project, an enterprise from the metal mechanic sector was chosen, where by means of a combination of an ant colony and genetic algorithms, the optimal route for an order is scheduled, achieving the optimization or suboptimization of its respective total process time in an upper percentage of 95%.El objetivo del presente trabajo es disminuir el tiempo de proceso (Makespan e incrementar el tiempo de trabajo de las maquinas, diminuyendo el tiempo de ocio en ambientes de Job Shop, a través del diseño de una Hiper-heurística basada en colonia de hormigas y algoritmos genéticos. Este trabajo se desarrolla en dos etapas: en la primera se realiza la definición e identificación de una Hiper-heurística para la secuenciación de procesos en ambientes Job shop. En la segunda etapa, es mostrada la efectividad del sistema en la programación de la producción. En el proyecto de investigación, se seleccionó una empresa del sector metalmecánico, donde por medio de una combinación de colonia de hormigas y algoritmos genéticos, se programa la ruta óptima para un pedido, logrando la optimización o suboptimización de su respectivo tiempo total de proceso en un porcentaje superior al 95%.

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 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.

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.

A hybrid job-shop scheduling system

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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...

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.

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.

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

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.

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

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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.

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.

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.

USE OF EXCEL WORKSHEETS WITH USER-FRIENDLY INTERFACE IN BATCH PROCESS (PSBP TO MINIMIZE THE MAKESPAN

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Rony Peterson da Rocha

2014-01-01

Full Text Available In the chemical industry, the necessity for scheduling is becoming more pronounced, especially in batch production mode. Nowadays, planning industrial activities is a necessity for survival. Intense competition requires diversified products and delivery in accordance with the requirements of consumers. These activities require quick decision making and the lowest possible cost, through an efficient Production Scheduling. So, this work addresses the Permutation Flow Shop scheduling problem, characterized as Production Scheduling in Batch Process (PSBP, with the objective of minimizing the total time to complete the schedule (Makespan. A method to approach the problem of production scheduling is to turn it into Mixed Integer Linear Programming- MILP, and to solve it using commercial mathematical programming packages. In this study an electronic spreadsheet with user-friendly interface (ESUFI was developed in Microsoft Excel. The ease of manipulation of the ESUFI is quite evident, as with the use of VBA language a user-friendly interface could be created between the user and the spreadsheet itself. The results showed that it is possible to use the ESUFI for small problems.

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

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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.

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.

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.

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.

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.

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).

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

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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.

Job shop scheduling problem with late work criterion

Science.gov (United States)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.

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

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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.

Flowshop Scheduling Using a Network Approach | Oladeinde ...

African Journals Online (AJOL)

In this paper, a network based formulation of a permutation flow shop problem is presented. Two nuances of flow shop problems with different levels of complexity are solved using different approaches to the linear programming formulation. Key flow shop parameters inclosing makespan of the flow shop problems were ...

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

Algoritmo genético para reducir el makespan en un flow shop híbrido flexible con máquinas paralelas no relacionadas y tiempos de alistamiento dependientes de la secuencia

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Juan Camilo López-Vargas

2015-01-01

Full Text Available El artículo propone el algoritmo genético simple o estándar (AGS como enfoque de solución al problema de programación de produc - ción para un ambiente tipo flow shop híbrido flexible minimizando el makespan. La codificación del algoritmo propuesto permite obtener resultados con tiempos de cómputo bastante razonables y con un nivel de convergencia del makespan cercano al 2%, con mejores solu - ciones que un algoritmo alternativo diseñado para el mismo caso de programación de producción. A partir de los resultados obtenidos en el proceso de experimentación y del posterior análisis comparativo, se concluye que a partir del modelamiento más completo de las condiciones reales de producción, el algoritmo genético ejecuta la programación de producción reduciendo el tiempo máximo de procesamiento, o makespan. En futuros trabajos, el enfoque de investigación será la búsqueda de más escenarios alternativos de producción, con el fin de incrementar la aplicación de este tipo de herramientas y generar impacto en los entornos empresariales reales.

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

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

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

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Ling-Huey Su

2015-09-01

Full Text Available Purpose: The aims of this article are to develop a new mathematical formulation and a new heuristic for the problem of preemptive two-agent scheduling in open shops subject to machine maintenance and eligibility constraints. Design/methodology: Using the ideas of minimum cost flow network and constraint programming, a heuristic and a network based linear programming are proposed to solve the problem. Findings: Computational experiments show that the heuristic generates a good quality schedule with a deviation of 0.25% on average from the optimum and the network based linear programming model can solve problems up to 110 jobs combined with 10 machines without considering the constraint that each operation can be processed on at most one machine at a time. In order to satisfy this constraint, a time consuming Constraint Programming is proposed. For n = 80 and m = 10, the average execution time for the combined models (linear programming model combined with Constraint programming exceeds two hours. Therefore, the heuristic algorithm we developed is very efficient and is in need. Practical implications: Its practical implication occurs in TFT-LCD and E-paper manufacturing wherein units go through a series of diagnostic tests that do not have to be performed in any specified order. Originality/value: The main contribution of the article is to split the time horizon into many time intervals and use the dispatching rule for each time interval in the heuristic algorithm, and also to combine the minimum cost flow network with the Constraint Programming to solve the problem optimally. 

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

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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.

PENJADWALAN PRODUKSI MENGGUNAKAN ALGORITMA JADWAL NON DELAY UNTUK MEMINIMALKAN MAKESPAN STUDI KASUS DI CV. BIMA MEBEL

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Setyo Harto

2016-04-01

Full Text Available CV. Mebel Bima merupakan sebuah perusahaan yang bergerak dalam bidang pengerjaan kayu khususnya pembuatan berbagai model daun pintu dan kusen. Tipe aliran produksi di perusaaan adalah job shop dikarenakan pengerjaan setiap job memiliki aliran yang berbeda di setiap mesinnya. Penjadwalan produksi di perusahaan adalah diurutkan berdasarkan total waktu penyelesaian job terlama sampai yang terkecil. Permasalahan di perusahaan selama ini adalah besarnya makespan yang dihasilkan oleh penjadwalan dengan metode perusahaan sehingga perusahaan mengalami keterlambatan penyelesaian job dari waktu yang sudah ditetapkan sebelumnya. Berdasarkan masalah tersebut penelitian ini bertujuan untuk menentukan urutan pengerjaan job dengan makespan yang lebih kecil menggunakan algoritma jadwal non delay dengan prioritas SPT. Tahap-tahap dalam penelitian ini adalah dimulai dari observasi langsung di perusahaan, studi literatur, perumusan masalah, pengambilan data, pengolahan data, dan terakhir adalah pembandingan hasil penjadwalan. Metode penjadwalan produksi yang digunakan di perusahaan menghasilkan makespan sebesar 194,4 jam atau 25 hari kerja (1 hari terdapat 8 jam kerja, sedangkan usulan penjadwalan dengan menggunakan algoritma jadwal non delay menghasilkan makespan sebesar 168,79 jam atau 22 hari kerja, dengan demikian Penjadwalan dengan menggunakan algoritma jadwal non delay dapat menghemat total waktu pengerjaan sebesar 24,85 jam atau 3 hari kerja lebih 0,85 jam.

On non-permutation solutions to some two machine flow shop scheduling problems

NARCIS (Netherlands)

V. Strusevich (Vitaly); P.J. Zwaneveld (Peter)

1994-01-01

textabstractIn this paper, we study two versions of the two machine flow shop scheduling problem, where schedule length is to be minimized. First, we consider the two machine flow shop with setup, processing, and removal times separated. It is shown that an optimal solution need not be a permutation

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.

FLOW-SHOP SCHEDULING WITH MULTIPLE OPERATIONS AND TIME LAGS

NARCIS (Netherlands)

RIEZEBOS, J; GAALMAN, GJC; GUPTA, JND

A scheduling system is proposed and developed for a special type of flow shop. Ln this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j - 1 has

Scheduling job shop - A case study

Science.gov (United States)

Abas, M.; Abbas, A.; Khan, W. A.

2016-08-01

The scheduling in job shop is important for efficient utilization of machines in the manufacturing industry. There are number of algorithms available for scheduling of jobs which depend on machines tools, indirect consumables and jobs which are to be processed. In this paper a case study is presented for scheduling of jobs when parts are treated on available machines. Through time and motion study setup time and operation time are measured as total processing time for variety of products having different manufacturing processes. Based on due dates different level of priority are assigned to the jobs and the jobs are scheduled on the basis of priority. In view of the measured processing time, the times for processing of some new jobs are estimated and for efficient utilization of the machines available an algorithm is proposed and validated.

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.

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.

A Method of Flow-Shop Re-Scheduling Dealing with Variation of Productive Capacity

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Kenzo KURIHARA

2005-02-01

Full Text Available We can make optimum scheduling results using various methods that are proposed by many researchers. However, it is very difficult to process the works on time without delaying the schedule. There are two major causes that disturb the planned optimum schedules; they are (1the variation of productive capacity, and (2the variation of products' quantities themselves. In this paper, we deal with the former variation, or productive capacities, at flow-shop works. When production machines in a shop go out of order at flow-shops, we cannot continue to operate the productions and we have to stop the production line. To the contrary, we can continue to operate the shops even if some workers absent themselves. Of course, in this case, the production capacities become lower, because workers need to move from a machine to another to overcome the shortage of workers and some shops cannot be operated because of the worker shortage. We developed a new re-scheduling method based on Branch-and Bound method. We proposed an equation for calculating the lower bound for our Branch-and Bound method in a practical time. Some evaluation experiments are done using practical data of real flow-shop works. We compared our results with those of another simple scheduling method, and we confirmed the total production time of our result is shorter than that of another method by 4%.

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 ...

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.

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

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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.

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.

Multiagent scheduling method with earliness and tardiness objectives in flexible job shops.

Science.gov (United States)

Wu, Zuobao; Weng, Michael X

2005-04-01

Flexible job-shop scheduling problems are an important extension of the classical job-shop scheduling problems and present additional complexity. Such problems are mainly due to the existence of a considerable amount of overlapping capacities with modern machines. Classical scheduling methods are generally incapable of addressing such capacity overlapping. We propose a multiagent scheduling method with job earliness and tardiness objectives in a flexible job-shop environment. The earliness and tardiness objectives are consistent with the just-in-time production philosophy which has attracted significant attention in both industry and academic community. A new job-routing and sequencing mechanism is proposed. In this mechanism, two kinds of jobs are defined to distinguish jobs with one operation left from jobs with more than one operation left. Different criteria are proposed to route these two kinds of jobs. Job sequencing enables to hold a job that may be completed too early. Two heuristic algorithms for job sequencing are developed to deal with these two kinds of jobs. The computational experiments show that the proposed multiagent scheduling method significantly outperforms the existing scheduling methods in the literature. In addition, the proposed method is quite fast. In fact, the simulation time to find a complete schedule with over 2000 jobs on ten machines is less than 1.5 min.

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

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Eliana María González-Neira

2017-03-01

Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

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.

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.

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...

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.

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

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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.

Selective methodology of population dynamics for optimizing a multiobjective environment of job shop production

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Santiago Ruiz

2015-01-01

Full Text Available This paper develops a methodology based on population genetics to improve the performance of two or more variables in job shop production systems. The methodology applies a genetic algorithm with special features in the individual selection when they pass from generation to generation. In comparison with the FIFO method, the proposed methodology showed better results in the variables makespan, idle time and energy cost. When compared with NSGA II, the methodology did not showed relevant differences in makespan and idle time; however better performance was obtained in energy cost and, especially, in the number of required iterations to get the optimal makespan.

Lower bounds for online makespan minimization on a small number of related machines

Czech Academy of Sciences Publication Activity Database

Jeż, Łukasz; Schwartz, J.; Sgall, J.; Békési, J.

2013-01-01

Roč. 16, č. 5 (2013), s. 539-547 ISSN 1094-6136 R&D Projects: GA AV ČR IAA100190902; GA ČR GBP202/12/G061 Institutional support: RVO:67985840 Keywords : online algorithms * scheduling * makespan Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2013 http://link.springer.com/article/10.1007%2Fs10951-012-0288-7

JOB SHOP METHODOLOGY BASED ON AN ANT COLONY

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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 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.

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

Permutation flow-shop scheduling problem to optimize a quadratic objective function

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Ren, Tao; Zhao, Peng; Zhang, Da; Liu, Bingqian; Yuan, Huawei; Bai, Danyu

2017-09-01

A flow-shop scheduling model enables appropriate sequencing for each job and for processing on a set of machines in compliance with identical processing orders. The objective is to achieve a feasible schedule for optimizing a given criterion. Permutation is a special setting of the model in which the processing order of the jobs on the machines is identical for each subsequent step of processing. This article addresses the permutation flow-shop scheduling problem to minimize the criterion of total weighted quadratic completion time. With a probability hypothesis, the asymptotic optimality of the weighted shortest processing time schedule under a consistency condition (WSPT-CC) is proven for sufficiently large-scale problems. However, the worst case performance ratio of the WSPT-CC schedule is the square of the number of machines in certain situations. A discrete differential evolution algorithm, where a new crossover method with multiple-point insertion is used to improve the final outcome, is presented to obtain high-quality solutions for moderate-scale problems. A sequence-independent lower bound is designed for pruning in a branch-and-bound algorithm for small-scale problems. A set of random experiments demonstrates the performance of the lower bound and the effectiveness of the proposed algorithms.

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.

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...

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

African Journals Online (AJOL)

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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.

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.

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...

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.

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.

An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications

Energy Technology Data Exchange (ETDEWEB)

Vydyanathan, Naga; Krishnamoorthy, Sriram; Sabin, Gerald M.; Catalyurek, Umit V.; Kurc, Tahsin; Sadayappan, Ponnuswamy; Saltz, Joel H.

2009-08-01

Complex parallel applications can often be modeled as directed acyclic graphs of coarse-grained application-tasks with dependences. These applications exhibit both task- and data-parallelism, and combining these two (also called mixedparallelism), has been shown to be an effective model for their execution. In this paper, we present an algorithm to compute the appropriate mix of task- and data-parallelism required to minimize the parallel completion time (makespan) of these applications. In other words, our algorithm determines the set of tasks that should be run concurrently and the number of processors to be allocated to each task. The processor allocation and scheduling decisions are made in an integrated manner and are based on several factors such as the structure of the taskgraph, the runtime estimates and scalability characteristics of the tasks and the inter-task data communication volumes. A locality conscious scheduling strategy is used to improve inter-task data reuse. Evaluation through simulations and actual executions of task graphs derived from real applications as well as synthetic graphs shows that our algorithm consistently generates schedules with lower makespan as compared to CPR and CPA, two previously proposed scheduling algorithms. Our algorithm also produces schedules that have lower makespan than pure taskand data-parallel schedules. For task graphs with known optimal schedules or lower bounds on the makespan, our algorithm generates schedules that are closer to the optima than other scheduling approaches.

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, S.

1999-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, Sigrid

2002-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

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

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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.

Hybrid particle swarm optimization with Cauchy distribution for solving reentrant flexible flow shop with blocking constraint

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Chatnugrob Sangsawang

2016-06-01

Full Text Available This paper addresses a problem of the two-stage flexible flow shop with reentrant and blocking constraints in Hard Disk Drive Manufacturing. This problem can be formulated as a deterministic FFS|stage=2,rcrc, block|Cmax problem. In this study, adaptive Hybrid Particle Swarm Optimization with Cauchy distribution (HPSO was developed to solve the problem. The objective of this research is to find the sequences in order to minimize the makespan. To show their performances, computational experiments were performed on a number of test problems and the results are reported. Experimental results show that the proposed algorithms give better solutions than the classical Particle Swarm Optimization (PSO for all test problems. Additionally, the relative improvement (RI of the makespan solutions obtained by the proposed algorithms with respect to those of the current practice is performed in order to measure the quality of the makespan solutions generated by the proposed algorithms. The RI results show that the HPSO algorithm can improve the makespan solution by averages of 14.78%.

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.

Optimal Algorithms and a PTAS for Cost-Aware Scheduling

NARCIS (Netherlands)

L. Chen; N. Megow; R. Rischke; L. Stougie (Leen); J. Verschae

2015-01-01

htmlabstractWe consider a natural generalization of classical scheduling problems in which using a time unit for processing a job causes some time-dependent cost which must be paid in addition to the standard scheduling cost. We study the scheduling objectives of minimizing the makespan and the

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

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Noor Hasnah Moin

2015-01-01

Full Text Available The job shop scheduling problem (JSSP is one of the well-known hard combinatorial scheduling problems. This paper proposes a hybrid genetic algorithm with multiparents crossover for JSSP. The multiparents crossover operator known as extended precedence preservative crossover (EPPX is able to recombine more than two parents to generate a single new offspring distinguished from common crossover operators that recombine only two parents. This algorithm also embeds a schedule generation procedure to generate full-active schedule that satisfies precedence constraints in order to reduce the search space. Once a schedule is obtained, a neighborhood search is applied to exploit the search space for better solutions and to enhance the GA. This hybrid genetic algorithm is simulated on a set of benchmarks from the literatures and the results are compared with other approaches to ensure the sustainability of this algorithm in solving JSSP. The results suggest that the implementation of multiparents crossover produces competitive results.

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.

Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines

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Eliana Marcela Peña Tibaduiza

2017-01-01

Full Text Available Context: The flow shop hybrid problem with unrelated parallel machines has been less studied in the academia compared to the flow shop hybrid with identical processors. For this reason, there are few reports about the kind of application of this problem in industries. Method: A literature review of the state of the art on flow-shop scheduling problem was conducted by collecting and analyzing academic papers on several scientific databases. For this aim, a search query was constructed using keywords defining the problem and checking the inclusion of unrelated parallel machines in such definition; as a result, 50 papers were finally selected for this study. Results: A classification of the problem according to the characteristics of the production system was performed, also solution methods, constraints and objective functions commonly used are presented. Conclusions: An increasing trend is observed in studies of flow shop with multiple stages, but few are based on industry case-studies.

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

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Yingni Zhai

2014-10-01

Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

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.

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.

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 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

Multi-objective group scheduling with learning effect in the cellular manufacturing system

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Mohammad Taghi Taghavi-fard

2011-01-01

Full Text Available Group scheduling problem in cellular manufacturing systems consists of two major steps. Sequence of parts in each part-family and the sequence of part-family to enter the cell to be processed. This paper presents a new method for group scheduling problems in flow shop systems where it minimizes makespan (Cmax and total tardiness. In this paper, a position-based learning model in cellular manufacturing system is utilized where processing time for each part-family depends on the entrance sequence of that part. The problem of group scheduling is modeled by minimizing two objectives of position-based learning effect as well as the assumption of setup time depending on the sequence of parts-family. Since the proposed problem is NP-hard, two meta heuristic algorithms are presented based on genetic algorithm, namely: Non-dominated sorting genetic algorithm (NSGA-II and non-dominated rank genetic algorithm (NRGA. The algorithms are tested using randomly generated problems. The results include a set of Pareto solutions and three different evaluation criteria are used to compare the results. The results indicate that the proposed algorithms are quite efficient to solve the problem in a short computational time.

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

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

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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.

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.

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.

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.

An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules

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Angela Hsiang-Ling Chen

2014-09-01

Full Text Available Projects are an important part of our activities and regardless of their magnitude, scheduling is at the very core of every project. In an ideal world makespan minimization, which is the most commonly sought objective, would give us an advantage. However, every time we execute a project we have to deal with uncertainty; part of it coming from known sources and part remaining unknown until it affects us. For this reason, it is much more practical to focus on making our schedules robust, capable of handling uncertainty, and even to determine a range in which the project could be completed. In this paper we focus on an approach to determine such a range for the Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP, a widely researched, NP-complete problem, but without adding any subjective considerations to its estimation. We do this by using a concept well known in the domain of thermodynamics, entropy and a three-stage approach. First we use Artificial Bee Colony (ABC—an effective and powerful meta-heuristic—to determine a schedule with minimized makespan which serves as a lower bound. The second stage defines buffer times and creates an upper bound makespan using an entropy function, with the advantage over other methods that it only considers elements which are inherent to the schedule itself and does not introduce any subjectivity to the buffer time generation. In the last stage, we use the ABC algorithm with an objective function that seeks to maximize robustness while staying within the makespan boundaries defined previously and in some cases even below the lower boundary. We evaluate our approach with two different benchmarks sets: when using the PSPLIB for the MRCPSP benchmark set, the computational results indicate that it is possible to generate robust schedules which generally result in an increase of less than 10% of the best known solutions while increasing the robustness in at least 20% for practically every

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.

Clarifying Cutting and Sewing Processes with Due Windows Using an Effective Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Rong-Hwa Huang

2013-01-01

Full Text Available The cutting and sewing process is a traditional flow shop scheduling problem in the real world. This two-stage flexible flow shop is often commonly associated with manufacturing in the fashion and textiles industry. Many investigations have demonstrated that the ant colony optimization (ACO algorithm is effective and efficient for solving scheduling problems. This work applies a novel effective ant colony optimization (EACO algorithm to solve two-stage flexible flow shop scheduling problems and thereby minimize earliness, tardiness, and makespan. Computational results reveal that for both small and large problems, EACO is more effective and robust than both the particle swarm optimization (PSO algorithm and the ACO algorithm. Importantly, this work demonstrates that EACO can solve complex scheduling problems in an acceptable period of time.

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...

Sort-Mid tasks scheduling algorithm in grid computing.

Science.gov (United States)

Reda, Naglaa M; Tawfik, A; Marzok, Mohamed A; Khamis, Soheir M

2015-11-01

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.

Open|SpeedShop Graphical User Interface Technology, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose to create a new graphical user interface (GUI) for an existing parallel application performance and profiling tool, Open|SpeedShop. The current GUI has...

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.

Analyse af problemstillinger i moderne produktionssystemer ved hjælp af operationsanalytiske metoder

DEFF Research Database (Denmark)

Paulli, Jan

This PhD thesis consists of 6 volumes, the first being the above-mentioned Resumé. Vol. 2: Some Aspects of Applying Simulated Annealing and Tabu Search to the Quadratic Assignment Problem. Vol. 3: A Hierarchical Approach for the FMS Scheduling Problem Vol. 4: Solving the General Multiprocessor Job-shop...... Scheduling Problem (co-author: S. Dauzèrérès) Vol. 5: A Global Tabu Search Procedure for the General Multiprocessor Job-shop Scheduling Problem (co-author: S. Dauzère-Pérès) Vol. 6: Makespan Estimations in Flexible Manufacturing Systems (co-author: J.C. Fransoo, T.G. de Kok)...

The Associations between Yelp Online Reviews and Vape Shops Closing or Remaining Open One Year Later.

Science.gov (United States)

Kong, Grace; Unger, Jennifer; Baezconde-Garbanati, Lourdes; Sussman, Steve

2017-01-01

Vape shops are popular brick-and-mortar stores that sell e-cigarette products but are not understood well. Previous analysis of Yelp reviews of vape shops located in various ethnic neighborhoods in Los Angeles, California in 2014 identified characteristics of vape shop as delineated by consumers. In this study, we assessed the associations between these characteristics and vape shops going out of business in 2015. Content analysis of Yelp reviews of 72 vape shops in 2014 identified 1) general characteristics of the reviews/reviewers, 2) vape shop, staff, and marketing attributes, 3) physical environment, and 4) health claims. In 2015, in-person visits confirmed that 22% of these vape shops closed permanently. We analyzed whether characteristics/attributes identified in 2014 associated with stores remaining open (n = 56) or permanently closing (n = 16) in 2015. Univariate findings showed that open vape shops relative to closed shops had greater 1) number of reviews, 2) rebuilds/fixings, 3) ratings of staff attributes as "helpful/patient/respectful," and 4) report of the physical environment as "bar type." Bar type vape shops and those with rebuilding/fixing capabilities were associated with staying open, suggesting the popularity of these attributes. Yelp consumer reviews is a useful research tool to identify consumer-determined important sustaining attributes of vape shops and may be used to identify aspects of enduring shops that need regulations.

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...

Analysis of multi-stage open shop processing systems

NARCIS (Netherlands)

Eggermont, C.E.J.; Schrijver, A.; Woeginger, G.J.; Schwentick, T.; Dürr, C.

2011-01-01

We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe system states. We show that it is easy to recognize system states that can be reached from the initial state (where the

The Associations between Yelp Online Reviews and Vape Shops Closing or Remaining Open One Year Later

Science.gov (United States)

Kong, Grace; Unger, Jennifer; Baezconde-Garbanati, Lourdes; Sussman, Steve

2017-01-01

INTRODUCTION Vape shops are popular brick-and-mortar stores that sell e-cigarette products but are not understood well. Previous analysis of Yelp reviews of vape shops located in various ethnic neighborhoods in Los Angeles, California in 2014 identified characteristics of vape shop as delineated by consumers. In this study, we assessed the associations between these characteristics and vape shops going out of business in 2015. METHODS Content analysis of Yelp reviews of 72 vape shops in 2014 identified 1) general characteristics of the reviews/reviewers, 2) vape shop, staff, and marketing attributes, 3) physical environment, and 4) health claims. In 2015, in-person visits confirmed that 22% of these vape shops closed permanently. We analyzed whether characteristics/attributes identified in 2014 associated with stores remaining open (n = 56) or permanently closing (n = 16) in 2015. RESULTS Univariate findings showed that open vape shops relative to closed shops had greater 1) number of reviews, 2) rebuilds/fixings, 3) ratings of staff attributes as “helpful/patient/respectful,” and 4) report of the physical environment as “bar type.” CONCLUSIONS Bar type vape shops and those with rebuilding/fixing capabilities were associated with staying open, suggesting the popularity of these attributes. Yelp consumer reviews is a useful research tool to identify consumer-determined important sustaining attributes of vape shops and may be used to identify aspects of enduring shops that need regulations. PMID:29057379

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...

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

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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.

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.

Sort-Mid tasks scheduling algorithm in grid computing

Directory of Open Access Journals (Sweden)

Naglaa M. Reda

2015-11-01

Full Text Available Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.

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

Science.gov (United States)

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.

Cloud Service Scheduling Algorithm Research and Optimization

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Hongyan Cui

2017-01-01

Full Text Available We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS. In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO and a Genetic Algorithm (GA to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO are optimal.

TAGUCHI METHOD FOR THREE-STAGE ASSEMBLY FLOW SHOP SCHEDULING PROBLEM WITH BLOCKING AND SEQUENCE-DEPENDENT SET UP TIMES

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AREF MALEKI-DARONKOLAEI

2013-10-01

Full Text Available This article considers a three-stage assembly flowshop scheduling problem minimizing the weighted sum of mean completion time and makespan with sequence-dependent setup times at the first stage and blocking times between each stage. To tackle such an NP-hard, two meta-heuristic algorithms are presented. The novelty of our approach is to develop a variable neighborhood search algorithm (VNS and a well-known simulated annealing (SA for the problem. Furthermore, to enhance the performance of the (SA, its parameters are optimized by the use of Taguchi method, but to setting parameters of VNS just one parameter has been used without Taguchi. The computational results show that the proposed VNS is better in mean and standard deviation for all sizes of the problem than SA, but on the contrary about CPU Time SA outperforms VNS.

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.

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 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.

Science.gov (United States)

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.

Scheduling projects with multiskill learning effect.

Science.gov (United States)

Zha, Hong; Zhang, Lianying

2014-01-01

We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results show that the learning effect cannot be neglected in project scheduling. By means of determining the level of induced learning, the project manager can balance the project makespan with total cost.

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.

An optimal algorithm for preemptive on-line scheduling

NARCIS (Netherlands)

Chen, B.; Vliet, van A.; Woeginger, G.J.

1995-01-01

We investigate the problem of on-line scheduling jobs on m identical parallel machines where preemption is allowed. The goal is to minimize the makespan. We derive an approximation algorithm with worst-case guarantee mm/(mm - (m - 1)m) for every m 2, which increasingly tends to e/(e - 1) ˜ 1.58 as m

Multiobjective genetic algorithm approaches to project scheduling under risk

OpenAIRE

Kılıç, Murat; Kilic, Murat

2003-01-01

In this thesis, project scheduling under risk is chosen as the topic of research. Project scheduling under risk is defined as a biobjective decision problem and is formulated as a 0-1 integer mathematical programming model. In this biobjective formulation, one of the objectives is taken as the expected makespan minimization and the other is taken as the expected cost minimization. As the solution approach to this biobjective formulation genetic algorithm (GA) is chosen. After carefully invest...

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.

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.

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

Science.gov (United States)

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.

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.

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.

Adaptive Incremental Genetic Algorithm for Task Scheduling in Cloud Environments

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Kairong Duan

2018-05-01

Full Text Available Cloud computing is a new commercial model that enables customers to acquire large amounts of virtual resources on demand. Resources including hardware and software can be delivered as services and measured by specific usage of storage, processing, bandwidth, etc. In Cloud computing, task scheduling is a process of mapping cloud tasks to Virtual Machines (VMs. When binding the tasks to VMs, the scheduling strategy has an important influence on the efficiency of datacenter and related energy consumption. Although many traditional scheduling algorithms have been applied in various platforms, they may not work efficiently due to the large number of user requests, the variety of computation resources and complexity of Cloud environment. In this paper, we tackle the task scheduling problem which aims to minimize makespan by Genetic Algorithm (GA. We propose an incremental GA which has adaptive probabilities of crossover and mutation. The mutation and crossover rates change according to generations and also vary between individuals. Large numbers of tasks are randomly generated to simulate various scales of task scheduling problem in Cloud environment. Based on the instance types of Amazon EC2, we implemented virtual machines with different computing capacity on CloudSim. We compared the performance of the adaptive incremental GA with that of Standard GA, Min-Min, Max-Min , Simulated Annealing and Artificial Bee Colony Algorithm in finding the optimal scheme. Experimental results show that the proposed algorithm can achieve feasible solutions which have acceptable makespan with less computation time.

SOLVING FLOWSHOP SCHEDULING PROBLEMS USING A DISCRETE AFRICAN WILD DOG ALGORITHM

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M. K. Marichelvam

2013-04-01

Full Text Available The problem of m-machine permutation flowshop scheduling is considered in this paper. The objective is to minimize the makespan. The flowshop scheduling problem is a typical combinatorial optimization problem and has been proved to be strongly NP-hard. Hence, several heuristics and meta-heuristics were addressed by the researchers. In this paper, a discrete African wild dog algorithm is applied for solving the flowshop scheduling problems. Computational results using benchmark problems show that the proposed algorithm outperforms many other algorithms addressed in the literature.

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.

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.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....

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.

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.

Heuristic algorithms for the minmax regret flow-shop problem with interval processing times.

Science.gov (United States)

Ćwik, Michał; Józefczyk, Jerzy

2018-01-01

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.

Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

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Yi Han

2013-01-01

Full Text Available This paper presents a shuffled frog leaping algorithm (SFLA for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.

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

A non-permutation flowshop scheduling problem with lot streaming: A Mathematical model

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Daniel Rossit

2016-06-01

Full Text Available In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems. The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines. In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming. Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied. The benefits grow as the number of stages in the production process increases but reach a limit. Beyond a certain point, the division of jobs into additional sublots does not improve the solution.

Job shop scheduling model for non-identic machine with fixed delivery time to minimize tardiness

Science.gov (United States)

Kusuma, K. K.; Maruf, A.

2016-02-01

Scheduling non-identic machines problem with low utilization characteristic and fixed delivery time are frequent in manufacture industry. This paper propose a mathematical model to minimize total tardiness for non-identic machines in job shop environment. This model will be categorized as an integer linier programming model and using branch and bound algorithm as the solver method. We will use fixed delivery time as main constraint and different processing time to process a job. The result of this proposed model shows that the utilization of production machines can be increase with minimal tardiness using fixed delivery time as constraint.

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.

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.

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...

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.

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.

Downtown Study Centre: An Open-Ended ABE Program in an Urban Shopping Mall

Science.gov (United States)

Harrison, David

1976-01-01

Describes an adult basic education facility after one year of operation in an urban shopping mall in Nanaimo, British Columbia, Canada. The center is an informal open-ended classroom and advising center where part-time adult learners study an individualized curriculum. Summarizes the major findings of a program evaluation. (EM)

A Two-Level Task Scheduler on Multiple DSP System for OpenCL

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Li Tian

2014-04-01

Full Text Available This paper addresses the problem that multiple DSP system does not support OpenCL programming. With the compiler, runtime, and the kernel scheduler proposed, an OpenCL application becomes portable not only between multiple CPU and GPU, but also between embedded multiple DSP systems. Firstly, the LLVM compiler was imported for source-to-source translation in which the translated source was supported by CCS. Secondly, two-level schedulers were proposed to support efficient OpenCL kernel execution. The DSP/BIOS is used to schedule system level tasks such as interrupts and drivers; however, the synchronization mechanism resulted in heavy overhead during task switching. So we designed an efficient second level scheduler especially for OpenCL kernel work-item scheduling. The context switch process utilizes the 8 functional units and cross path links which was superior to DSP/BIOS in the aspect of task switching. Finally, dynamic loading and software managed CACHE were redesigned for OpenCL running on multiple DSP system. We evaluated the performance using some common OpenCL kernels from NVIDIA, AMD, NAS, and Parboil benchmarks. Experimental results show that the DSP OpenCL can efficiently exploit the computing resource of multiple cores.

7 CFR 29.9404 - Marketing area opening dates and marketing schedules.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Marketing area opening dates and marketing schedules... MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE COMMODITY....9404 Marketing area opening dates and marketing schedules. (a) The Flue-Cured Tobacco Advisory...

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...

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.

GLOA: A New Job Scheduling Algorithm for Grid Computing

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Zahra Pooranian

2013-03-01

Full Text Available The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA, to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

PENJADWALAN FLOWSHOP MENGGUNAKAN ALGORITMA NAWAZ ENSCORE HAM

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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 lower bound on deterministic online algorithms for scheduling on related machines without preemption

Czech Academy of Sciences Publication Activity Database

Ebenlendr, Tomáš; Sgall, J.

2015-01-01

Roč. 56, č. 1 (2015), s. 73-81 ISSN 1432-4350 R&D Projects: GA ČR GBP202/12/G061; GA AV ČR IAA100190902 Institutional support: RVO:67985840 Keywords : online algorithms * scheduling * makespan Subject RIV: IN - Informatics, Computer Science Impact factor: 0.719, year: 2015 http://link.springer.com/article/10.1007%2Fs00224-013-9451-6

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

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.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

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Maryam Mousavi

Full Text Available Flexible manufacturing system (FMS enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs. An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA, particle swarm optimization (PSO, and hybrid GA-PSO to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

Science.gov (United States)

Mousavi, Maryam; Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

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.

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

Directory of Open Access Journals (Sweden)

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.

Very Large-Scale Neighborhoods with Performance Guarantees for Minimizing Makespan on Parallel Machines

NARCIS (Netherlands)

Brueggemann, T.; Hurink, Johann L.; Vredeveld, T.; Woeginger, Gerhard

2006-01-01

We study the problem of minimizing the makespan on m parallel machines. We introduce a very large-scale neighborhood of exponential size (in the number of machines) that is based on a matching in a complete graph. The idea is to partition the jobs assigned to the same machine into two sets. This

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.

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

Science.gov (United States)

Abdullahi, Mohammed; Ngadi, Md Asri

2016-01-01

Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

Directory of Open Access Journals (Sweden)

Mohammed Abdullahi

Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

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 ...

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

Directory of Open Access Journals (Sweden)

K. Belkadi

2006-01-01

Full Text Available This paper addresses scheduling problems in hybrid flow shop-like systems with a migration parallel genetic algorithm (PGA_MIG. This parallel genetic algorithm model allows genetic diversity by the application of selection and reproduction mechanisms nearer to nature. The space structure of the population is modified by dividing it into disjoined subpopulations. From time to time, individuals are exchanged between the different subpopulations (migration. Influence of parameters and dedicated strategies are studied. These parameters are the number of independent subpopulations, the interconnection topology between subpopulations, the choice/replacement strategy of the migrant individuals, and the migration frequency. A comparison between the sequential and parallel version of genetic algorithm (GA is provided. This comparison relates to the quality of the solution and the execution time of the two versions. The efficiency of the parallel model highly depends on the parameters and especially on the migration frequency. In the same way this parallel model gives a significant improvement of computational time if it is implemented on a parallel architecture which offers an acceptable number of processors (as many processors as subpopulations.

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.

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.

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...

Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

Directory of Open Access Journals (Sweden)

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.

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

Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

Directory of Open Access Journals (Sweden)

Hesam Izakian

2009-07-01

Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

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.

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...

A comparison of mixed-integer linear programming models for workforce scheduling with position-dependent processing times

Science.gov (United States)

Moreno-Camacho, Carlos A.; Montoya-Torres, Jairo R.; Vélez-Gallego, Mario C.

2018-06-01

Only a few studies in the available scientific literature address the problem of having a group of workers that do not share identical levels of productivity during the planning horizon. This study considers a workforce scheduling problem in which the actual processing time is a function of the scheduling sequence to represent the decline in workers' performance, evaluating two classical performance measures separately: makespan and maximum tardiness. Several mathematical models are compared with each other to highlight the advantages of each approach. The mathematical models are tested with randomly generated instances available from a public e-library.

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

Science.gov (United States)

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.

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.

Integrating and scheduling an open set of static analyses

DEFF Research Database (Denmark)

Eichberg, Michael; Mezini, Mira; Kloppenburg, Sven

2006-01-01

to keep the set of analyses open. We propose an approach to integrating and scheduling an open set of static analyses which decouples the individual analyses and coordinates the analysis executions such that the overall time and space consumption is minimized. The approach has been implemented...... for the Eclipse IDE and has been used to integrate a wide range of analyses such as finding bug patterns, detecting violations of design guidelines, or type system extensions for Java....

Multi-objective ACO algorithms to minimise the makespan and the total rejection cost on BPMs with arbitrary job weights

Science.gov (United States)

Jia, Zhao-hong; Pei, Ming-li; Leung, Joseph Y.-T.

2017-12-01

In this paper, we investigate the batch-scheduling problem with rejection on parallel machines with non-identical job sizes and arbitrary job-rejected weights. If a job is rejected, the corresponding penalty has to be paid. Our objective is to minimise the makespan of the processed jobs and the total rejection cost of the rejected jobs. Based on the selected multi-objective optimisation approaches, two problems, P1 and P2, are considered. In P1, the two objectives are linearly combined into one single objective. In P2, the two objectives are simultaneously minimised and the Pareto non-dominated solution set is to be found. Based on the ant colony optimisation (ACO), two algorithms, called LACO and PACO, are proposed to address the two problems, respectively. Two different objective-oriented pheromone matrices and heuristic information are designed. Additionally, a local optimisation algorithm is adopted to improve the solution quality. Finally, simulated experiments are conducted, and the comparative results verify the effectiveness and efficiency of the proposed algorithms, especially on large-scale instances.

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

Directory of Open Access Journals (Sweden)

S. Dousthaghi

2012-08-01

Full Text Available This paper considers an economic lot and delivery scheduling problem (ELDSP in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP approach. In this paper, a mixed-integer nonlinear programming (MINLP model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples.

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

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 ...

Short-term scheduling of an open-pit mine with multiple objectives

Science.gov (United States)

Blom, Michelle; Pearce, Adrian R.; Stuckey, Peter J.

2017-05-01

This article presents a novel algorithm for the generation of multiple short-term production schedules for an open-pit mine, in which several objectives, of varying priority, characterize the quality of each solution. A short-term schedule selects regions of a mine site, known as 'blocks', to be extracted in each week of a planning horizon (typically spanning 13 weeks). Existing tools for constructing these schedules use greedy heuristics, with little optimization. To construct a single schedule in which infrastructure is sufficiently utilized, with production grades consistently close to a desired target, a planner must often run these heuristics many times, adjusting parameters after each iteration. A planner's intuition and experience can evaluate the relative quality and mineability of different schedules in a way that is difficult to automate. Of interest to a short-term planner is the generation of multiple schedules, extracting available ore and waste in varying sequences, which can then be manually compared. This article presents a tool in which multiple, diverse, short-term schedules are constructed, meeting a range of common objectives without the need for iterative parameter adjustment.

E2023 ITEA SHOPS Collection of information on electricity. Part 2/2; E2023 ITEA SHOPS - Saehkoeenergiatiedon keruu. Osa 2/2

Energy Technology Data Exchange (ETDEWEB)

Savelius, A. [Enermet Oy, Jyskae (Finland)

2006-12-19

The Smart Home Payment Services (SHOPS) project aims at supporting those advanced functions for the payment of home utilities leading to innovative solutions and opening the door to a new generation of services. The main project innovation is a proposed open, cross-domain, platform-neutral system for describing services (e.g. Automatic Meter Reading) provided by devices and applications. The system description model elaborated by SHOPS combined existing standards and extend their reach. The technology developed will provide a high-level design base, reducing the cost and delay of new devices and applications creation. SHOPS architecture is based on advanced network and web technologies while careful attention is paid to data security and user privacy. (orig.)

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…

A hybrid electromagnetism-like algorithm for a multi-mode resource-constrained project scheduling problem

Directory of Open Access Journals (Sweden)

Mohammad Hossein Sadeghi

2013-08-01

Full Text Available In this paper, two different sub-problems are considered to solve a resource constrained project scheduling problem (RCPSP, namely i assignment of modes to tasks and ii scheduling of these tasks in order to minimize the makespan of the project. The modified electromagnetism-like algorithm deals with the first problem to create an assignment of modes to activities. This list is used to generate a project schedule. When a new assignment is made, it is necessary to fix all mode dependent requirements of the project activities and to generate a random schedule with the serial SGS method. A local search will optimize the sequence of the activities. Also in this paper, a new penalty function has been proposed for solutions which are infeasible with respect to non-renewable resources. Performance of the proposed algorithm has been compared with the best algorithms published so far on the basis of CPU time and number of generated schedules stopping criteria. Reported results indicate excellent performance of the algorithm.

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.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...

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.

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

Science.gov (United States)

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

Science.gov (United States)

Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

2017-01-01

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

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

ENHANCED HYBRID PSO – ACO ALGORITHM FOR GRID SCHEDULING

Directory of Open Access Journals (Sweden)

P. Mathiyalagan

2010-07-01

Full Text Available Grid computing is a high performance computing environment to solve larger scale computational demands. Grid computing contains resource management, task scheduling, security problems, information management and so on. Task scheduling is a fundamental issue in achieving high performance in grid computing systems. A computational GRID is typically heterogeneous in the sense that it combines clusters of varying sizes, and different clusters typically contains processing elements with different level of performance. In this, heuristic approaches based on particle swarm optimization and ant colony optimization algorithms are adopted for solving task scheduling problems in grid environment. Particle Swarm Optimization (PSO is one of the latest evolutionary optimization techniques by nature. It has the better ability of global searching and has been successfully applied to many areas such as, neural network training etc. Due to the linear decreasing of inertia weight in PSO the convergence rate becomes faster, which leads to the minimal makespan time when used for scheduling. To make the convergence rate faster, the PSO algorithm is improved by modifying the inertia parameter, such that it produces better performance and gives an optimized result. The ACO algorithm is improved by modifying the pheromone updating rule. ACO algorithm is hybridized with PSO algorithm for efficient result and better convergence in PSO algorithm.

Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

Directory of Open Access Journals (Sweden)

Bo Cheng

2016-08-01

Full Text Available Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1 It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2 It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

Science.gov (United States)

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

Science.gov (United States)

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

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....

Evolutionary approaches for scheduling a flexible manufacturing system with automated guided vehicles and robots

Directory of Open Access Journals (Sweden)

Ramaraj Natarajan

2012-08-01

Full Text Available This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV and two robots in a Flexible Manufacturing System (FMS formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA and Artificial Immune System (AIS algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.

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 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.

Optimal Rules for Single Machine Scheduling with Stochastic Breakdowns

Directory of Open Access Journals (Sweden)

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.

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 ...

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...

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.

Personality Traits as Predictors of Shopping Motivations and Behaviors: A Canonical Correlation Analysis

Directory of Open Access Journals (Sweden)

Ali Gohary

2014-10-01

Full Text Available This study examines the relationship between Big Five personality traits with shopping motivation variables consisting of compulsive and impulsive buying, hedonic and utilitarian shopping values. Two hundred forty seven college students were recruited to participate in this research. Bivariate correlation demonstrates an overlap between personality traits; consequently, canonical correlation was performed to prevent this phenomenon. The results of multiple regression analysis suggested conscientiousness, neuroticism and openness as predictors of compulsive buying, impulsive buying and utilitarian shopping values. In addition, the results showed significant differences between males and females on conscientiousness, neuroticism, openness, compulsive buying and hedonic shopping value. Besides, using hierarchical regression analysis, we examined sex as moderator between Big Five personality traits and shopping variables, but we didn’t find sufficient evidence to prove it.

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).

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.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

Science.gov (United States)

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

E-Commerce Performance. Shopping Cart Key Performance Indicators

Directory of Open Access Journals (Sweden)

Mihaela I. MUNTEAN

2016-01-01

Full Text Available In an e-commerce performance framework is important to identify the key performance indicators that measure success and together provide the greatest context into the business perfor-mance. Shopping carts are an essential part of ecommerce, a minimal set of key performance indicators being the subject of our debate. The theoretical approach is sustained by a case study, an e-shop implemented using PHP and MySQL, for simulating main business processes within the considered performance framework. Our approach opens a perspective for future research using additional indicators in order to properly evaluate the global performance of any e-shop.

A Hybrid Metaheuristic for Multi-Objective Scientific Workflow Scheduling in a Cloud Environment

Directory of Open Access Journals (Sweden)

Nazia Anwar

2018-03-01

Full Text Available Cloud computing has emerged as a high-performance computing environment with a large pool of abstracted, virtualized, flexible, and on-demand resources and services. Scheduling of scientific workflows in a distributed environment is a well-known NP-complete problem and therefore intractable with exact solutions. It becomes even more challenging in the cloud computing platform due to its dynamic and heterogeneous nature. The aim of this study is to optimize multi-objective scheduling of scientific workflows in a cloud computing environment based on the proposed metaheuristic-based algorithm, Hybrid Bio-inspired Metaheuristic for Multi-objective Optimization (HBMMO. The strong global exploration ability of the nature-inspired metaheuristic Symbiotic Organisms Search (SOS is enhanced by involving an efficient list-scheduling heuristic, Predict Earliest Finish Time (PEFT, in the proposed algorithm to obtain better convergence and diversity of the approximate Pareto front in terms of reduced makespan, minimized cost, and efficient load balance of the Virtual Machines (VMs. The experiments using different scientific workflow applications highlight the effectiveness, practicality, and better performance of the proposed algorithm.

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 ...

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.

Position Paper: OpenMP scheduling on ARM big.LITTLE architecture

OpenAIRE

Butko , Anastasiia; Bessad , Louisa; Novo , David; Bruguier , Florent; Gamatié , Abdoulaye; Sassatelli , Gilles; Torres , Lionel; Robert , Michel

2016-01-01

International audience; Single-ISA heterogeneous multicore systems are emerging as a promising direction to achieve a more suitable balance between performance and energy consumption. However, a proper utilization of these architectures is essential to reach the energy benefits. In this paper, we demonstrate the ineffectiveness of popular OpenMP scheduling policies executing Rodinia benchmark on the Exynos 5 Octa (5422) SoC, which integrates the ARM big.LITTLE architecture.

40 CFR 256.27 - Recommendation for schedules leading to compliance with the prohibition of open dumping.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Recommendation for schedules leading to compliance with the prohibition of open dumping. 256.27 Section 256.27 Protection of Environment... SOLID WASTE MANAGEMENT PLANS Solid Waste Disposal Programs § 256.27 Recommendation for schedules leading...

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....

Lower Bounds and Semi On-line Multiprocessor Scheduling

Directory of Open Access Journals (Sweden)

T.C. Edwin Cheng

2003-10-01

Full Text Available We are given a set of identical machines and a sequence of jobs from which we know the sum of the job weights in advance. The jobs have to be assigned on-line to one of the machines and the objective is to minimize the makespan. An algorithm with performance ratio 1.6 and a lower bound of 1.5 is presented. This improves recent results by Azar and Regev who published an algorithm with performance ratio 1.625 for the less general problem that the optimal makespan is known in advance.

Evaluation of Meta scheduler Architectures and Task assignment Policies for High throughput Computing

CERN Document Server

Caron, E; Tsaregorodtsev, A Yu

2006-01-01

In this paper we present a model and simulator for many clusters of heterogeneous PCs belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. These studies indicate that the simulator is consistent. Next, we do the comparison with a real batch system and we obtain an average error of 10.5\\% for the response time and 12\\% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called \\dirac in a high throughput context. We justify our decentralized, adaptive and opportunistic approach in comparison to a centralized approach in such a context.

A FAST AND ELITIST BI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR SCHEDULING INDEPENDENT TASKS ON HETEROGENEOUS SYSTEMS

Directory of Open Access Journals (Sweden)

G.Subashini

2010-07-01

Full Text Available To meet the increasing computational demands, geographically distributed resources need to be logically coupled to make them work as a unified resource. In analyzing the performance of such distributed heterogeneous computing systems scheduling a set of tasks to the available set of resources for execution is highly important. Task scheduling being an NP-complete problem, use of metaheuristics is more appropriate in obtaining optimal solutions. Schedules thus obtained can be evaluated using several criteria that may conflict with one another which require multi objective problem formulation. This paper investigates the application of an elitist Nondominated Sorting Genetic Algorithm (NSGA-II, to efficiently schedule a set of independent tasks in a heterogeneous distributed computing system. The objectives considered in this paper include minimizing makespan and average flowtime simultaneously. The implementation of NSGA-II algorithm and Weighted-Sum Genetic Algorithm (WSGA has been tested on benchmark instances for distributed heterogeneous systems. As NSGA-II generates a set of Pareto optimal solutions, to verify the effectiveness of NSGA-II over WSGA a fuzzy based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set.

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.

Census tract correlates of vape shop locations in New Jersey.

Science.gov (United States)

Giovenco, Daniel P; Duncan, Dustin T; Coups, Elliot J; Lewis, M Jane; Delnevo, Cristine D

2016-07-01

Vape shops are opening across the USA, but little is known about the types of neighborhoods where they are located. This study explores community-level predictors of vape shop locations in New Jersey, USA. Vape shops were identified in July 2015 using a validated systematic online search protocol and geocoded using Google Earth Pro. Multivariable logistic regression identified demographic and other predictors of vape shop presence at the census tract level. Tobacco outlet density was consistently associated with higher odds of vape shop presence after adjusting for covariates (pretail were negatively associated with vapor outlets. Census tracts with a higher proportion of non-Hispanic black residents had significantly lower odds of having a vape shop (β=-0.03, pretail is high, but where fewer racial minorities live. The retail environment may communicate social norms regarding vaping and ultimately influence use behaviors of community residents. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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.

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

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.

Locality-Aware Task Scheduling and Data Distribution for OpenMP Programs on NUMA Systems and Manycore Processors

Directory of Open Access Journals (Sweden)

Ananya Muddukrishna

2015-01-01

Full Text Available Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers.

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 ...

Open | SpeedShop: An Open Source Infrastructure for Parallel Performance Analysis

Directory of Open Access Journals (Sweden)

Martin Schulz

2008-01-01

Full Text Available Over the last decades a large number of performance tools has been developed to analyze and optimize high performance applications. Their acceptance by end users, however, has been slow: each tool alone is often limited in scope and comes with widely varying interfaces and workflow constraints, requiring different changes in the often complex build and execution infrastructure of the target application. We started the Open | SpeedShop project about 3 years ago to overcome these limitations and provide efficient, easy to apply, and integrated performance analysis for parallel systems. Open | SpeedShop has two different faces: it provides an interoperable tool set covering the most common analysis steps as well as a comprehensive plugin infrastructure for building new tools. In both cases, the tools can be deployed to large scale parallel applications using DPCL/Dyninst for distributed binary instrumentation. Further, all tools developed within or on top of Open | SpeedShop are accessible through multiple fully equivalent interfaces including an easy-to-use GUI as well as an interactive command line interface reducing the usage threshold for those tools.

PENJADWALAN FLOWSHOP DENGAN MENGGUNAKAN SIMULATED ANNEALING

Directory of Open Access Journals (Sweden)

Muhammad Firdaus

2015-04-01

Full Text Available This article apply a machine scheduling technique, named Simulate Annealing (SA to schedule 8 jobs and 5 machines to minimize makespan. A flowshop production flow is chosen as a case study to collect data and attempted to reduce jobs’ makespan. This article also does a sensitivity analysis to explore the implication of the changes of SA parameters as temperature. The results shows that the completion time of the jobs uses SA algoritm can decrease the completion time of the jobs, about 5 hours lower than the existing method. Moreover, total idle time of the machines is also reduced by 2.18 per cent using SA technique. Based on the sensitivity analysis, it indicates that there is a significant relationship between the changes of temperatures and makespan and computation time.

Artificial intelligence for the CTA Observatory scheduler

Science.gov (United States)

Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

2014-08-01

The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint

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.

Aplicación de un algoritmo ACO al problema de taller de flujo de permutación con tiempos de preparación dependientes de la secuencia y minimización de makespan An ant colony algorithm for the permutation flowshop with sequence dependent setup times and makespan minimization

Directory of Open Access Journals (Sweden)

Eduardo Salazar Hornig

2011-08-01

Full Text Available En este trabajo se estudió el problema de secuenciamiento de trabajos en el taller de flujo de permutación con tiempos de preparación dependientes de la secuencia y minimización de makespan. Para ello se propuso un algoritmo de optimización mediante colonia de hormigas (ACO, llevando el problema original a una estructura semejante al problema del vendedor viajero TSP (Traveling Salesman Problem asimétrico, utilizado para su evaluación problemas propuestos en la literatura y se compara con una adaptación de la heurística NEH (Nawaz-Enscore-Ham. Posteriormente se aplica una búsqueda en vecindad a la solución obtenida tanto por ACO como NEH.This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic.

STUDI PERBANDINGAN PERFORMANCE ALGORITMA HEURISTIK POUR TERHADAP MIXED INTEGER PROGRAMMING DALAM MENYELESAIKAN PENJADWALAN FLOWSHOP

Directory of Open Access Journals (Sweden)

Tessa Vanina Soetanto

2004-01-01

Full Text Available This paper presents a study about new heuristic algorithm performance compared to Mixed Integer Programming (MIP method in solving flowshop scheduling problem to reach minimum makespan. Performance appraisal is based on Efficiency Index (EI, Relative Error (RE and Elapsed Runtime. Abstract in Bahasa Indonesia : Makalah ini menyajikan penelitian tentang performance algoritma heuristik Pour terhadap metode Mixed Integer Programming (MIP dalam menyelesaikan masalah penjadwalan flowshop dengan tujuan meminimalkan makespan. Penilaian performance dilakukan berdasarkan nilai Efficiency Index (EI, Relative Error (RE dan Elapsed Runtime. Kata kunci: flowshop, makespan, algoritma heuristik Pour, Mixed Integer Programming.

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.

Online Shopping Woes

Institute of Scientific and Technical Information of China (English)

Hou Weili

2011-01-01

AS a frequent online shopper,Zhou Fangjie,a 28-year-old white-collar worker,was annoyed when she could not open Hanyidushe,an online shop selling Korean-style clothing on Taobao Mall.Her experience resulted from the online protest initiated by small vendors on Taobao Mall,China's largest business to consumer online platform.Thousands of small vendors started the protest against larger established vendors by discrediting them through False orders,forming an anti-Taobao Union and setting up a chat room to devise ways to disrupt operations on Taobao Mall.

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.

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.

Shopping versus Nature? An Exploratory Study of Everyday Experiences.

Science.gov (United States)

Craig, Tony P; Fischer, Anke; Lorenzo-Arribas, Altea

2018-01-01

Although a growing volume of empirical research shows that being in nature is important for human wellbeing, the definition of what constitutes an 'experience in nature,' and how this is different from other types of experiences, is very often left implied. In this paper we contrast everyday experiences involving nature with a category of everyday experience in which most people regularly partake. We present an exploratory study in which people ( N = 357) were explicitly asked to describe a memory they had of an everyday 'experience which involved nature,' as well as an everyday 'experience which involved shopping.' The open-ended responses to these questions were analyzed both quantitatively and qualitatively. Nature experiences were generally found to be more positive than shopping experiences, and they were more likely to be rated as 'peaceful' and 'active' compared to shopping experiences. Follow-up analyses indicate a significant interaction between experience category (nature or shopping), and the relationship between connectedness to nature and the amount of pleasure associated with that experience: The more strongly connected to nature a respondent was, the larger the disparity between the pleasantness of the shopping experience and that of the experience in nature tended to be.

Shopping for Jobs: Mall Internship Program Opens Doors for HVAC Students.

Science.gov (United States)

Nolot, Terry

1995-01-01

Ivy Tech State College uses River Falls, a shopping mall, as an enormous heating, ventilation, and air conditioning laboratory. Students spend Saturdays working with full-time technicians getting invaluable training and experience. Students see the program as a professional opportunity and a direct route to jobs. (JOW)

Nudging Leads Consumers In Colorado To Shop But Not Switch ACA Marketplace Plans.

Science.gov (United States)

Marzilli Ericson, Keith M; Kingsdale, Jon; Layton, Tim; Sacarny, Adam

2017-02-01

The Affordable Care Act (ACA) dramatically expanded the use of regulated marketplaces in health insurance, but consumers often fail to shop for plans during open enrollment periods. Typically these consumers are automatically reenrolled in their old plans, which potentially exposes them to unexpected increases in their insurance premiums and cost sharing. We conducted a randomized intervention to encourage enrollees in an ACA Marketplace to shop for plans. We tested the effect of letters and e-mails with personalized information about the savings on insurance premiums that they could realize from switching plans and the effect of generic communications that simply emphasized the possibility of saving. The personalized and generic messages both increased shopping on the Marketplace's website by 23 percent, but neither type of message had a significant effect on plan switching. These findings show that simple "nudges" with even generic information can promote shopping in health insurance marketplaces, but whether they can lead to switching remains an open question. Project HOPE—The People-to-People Health Foundation, Inc.

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

Labor construction trends

International Nuclear Information System (INIS)

McCall, H.W.

1976-01-01

The increasing costs and schedule delays being experienced in construction projects have led companies to look for alternatives to their present methods of expansion. One of the facets being evaluated is the construction labor posture. As a result, more companies are employing open shop contractors. Certain benefits can be realized by open shop construction. Productivity, in terms of the time required and overall costs, is definitely improved at no sacrifice in quality. Before an owner decides to build a project open shop, however, he must be fully aware of the pro's and con's of both types of labor posture. He must know to select a capable open shop contractor and he must realize his obligations for a successful open shop program

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.

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

Directory of Open Access Journals (Sweden)

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.

Shopping versus Nature? An Exploratory Study of Everyday Experiences

Directory of Open Access Journals (Sweden)

Tony P. Craig

2018-01-01

Full Text Available Although a growing volume of empirical research shows that being in nature is important for human wellbeing, the definition of what constitutes an ‘experience in nature,’ and how this is different from other types of experiences, is very often left implied. In this paper we contrast everyday experiences involving nature with a category of everyday experience in which most people regularly partake. We present an exploratory study in which people (N = 357 were explicitly asked to describe a memory they had of an everyday ‘experience which involved nature,’ as well as an everyday ‘experience which involved shopping.’ The open-ended responses to these questions were analyzed both quantitatively and qualitatively. Nature experiences were generally found to be more positive than shopping experiences, and they were more likely to be rated as ‘peaceful’ and ‘active’ compared to shopping experiences. Follow-up analyses indicate a significant interaction between experience category (nature or shopping, and the relationship between connectedness to nature and the amount of pleasure associated with that experience: The more strongly connected to nature a respondent was, the larger the disparity between the pleasantness of the shopping experience and that of the experience in nature tended to be.

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

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.

Inter-terminal transfer between port terminals. A continuous mathematical programming model to optimize scheduling and deployment of transport units

Energy Technology Data Exchange (ETDEWEB)

Morales Fusco, P.; Pedrielli, G.; Zhou, C.; Hay Lee, L.; Peng Chew, E.

2016-07-01

In most large port cities, the challenge of inter-terminal transfers (ITT) prevails due to the long distance between multiple terminals. The quantity of containers requiring movement between terminals as they connect from pre-carrier to on-carrier is increasing with the formation of the mega-alliances. The paper proposes a continuous time mathematical programming model to optimize the deployment and schedule of trucks and barges to minimize the number of operating transporters, their makespan, costs and the distance travelled by the containers by choosing the right combination of transporters and container movements while fulfilling time window restrictions imposed on reception of the containers. A multi-step routing problem is developed where transporters can travel from one terminal to another and/or load or unload containers from a specific batch at each step. The model proves successful in identifying the costless schedule and means of transportation. And a sensibility analysis over the parameters used is provided. (Author)

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....

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems.

Directory of Open Access Journals (Sweden)

Hajara Idris

Full Text Available The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user's Quality of Service (QoS requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user's QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time.

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...

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

Science.gov (United States)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

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.

Parallel patterns determination in solving cyclic flow shop problem with setups

Directory of Open Access Journals (Sweden)

Bożejko Wojciech

2017-06-01

Full Text Available The subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP. We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.

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.

How Traumatic Violence Permanently Changes Shopping Behavior

Directory of Open Access Journals (Sweden)

Ozge Sigirci

2016-09-01

Full Text Available Traumatic experiences – such as combat, living in a conflict country or war-torn nation, or experiencing a violent crime or natural disaster – change social relationships and may also influence a life-time of consumer relationships with brands and shopping. Our focus on this previously overlooked area is centered on an analysis of the long-term shopping habits of 355 combat veterans. We show that those who experienced heavy trauma (e.g., heavy combat exhibited similar disconnection from brands as others have experienced in social relationships. They became more transactional in that they were more open to switching brands, to trying new products, and buying the least expensive alternative (p < 0.01. In contrast, those who had experienced a light trauma were more influenced by ads and more open to buying brands even when they cost more (p < 0.00. Trauma, such as combat, may change one’s decision horizon. Functionality and price become more important, which is consistent with the idea that they are more focused on the present moment than on building on the past or saving for the future.

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...

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

Science.gov (United States)

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

Science.gov (United States)

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

PERBANDINGAN KINERJA ALGORITMA GENETIKA DAN SIMULATED ANNEALING UNTUK MASALAH MULTIPLE OBJECTIVE PADA PENJADWALAN FLOWSHOP

Directory of Open Access Journals (Sweden)

I Gede Agus Widyadana

2002-01-01

Full Text Available The research is focused on comparing Genetics algorithm and Simulated Annealing in the term of performa and processing time. The main purpose is to find out performance both of the algorithm to solve minimizing makespan and total flowtime in a particular flowshop system. Performances of the algorithms are found by simulating problems with variation of jobs and machines combination. The result show the Simulated Annealing is much better than the Genetics up to 90%. The Genetics, however, only had score in processing time, but the trend that plotted suggest that in problems with lots of jobs and lots of machines, the Simulated Annealing will run much faster than the Genetics. Abstract in Bahasa Indonesia : Penelitian ini difokuskan pada pembandingan algoritma Genetika dan Simulated Annealing ditinjau dari aspek performa dan waktu proses. Tujuannya adalah untuk melihat kemampuan dua algoritma tersebut untuk menyelesaikan problem-problem penjadwalan flow shop dengan kriteria minimasi makespan dan total flowtime. Kemampuan kedua algoritma tersebut dilihat dengan melakukan simulasi yang dilakukan pada kombinasi-kombinasi job dan mesin yang berbeda-beda. Hasil simulasi menunjukan algoritma Simulated Annealing lebih unggul dari algoritma Genetika hingga 90%, algoritma Genetika hanya unggul pada waktu proses saja, namun dengan tren waktu proses yang terbentuk, diyakini pada problem dengan kombinasi job dan mesin yang banyak, algoritma Simulated Annealing dapat lebih cepat daripada algoritma Genetika. Kata kunci: Algoritma Genetika, Simulated Annealing, flow shop, makespan, total flowtime.

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...

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.

Double Girder Bridge Crane with Double Cycling: Scheduling Strategy and Performance Evaluation

Directory of Open Access Journals (Sweden)

Dandan Wang

2014-01-01

Full Text Available This paper introduces a novel quay crane design, double girder bridge crane (DGBC. DGBC is capable of handling containers of two adjacent bays simultaneously, avoiding crane collisions, saving travelling and reposition cost, and eventually improving terminal efficiency. This problem is formulated as a resource-constrained project scheduling with objective to minimize the maximum completion time. A two-stage heuristic algorithm is proposed in which an operating sequences on each bay is obtained by double cycling, and the integrated timetable for both bays is constructed by solving resource conflicts using the proposed minimum cost strategy. We examine effectiveness and performance of applying DGBC with double cycling. A case study is presented to illustrate how DGBC works with the two-stage method. Three extreme cases with respective conflict types are investigated to develop the performance bounds of DGBC with double cycling. The results show that DGBC can significantly improve terminal productivity, and outperforms single girder crane in both makespan and the lift operation percentage. The highest DGBC efficiency does not require maximum double cycles in two bay schedules; rather the integrated timetable for two bays is the main contribution to the DGBC performance as it yields better cooperation between two spreaders and the driver.

A Mathematical Model for Scheduling a Batch Processing Machine with Multiple Incompatible Job Families, Non-identical Job dimensions, Non-identical Job sizes, Non-agreeable release times and due dates

International Nuclear Information System (INIS)

Ramasubramaniam, M; Mathirajan, M

2013-01-01

The paper addresses the problem scheduling a batch processing machine with multiple incompatible job families, non-identical job dimensions, non-identical job sizes and non-agreeable release dates to minimize makespan. The research problem is solved by proposing a mixed integer programming model that appropriately takes into account the parameters considered in the problem. The proposed is validated using a numerical example. The experiment conducted show that the model can pose significant difficulties in solving the large scale instances. The paper concludes by giving the scope for future work and some alternative approaches one can use for solving these class of problems.

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 ...

Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids

Directory of Open Access Journals (Sweden)

M. Christobel

2015-01-01

Full Text Available One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO algorithm based on the particle’s best position (pbDPSO and global best position (gbDPSO is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF and First Come First Serve (FCFS algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER and Dynamic Voltage Scaling (DVS were used in the proposed DPSO algorithm.

Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids

Science.gov (United States)

Christobel, M.; Tamil Selvi, S.; Benedict, Shajulin

2015-01-01

One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO) algorithm based on the particle's best position (pbDPSO) and global best position (gbDPSO) is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF) and First Come First Serve (FCFS) algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER) and Dynamic Voltage Scaling (DVS) were used in the proposed DPSO algorithm. PMID:26075296

An imperialist competitive algorithm for solving the production scheduling problem in open pit mine

Directory of Open Access Journals (Sweden)

Mojtaba Mokhtarian Asl

2016-06-01

Full Text Available Production scheduling (planning of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem.

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.

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|SpeedShop

Energy Technology Data Exchange (ETDEWEB)

Galarowicz, James E. [Krell Institute, Ames, IA (United States); Miller, Barton P. [Univ. of Wisconsin, Madison, WI (United States). Computer Sciences Dept.; Hollingsworth, Jeffrey K. [Univ. of Maryland, College Park, MD (United States). Computer Sciences Dept.; Roth, Philip [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Future Technologies Group, Computer Science and Math Division; Schulz, Martin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing (CASC)

2013-12-19

In this project we created a community tool infrastructure for program development tools targeting Petascale class machines and beyond. This includes tools for performance analysis, debugging, and correctness tools, as well as tuning and optimization frameworks. The developed infrastructure provides a comprehensive and extensible set of individual tool building components. We started with the basic elements necessary across all tools in such an infrastructure followed by a set of generic core modules that allow a comprehensive performance analysis at scale. Further, we developed a methodology and workflow that allows others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In order to form the core modules, we built on the existing Open|SpeedShop infrastructure and decomposed it into individual modules that match the necessary tool components. At the same time, we addressed the challenges found in performance tools for petascale systems in each module. When assembled, this instantiation of community tool infrastructure provides an enhanced version of Open|SpeedShop, which, while completely different in its architecture, provides scalable performance analysis for petascale applications through a familiar interface. This project also built upon and enhances capabilities and reusability of project partner components as specified in the original project proposal. The overall project team’s work over the project funding cycle was focused on several areas of research, which are described in the following sections. The reminder of this report also highlights related work as well as preliminary work that supported the project. In addition to the project partners funded by the Office of Science under this grant, the project team included several collaborators who contribute to the overall design of the envisioned tool infrastructure. In particular, the project team worked closely with the other two DOE NNSA

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...

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.

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 ...

How Traumatic Violence Permanently Changes Shopping Behavior.

Science.gov (United States)

Sigirci, Ozge; Rockmore, Marc; Wansink, Brian

2016-01-01

Traumatic experiences - such as combat, living in a conflict country or war-torn nation, or experiencing a violent crime or natural disaster - change social relationships and may also influence a life-time of consumer relationships with brands and shopping. Our focus on this previously overlooked area is centered on an analysis of the long-term shopping habits of 355 combat veterans. We show that those who experienced heavy trauma (e.g., heavy combat) exhibited similar disconnection from brands as others have experienced in social relationships. They became more transactional in that they were more open to switching brands, to trying new products, and buying the least expensive alternative (p buying brands even when they cost more (p < 0.00). Trauma, such as combat, may change one's decision horizon. Functionality and price become more important, which is consistent with the idea that they are more focused on the present moment than on building on the past or saving for the future.

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

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....

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...

Verification Tools Secure Online Shopping, Banking

Science.gov (United States)

2010-01-01

Just like rover or rocket technology sent into space, the software that controls these technologies must be extensively tested to ensure reliability and effectiveness. Ames Research Center invented the open-source Java Pathfinder (JPF) toolset for the deep testing of Java-based programs. Fujitsu Labs of America Inc., based in Sunnyvale, California, improved the capabilities of the JPF Symbolic Pathfinder tool, establishing the tool as a means of thoroughly testing the functionality and security of Web-based Java applications such as those used for Internet shopping and banking.

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.

An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem

Directory of Open Access Journals (Sweden)

Jianhui Mou

2014-01-01

Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.

Vape shop retailers' perceptions of their customers, products and services: A content analysis.

Science.gov (United States)

Tsai, Jennifer Y; Bluthenthal, Ricky; Allem, Jon-Patrick; Garcia, Robert; Garcia, Jocelyn; Unger, Jennifer; Baezconde-Garbanati, Lourdes; Sussman, Steve Y

2016-01-01

The popularity of electronic cigarettes (e-cigarettes) has spurred the growth of vape shops, but little is known about the retailers who may play an important role in the introduction and dissemination of vape products. In this paper we examine how retailers profile their customers and their perceptions of vaping, and the services their shops provide. Semi-structured interviews were conducted with a convenience sample of retailers (n=77) located across southern California. Open-ended questions were coded and analyzed using a content analysis approach. Three themes emerged from the content analysis: who vapes, why people vape, and the vape shop environment. Retailers profiled customers as friendly, health conscious, and interested in tobacco cessation or cessation maintenance. Retailers believed e-cigarettes were used recreationally or as products that help curb other addictive behaviors. While most retailers reported positive experiences with vaping, some reported potentially negative experiences including failed cessation attempts, dual use of e-cigarettes and combustible cigarettes, and increased nicotine dependence. Retailers reported that they regularly answer questions about vaping and believe their shops function as social lounges that are tied to other recreational activities. Retailers attach certain characteristics to their clientele, perceive certain health benefits associated with vaping, and seek to establish their shops as places that provide guidance on vape products as well as shops with a recreational aesthetic. As vape shops grow in popularity, additional research on, and regulation of, these retailers will be necessary. Education campaigns are needed to inform retailers of the benefits and consequences of vaping.

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

Machine Shop Lathes.

Science.gov (United States)

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Shop Floor-Level Control of Manufacturing Companies: An Interview Study in Finland

Directory of Open Access Journals (Sweden)

Tokola Henri

2015-02-01

Full Text Available This paper publishes the results of interviews regarding shop-floor-level control of 18 Finnish manufacturing companies. The interviews had 17 open questions relating to demand characteristics, shop floor-level control issues, production flexibility, inventory control, and potential development areas. In order to get insights from the interviews, this paper analyses the answers from the interviews and categorises them into typical answers. The companies that were interviewed are also categorised as small companies with their own end products, subcontractors, or large companies with their own end products, and the emphasis of the analysis is on how companies differ in their shop floor-level control. The results show that different types of companies have different characteristics. Small companies are characterised by constant workflow, seasonal trends in demand, and the use of forecasts. Subcontractors have great daily variation in their demand and processing times. Large companies tend to focus on inventory issues.

Business Plan a Vietnamese Coffee Shop in Helsinki

OpenAIRE

Do Tu, Linh

2017-01-01

Nowadays, economy is more and more developing. In consequence, startups have become a trend. Nonetheless, starting an own business is not an easy task, and become an entrepreneur also require many skills. Planning a business plan is a vital process. The number of Vietnamese people and Asian people is now increasing in the Finnish society. Therefore, opening a Vietnamese coffee shop is the extraordinarily step that will help not only the author approach the economy evolutio...

CERN Shop: Christmas Sale, 10 & 16.12.2004

CERN Multimedia

2004-01-01

Looking for Christmas present ideas? Come to the Reception Shop Special Stand in Meyrin, Main Building, ground floor, on Friday 10 and/or on Thursday 16 December from 10:30 to 16:00. CERN 50th Anniversary sweat-shirt (grey in M, L, XL) 30.- CERN 50th Anniversary T-shirt, (S, M, L, XL) 20.- CERN 50th Anniversary silk tie (2 colours) 30.- Einstein silk tie (blue, grey) 45.- Silk scarf 40.- Swiss army knife with CERN logo 25.- Swiss Duo-Pack with CERN logo 30.- CERN 50th Anniversary watch (2 models) 40.- CERN pens (2 models) 5.- Small Open Day souvenirs (a few different items) 2.- CERN 50th Anniversary Book (English & French) 70.- "Prestigious Discoveries" at CERN (English/anglais) 32.- "Particle Odyssey" soft cover (English/anglais) 35.- If you miss this special occasion, the articles are also available at the Reception Shop in Building 33 from Monday to Saturday between 08:30 and 17:00 hrs. Education and Communica...

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.

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

Directory of Open Access Journals (Sweden)

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.

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.

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...

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.

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

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...

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...

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

Science.gov (United States)

Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

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 ...

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.

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.

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.

REDUCING LEAD TIME USING FUZZY LOGIC AT JOB SHOP

Directory of Open Access Journals (Sweden)

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

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…

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.

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

Article Abstract

African Journals Online (AJOL)

Implementation of an online scheduling support system in a high mix manufacturing firm. Author(s): L. Siva Rama Krishna1*, V. Mahesh2, Sandeep Dulluri 3, C. S. P. Rao4 ... A priority based heuristic for minimizing the makespan is presented.

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

Directory of Open Access Journals (Sweden)

Xinli Xu

2013-01-01

Full Text Available A two-level batch chromosome coding scheme is proposed to solve the lot splitting problem with equipment capacity constraints in flexible job shop scheduling, which includes a lot splitting chromosome and a lot scheduling chromosome. To balance global search and local exploration of the differential evolution algorithm, a hybrid discrete differential evolution algorithm (HDDE is presented, in which the local strategy with dynamic random searching based on the critical path and a random mutation operator is developed. The performance of HDDE was experimented with 14 benchmark problems and the practical dye vat scheduling problem. The simulation results showed that the proposed algorithm has the strong global search capability and can effectively solve the practical lot splitting problems with equipment capacity constraints.

Marketing plan for a web shop business

OpenAIRE

Koskivaara, Leonilla

2014-01-01

Internet has changed the buying behavior of consumers during the past years and companies need to adapt to the changes. Web shop business is an important sales channel of today’s companies. Advantages of a web shop business include cost effectiveness and potential to do business globally. Challenges of a web shop business include search engine optimization and running both, a retail store and a web shop at the same time. Social media has become an important marketing channel and has bec...

Characteristics of prescribers whose patients shop for opioids: results from a cohort study.

Science.gov (United States)

Cepeda, M Soledad; Fife, Daniel; Berlin, Jesse A; Mastrogiovanni, Gregory; Yuan, Yingli

2012-01-01

Little is known about the prevalence of opioid shoppers in clinical practices and the relation between prescriber characteristics and the risk of having opioid shoppers. Describe the prevalence of opioid shoppers in prescribers' practices. Assess the relation between prescribers' characteristics and patient opioid shopping behavior. Retrospective cohort study using a large US retail prescription database. Patients with ≥1 opioid dispensing were followed 18 months. These patients' prescribers are the focus of the study. A patient was a "shopper" if he or she had opioid prescriptions written by ≥1 prescriber with ≥1 day of overlap filled at ≥3 pharmacies and a "heavy shopper" if he or she had ≥5 shopping episodes. The proportions of shoppers by prescriber and the proportion of prescribers with ≥1 shopper or heavy shopper were calculated. Among 858,290 opioid prescribers, most (87 percent) had no shoppers and 98 percent had no heavy shoppers. Prescribers who were aged 70-79 years, male, or who prescribed schedule II opioids had an increased likelihood of having shoppers. As the number of patients for whom a prescriber prescribed opioids increased, the proportion of shoppers also increased. Prescribers with 66 or more patients receiving opioids, who represented 25 percent of prescribers, prescribed for 82 percent of all shoppers. The great majority of opioid prescribers appear to have no shoppers in their practice. Any educational program will be more cost effective if targeted to prescribers of schedule II opioids with a large volume of patients requiring opioids.

Heuristic Scheduling in a Nigeria Furniture Shop | Anude | Nigerian ...

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.

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.

Comparison of the risks of shopping behavior and opioid abuse between tapentadol and oxycodone and association of shopping behavior and opioid abuse.

Science.gov (United States)

Cepeda, M Soledad; Fife, Daniel; Kihm, Mary A; Mastrogiovanni, Greg; Yuan, Yingli

2014-12-01

This study compared the risks of opioid shopping behavior and opioid abuse between tapentadol immediate release and oxycodone immediate release and, to validate the definition of shopping, examined the association between opioid shopping and opioid abuse further. This retrospective cohort study using linked dispensing and diagnosis databases followed opioid-naive patients for development of shopping behavior and/or opioid abuse during 1 year after initial exposure to tapentadol or oxycodone. Shopping was defined by having overlapping opioid prescriptions from >1 prescriber filled at ≥3 pharmacies; abuse by having International Classification of Diseases, 9th revision diagnoses reflecting opioid abuse, addiction, or dependence. To determine their association, we cross-tabulated shopping and opioid abuse and calculated odds ratios. Risks of developing each outcome were estimated using logistic regression. Among 277,401 participants initiating opioid use with tapentadol (39,524) or oxycodone (237,877), 0.6% developed shopping behavior, 0.75% developed abuse. Higher proportions of patients in the oxycodone group developed shopping behavior and abuse than in the tapentadol group (shopping: adjusted odds ratio [95% confidence interval], 0.45 [0.36-0.55]; abuse: 0.44 [0.37-0.54]). Shopping behavior and abuse were associated; of those with shopping behavior, 6.5% had abuse. Age (18 to 64 y), sex (male), prior benzodiazepine use, paying cash, and history (mood disorders, abuse of nonopioid medications, and back pain) were risk factors for developing either outcome. Shopping behavior and abuse measure complementary, but associated, constructs, which further validates the current definition of shopping. The risk of developing either is lower among patients who initiate opioid use with tapentadol than those who initiate opioid use with oxycodone.

Shop stewards' learning and union strategies

DEFF Research Database (Denmark)

Warring, Niels

2007-01-01

In Denmark the trade unions have well established educational systems providing the shop stewards with a variety of competencies. Union courses have been analysed focusing on shop stewards' satisfaction with the content and the practical impact of the courses. However, little attention has been...... different theoretical traditions: Shop steward's learning is situational, relational and cross-contextual. Shop stewards' learning is lifelong and life wide. And shop stewards' learning is closely connected to the development of the labour market and not least the unions' priorities, interpretation...

Why do you shop there? A mixed methods study mapping household food shopping patterns onto weekly routines of black women.

Science.gov (United States)

DiSantis, Katherine Isselmann; Hillier, Amy; Holaday, Rio; Kumanyika, Shiriki

2016-01-28

The effectiveness of initiatives to increase healthy food access may be affected by where people decide to shop. People with poor neighborhood access to large grocery stores develop shopping patterns that require traveling to other areas, and some people who do have neighborhood access also travel elsewhere for food shopping. We sought to gain an understanding of household food shopping patterns in a sample of Black women in terms of where they shopped and why. All food shopping trips of 35 low- or middle/high-income black mothers or caregivers living with at least one child were identified from grocery shopping receipts collected over four consecutive weeks. Food shopping locations were mapped along with locations of participants' homes and other places they visited during weekly routine travels (e.g. work, child's school). Semi-structured individual interviews elicited narrative information about whether and how grocery shopping trips were linked to routine travels. Inductive content analysis was utilized to identify emergent themes from interviews. Themes were considered in relation to geospatial distances and travel patterns identified through mapping of participants' shopping. Participants shopped at an average of six different stores, traveling on average a total of 35 miles (sd = 41) (Euclidian distance) over the four weeks. The most frequented store was within a mile of home (57%) or home or another place visited in the weekly routine for about 77% of participants. Interview results emphasized the concept of convenience which referred to geographical proximity to the home or routine destinations and also to potential to save time because several stores were co-located or because the store layout was easy to navigate and familiar. Store selection also related to mode of transportation, pricing, and family preference for certain foods. People have specific reasons for consistently shopping in areas outside of their neighborhood of residence. Incorporating

Optimasi Penjadwalan Pengerjaan Software Pada Software House Dengan Flow-Shop Problem Menggunakan Artificial Bee Colony

Directory of Open Access Journals (Sweden)

Muhammad Fhadli

2016-12-01

This research proposed an implementation related to software execution scheduling process at a software house with Flow-Shop Problem (FSP using Artificial Bee Colony (ABC algorithm. Which in FSP required a solution to complete some job/task along with its overall cost at a minimum. There is a constraint that should be kept to note in this research, that is the uncertainty completion time of its jobs. In this research, we will present a solution that is a sequence order of project execution with its overall completion time at a minimum. An experiment will be performed with 3 attempts on each experiment conditions, that is an experiment of iteration parameter and experiment of limit parameter. From this experiment, we concluded that the use of this algorithm explained in this paper can reduce project execution time if we increase the value of total iteration and total colony. Keywords: optimization, flow-shop problem, artificial bee colony, swarm intelligence, meta-heuristic.

Modelling Electrical Energy Consumption in Automotive Paint Shop

Science.gov (United States)

Oktaviandri, Muchamad; Safiee, Aidil Shafiza Bin

2018-03-01

Industry players are seeking ways to reduce operational cost to sustain in a challenging economic trend. One key aspect is an energy cost reduction. However, implementing energy reduction strategy often struggle with obstructions, which slow down their realization and implementation. Discrete event simulation method is an approach actively discussed in current research trend to overcome such obstructions because of its flexibility and comprehensiveness. Meanwhile, in automotive industry, paint shop is considered the most energy consumer area which is reported consuming about 50%-70% of overall automotive plant consumption. Hence, this project aims at providing a tool to model and simulate energy consumption at paint shop area by conducting a case study at XYZ Company, one of the automotive companies located at Pekan, Pahang. The simulation model was developed using Tecnomatix Plant Simulation software version 13. From the simulation result, the model was accurately within ±5% for energy consumption and ±15% for maximum demand after validation with real system. Two different energy saving scenarios were tested. Scenario 1 was based on production scheduling approach under low demand situation which results energy saving up to 30% on the consumption. Meanwhile scenario 2 was based on substituting high power compressor with the lower power compressor. The results were energy consumption saving of approximately 1.42% and maximum demand reduction about 1.27%. This approach would help managers and engineers to justify worthiness of investment for implementing the reduction strategies.

Marketing activities of vape shops across racial/ethnic communities.

Science.gov (United States)

Garcίa, Robert; Sidhu, Anupreet; Allem, Jon-Patrick; Baezconde-Garbanati, Lourdes; Unger, Jennifer B; Sussman, Steve

2016-01-01

There has been a surge in the number of vape shops in the USA. Research on the marketing practices of e-cigarette manufacturers is scarce and even less known are the practices of vape shop retailers. Past research on tobacco marketing has shown differences in the amount and content of marketing material, based on a community's demographic profile. This study examined marketing strategies in vape shops and explored differences among vape shops located in communities that differ by ethnic composition. Data was gathered in 2014 from a pilot-study on vape shops (n=77) in Los Angeles, which documented the characteristics of shops through employee interviews and in-store observations. Data were collected from shops located in communities that were predominantly, African-American (n=20), Hispanic (n=17), Korean (n=18), or non-Hispanic White (n=22). Sixty-one percent of vape shops had advertisements (print ads and posters) for e-cigarettes and 84% offered discounts. Vape shops in Hispanic communities were more likely to have ethnic specific marketing material compared to shops in other communities. All the shops provided customers with free samples, however those in Korean and non-Hispanic White communities had a significantly higher prevalence of customer accessible free samples. Vape shop marketing practices differed by ethnic community. A large majority of shops provided free samples to their customers, a practice which is now banned by the FDA. It will be important to monitor how vape shops will adjust their marketing strategy because of this ban. Future research should expand on the findings presented here to provide regulators with further crucial information.

Improved Harmony Search Algorithm for Truck Scheduling Problem in Multiple-Door Cross-Docking Systems

Directory of Open Access Journals (Sweden)

Zhanzhong Wang

2018-01-01

Full Text Available The key of realizing the cross docking is to design the joint of inbound trucks and outbound trucks, so a proper sequence of trucks will make the cross-docking system much more efficient and need less makespan. A cross-docking system is proposed with multiple receiving and shipping dock doors. The objective is to find the best door assignments and the sequences of trucks in the principle of products distribution to minimize the total makespan of cross docking. To solve the problem that is regarded as a mixed integer linear programming (MILP model, three metaheuristics, namely, harmony search (HS, improved harmony search (IHS, and genetic algorithm (GA, are proposed. Furthermore, the fixed parameters are optimized by Taguchi experiments to improve the accuracy of solutions further. Finally, several numerical examples are put forward to evaluate the performances of proposed algorithms.

CERN Shop - Christmas Sale in Bldg. 33

CERN Multimedia

PH Department

Looking for Christmas present ideas? The CERN Shop will give the CERN card holders a special reduction of 10 % on all CERN Shop articles from Friday 11.12.2009 to Thursday 17.12.2009. Come to visit the CERN Shop at the Reception, Building 33. PH-EDU-PO

Reflexivity in performative science shop projects

OpenAIRE

Beunen, R.; Duineveld, M.; During, R.; Straver, G.H.M.B.; Aalvanger, A.

2012-01-01

Science shop research projects offer possibilities for universities to engage with communities. Many science shop projects directly or indirectly intend to empower certain marginalised groups or interests within a decision-making process. In this article we argue that it is important to reflect on the role and position the researchers have in these projects. We present three science shop projects to illustrate some of the dilemmas that may arise in relation to citizen empowerment, democracy, ...

Handbook for Trade and Industrial Shop Teachers.

Science.gov (United States)

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

This handbook is intended to help teachers of pre-employment shop courses in organizing and delivering instruction in both the shop and classroom. Addressed in the guide are the following topics: the instructor's place in the local school organization; the instructor's job (objectives, advisory committees, occupational analysis, shop/classroom and…

Dimensions of Consumer's Perceived Risk in Online Shopping

Institute of Scientific and Technical Information of China (English)

YE Naiyi

2004-01-01

Perceived risk is an important concept in consumer behavior in online shopping. It impedes the adopting online shopping. A structure model with seven factors of consumer's perceived risk in online shopping is developed in this paper. The results have the descriptive power about Chinese consumers' perceived risk in Internet shopping and provide framework for managerial use in China's e-commerce market environment.

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.

Social image of students who shop and don't shop online.

Science.gov (United States)

Lammers, H Bruce; Curren, Mary T; Cours, Deborah; Lammers, Marilyn L

2003-06-01

A descriptive survey of a stratified random sample of 326 undergraduates from a large, diverse university in Los Angeles was conducted to assess whether resistance to online shopping might be, in part, related to negative social perceptions of those who shop online. Indirect questioning showed that students perceived online student shoppers as more lazy and less likely to fear for the safety and security of others but also as more trustworthy, attractive, successful, and smart. Differences in social perceptions were not related to these students' own online spending.

INDONESIAN CUSTOMER SATISFACTION IN ONLINE SHOPPING TRADING

Directory of Open Access Journals (Sweden)

Hermawan F.

2018-03-01

Full Text Available This research aims to find out if the ease of shopping, site design, informative, comprehensive, and communication have a significant influence on the level of Indonesian customer satisfaction in online shopping transactions and how the impact to the word of mouth communication. Respondents of this study are the 250 students of Jakarta colleges. This study found that the variables of design, simplicity, and security have an influence on customer satisfaction in shopping online, while the informative variable and communication have no influence on the customer's satisfaction online shopping.

Space Odyssey Gift Shop

Science.gov (United States)

2000-01-01

The Space Odyssey Gift Shop located in StenniSphere at the John C. Stennis Space Center in Hancock County, Miss., offers every visitor the opportunity to go home with 'the right stuff' from his or her StenniSphere visit. The gift shop is located just inside the front doors to StenniSphere and offers a wide range of space-related apparel, memorabilia, toys, books, mission patches and more.

Hepatic volumetry with PhotoShop in personal computer.

Science.gov (United States)

Lu, Yi; Wu, Zheng; Liu, Chang; Wang, Hao-Hua

2004-02-01

Convenient way to clarify liver volume or tumor volume in the liver is eagerly demanded by hepatobiliary surgeons, for so many aspects of clinical work need to know the liver volumetry. At present, some methods have been used to measure the liver volumetry, such as computed tomography (CT) scans, three-dimensional ultrasound volumetric system([1]) and 3-dimensional sonography([2,3]) et al. But enough volumetric information was failed to obtain by surgeons and a new way of measuring the liver volumetry that can be operated by themselves is exigent. Whereas we devise a new method of using PhotoShop in personal computer to measure the liver volumetry. A piece of whole CT film was transformed to a high quality digitized image by digital camera or scanner and then the digitized image was conducted as JPEG file into personal computer. The JPEG image file of CT film was opened by PhotoShop. Determining the edge of interested areas, and the data of pixel values of the interested areas divided by 1 cm2 pixel value will produce the actual area with the unit of square centimeter. If section thickness of CT scan is 1 cm, the sum of the areas of the liver or tumor in all sections naturally is the volume of the liver or tumor. Comparison of 10 hepatic volumes gained by this method and those gained by the GE Prospeed CT set showed a good relativity between the two groups. The volumes of three right lobes were calculated by this method before lobectomy and their real volumes were obtained postoperatively by a volumenometer. Their variation was limited to 5%. Hepatic volume obtained by PhotoShop is reliable. This method can be used to measure hepatic volume perfectly to meet clinical demand, and many parameters such as liver resection rate, graft volume can be achieved. The disadvantage of this method is the step of copying the pixel value from PhotoShop to Microsoft Excel.

Determinants Of Online Shopping In Manado

OpenAIRE

Halim, Ellen

2013-01-01

Retailers utilize online media to reach more potential customers. Internet connects the retailer and customers without any geographic location boundaries. Internet growth has a positive impact for business world. There is a new shopping method in non-store shopping as people can buy products or services without having to travel to the outlets like traditional retail does. With the increase of online retailers on internet world, online shopping became popular. The objective of this research is...

Potential of Natural Ventilation in Shopping Centres

DEFF Research Database (Denmark)

Diederichsen, Alice; Friis, Kristina; Brohus, Henrik

2008-01-01

The indoor environmental quality (IEQ) is a fundamental requirement for a well performing shopping centre. This paper contains a pilot study of the potential of using hybrid ventilation (a combination of automatically controlled natural and mechanical ventilation - respectively NV and MV) in shop......The indoor environmental quality (IEQ) is a fundamental requirement for a well performing shopping centre. This paper contains a pilot study of the potential of using hybrid ventilation (a combination of automatically controlled natural and mechanical ventilation - respectively NV and MV......) in shopping centres with focus on both the achieved IEQ and energy consumptions for air movement. By thermal building simulations it is found that there exists an interesting potential for hybrid ventilation of shopping centres, which can lead to great savings in the electrical energy consumptions...

Special aspects for forming the interiors of thai shopping malls through the use of the biological approach

Science.gov (United States)

Kuznetsova, Iryna O.; Rosliakova, Ljubov V.; Zakharchuk, Viktorija L.; Samosudova, Natalia

2017-10-01

This study reviews the biological approach to Thai shopping mall’s interior design planning. The authors defined the principles of the mall’s design optimization in Thailand on the basis of the imitation of biological samples at constructive, art-compositional, organizational and ecological levels. The analysis of forming the shopping malls interiors and space-planning solutions is based on the imitation of eight basic levels of organization of living things: molecules, cells, tissues, organs, organisms, populations, ecosystem and biosphere. The examples of the direct and implicit application of biological analogues were demonstrated in the architecture and design of Thai shopping malls. In the study, the shopping mall is regarded as an open self-sufficient system with a high level of autonomy and a fortified structural organization that includes various functional components. On the basis of the analysis of existing Thai shopping malls, a list of the basic requirements for the design of the malls was compiled. This corresponds to the needs and desires of the modern customer and ensures the competitiveness of the establishment. The phenomenon of multisensory design approach that enhances the psychophysical comfort of the shopping mall visitors is described. Socio-cultural and geographical factors were identified which determine the development of biodesign in Thailand. The article reveals the potential for a combination of biology and design to enhance the aesthetics, ergonomics and efficiency of the shopping malls. The prospects within the development of this field and the possibility of applying the solutions in practice were explored.

HESITANCY TOWARDS ONLINE SHOPPING, A STUDY OF PAKISTANI CONSUMERS

Directory of Open Access Journals (Sweden)

Usman YOUSAF

2012-01-01

Full Text Available To study the influence of Perceived cost, risk, convenience and enjoyment on online consumer purchases. Being more convenient online shopping seems painless compared to in store shopping, why consumers are still reluctant to shop online?.A sample of 220 questionnaires was filled from different departments at University of Sargodha. Respondents were asked to fill the questionnaire based on four factors (Perceived cost, Perceived risk, Perceived convenience, Perceived enjoyment, there were 2 general questions. Out of 220, 207 questionnaires were returned. One sample test is applied in this study to check the reliability of independent variables. Analysis was also done on basis of gender and their ages. The most important factor out of four, which can persuade the customer's online buying decision, is delivery cost for purchased items and it has negative relationship with dependent variable, moreover perceived risk has also negative relationship with dependent one. Perceived convenience and Perceived enjoyment has positive relationship with online shopping preference. As online shopping is easier to do but due to extra delivery cost and risk factors consumers do not adopt online shopping and these factors should be minimized to promote online shopping. Online shopping should be promoted and to gain the consumer confidence, delivery cost and risk factor should be minimized. As online shopping is easier to do as compared to offline shopping but people still reluctant to use internet for online shopping, so to promote online shopping delivery cost and risk factor should be minimized to gain consumers attraction and confidence. People want to experience online shopping but it won’t be promoted until delivery cost and perceived risk factors be reduced. A little work has been done on exploring the factors that influence the online buying decision. These factors are called situational factors and include delivery charges, risk factors, convenience

Commuter Shopping : A study in understanding commuting in the context of shopping

OpenAIRE

Andersson, Åsa; Skoog, Sara; Svensson, Johanna

2014-01-01

Background For ages people have commuted to work, or to other activities, located outside their home municipality. Statements found indicate that the basic decision for commuting are based on utility maximisation and no matter what the character of the benefit is; it should be higher than what can be found closer to the home location. This thesis aims to investigate if people are also commuting with the purpose of obtaining benefits from shopping. The shopping location will in this thesis be ...

Retail Shopping Lists

DEFF Research Database (Denmark)

Schmidt, Marcus

2012-01-01

categories. An association between the frequency of a brand's appearance on lists and the amount of money spent on advertising the brand could not be found. A strong link between brands, prices and store names is revealed. Price in the majority of cases refers to brands rather than to product categories......The paper addresses consumers' shopping lists. The current study is based on a survey of 871 lists collected at retail grocery stores. Most items on shopping lists appear on the product category level rather than the brand level. The importance of the brand level varies considerably across product...

A novel modeling approach for job shop scheduling problem under uncertainty

Directory of Open Access Journals (Sweden)

Behnam Beheshti Pur

2013-11-01

Full Text Available When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.

Growing Shopping Malls and Behavior of Urban Shoppers

OpenAIRE

Rajagopal

2009-01-01

Shopping malls contribute to business more significantly than traditional markets which were viewed as simple convergence of supply and demand. Shopping malls attract buyers and sellers, and induce customers providing enough time to make choices as well as a recreational means of shopping. However, competition between malls, congestion of markets and traditional shopping centers has led mall developers and management to consider alternative methods to build excitement with customers. This stu...

Designing electronic shops, persuading consumers to buy

DEFF Research Database (Denmark)

Dormann, Claire

2000-01-01

The purpose of this article is to show how to design persuasive and successful Web shops. An approach to commercial site design that draws on theories of visual persuasion is proposed. We focus on the role of emotion. Images in an ad are typically meant to create some emotional disposition toward....... To strengthen the discussion, an evaluation of shop home pages, situated within the perspective of visual persuasion is presented. This study has given some indications that viewers form distinctive emotional impressions from shop designs. Thus, by building on visual persuasion theories, we can learn how...... to design seductive Web shops....

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.

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

Directory of Open Access Journals (Sweden)

M. Frutos

2013-01-01

Full Text Available Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.

Using Optimization Models for Scheduling in Enterprise Resource Planning Systems

Directory of Open Access Journals (Sweden)

Frank Herrmann

2016-03-01

Full Text Available Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.

The 3D virtual environment online for real shopping

OpenAIRE

Khalil, Nahla

2015-01-01

The development of information technology and Internet has led to rapidly progressed in e-commerce and online shopping, due to the convenience that they provide consumers. E-commerce and online shopping are still not able to fully replace onsite shopping. In contrast, conventional online shopping websites often cannot provide enough information about a product for the customer to make an informed decision before checkout. 3D virtual shopping environment show great potential for enhancing e-co...

RURAL CUSTOMER SATISFACTION TOWARDS ONLINE SHOPPING IN POLLACHI TALUK

OpenAIRE

K. Jayaprakash; A. Pavithra

2017-01-01

Online shopping is a recent phenomenon in electronic commerce and its definitely going to be the future of shopping in the world. It is user friendly compare to in store shopping because consumers can just complete his requirements just with a click of mouse without leaving their home. In the present work, the researcher intended to analyze the most preferred online shopping website, factors influencing the rural customers towards online shopping and to analyze the level satisfaction of the ...

Designing an advanced available-to-promise mechanism compatible with the make-to-forecast production systems through integrating inventory allocation and job shop scheduling with due dates and weighted earliness/tardiness cost

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2016-06-01

Full Text Available In the competitive business world, applying a reliable and powerful mechanism to support decision makers in manufacturing companies and helping them save time by considering varieties of effective factors is an inevitable issue. Advanced Available-to-Promise is a perfect tool to design and perform such a mechanism. In this study, this mechanism which is compatible with the Make-to-Forecast production systems is presented. The ability to distinguish between batch mode and real-time mode advanced available-to-promise is one of the unique superiorities of the proposed model. We also try to strengthen this mechanism by integrating the inventory allocation and job shop scheduling by considering due dates and weighted earliness/tardiness cost that leads to more precise decisions. A mixed integer programming (MIP model and a heuristic algorithm according to its disability to solve large size problems are presented. The designed experiments and the obtained results have proved the efficiency of the proposed heuristic method.

48 CFR 252.227-7033 - Rights in shop drawings.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Rights in shop drawings... of Provisions And Clauses 252.227-7033 Rights in shop drawings. As prescribed in 227.7107-(1)(c), use the following clause: Rights in Shop Drawings (APR 1966) (a) Shop drawings for construction means...

48 CFR 1952.227-77 - Rights in shop drawings.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Rights in shop drawings... Rights in shop drawings. As prescribed in 1927.405(h), insert the following clause: Rights in Shop Drawings (FEB 1985) (a) Shop drawings for construction means drawings, submitted to the Government by the...

Determinants of Customer Continuance Intention of Online Shopping

Directory of Open Access Journals (Sweden)

Al-maghrabi, T.

2011-01-01

Full Text Available The purpose of this study is to clarify theory and identify factors that could explain the level of continuance intention of e-shopping. A revised technology acceptance model integrates expectation confirmation theory and investigates effects of age differences. An online survey of internet shoppers in Saudi Arabia. Structural equation modelling and invariance analysis confirm model fit. The findings confirm that perceived usefulness, enjoyment and social pressure are determinants of e-shopping continuance. The structural weights are mostly equivalent between young and old but the regression path from perceived usefulness to social pressure is stronger for younger respondents. This research moves beyond e-shopping intentions to factors affecting e-shopping continuance, explaining 55% of intention to continue shopping online. Online strategies cannot ignore direct and indirect effects on continuance intentions. The findings contribute to literature on internet shopping and continuance intentions in the context of Saudi Arabia.

网上购物扩展的计划行为模型的提出与验证%The Development and Confirmation of Online Shopping ETPB Model

Institute of Scientific and Technical Information of China (English)

郑宏明

2009-01-01

整合了以往的计划行为模型、技术接受模型、交易成本分析,提出了网上购物扩展的计划行为模型(ETPB),并对该模型用结构方程进行了验证.结果发现,开放性人格通过网上购物行为控制正向影响网上购物意向,信任倾向分别通过网上购物交易成本、主观参照正向影响网上购物意向.对于大学生来说,开放性人格对网上购物意向有间接正向影响,而信任倾向、网上购物风险对网上购物意向没有显著的影响;对在职人员来说,信任倾向通过网上购物交易成本间接正向影响网上购物意向,网上购物风险对网上购物意向有直接正向影响,而开放性人格对网上购物意向不存在显著的间接影响.%This research integrated the previous models, TPB, TAM, TCA, and developed a expanded TPB model and test the ETPB model by LISREL. The results indicated that Openness indirectly influence the online shopping intention through online shopping self - efficacy positively while trust propensity does through online shopping transaction coat and subjective norm respectively. For college students openness has indirect positive effect on online shopping intention while trust propensity (through mediating variables) and online shopping risk have no significant effect on online shopping intention; for employees trust propensity (through subjective norm) and online shopping risk have significant effect on online shopping intention but the indirect effect of openness on online shopping intention is not significant.

An Exploratory Analysis of Online Shopping Behavior in Turkey

Directory of Open Access Journals (Sweden)

Adnan Veysel Ertemel

2017-06-01

Full Text Available Alongside the technologic developments, transformation in user behavior and business models has been observed. New areas and models are emerged in a lot of grounds like the communication of people or daily activities. So a new face put for shopping behavior by the e-commerce, which is one of the novelties. This study tries to research online shopping behavior in Turkey. With a quantitative research, device usage, the reasons behind to shop or not to shop online, online shopping category and e-commerce site preferences, payment methods, international e-commerce and online marketplace usage is investigated. As implications of the research, “saving time“ is found to be the foremost reason for shopping online in Turkey and “travel and bookings” category is found as the most shopped category among the results of the survey.

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

A genetic algorithm approach for open-pit mine production scheduling

Directory of Open Access Journals (Sweden)

Aref Alipour

2017-06-01

Full Text Available In an Open-Pit Production Scheduling (OPPS problem, the goal is to determine the mining sequence of an orebody as a block model. In this article, linear programing formulation is used to aim this goal. OPPS problem is known as an NP-hard problem, so an exact mathematical model cannot be applied to solve in the real state. Genetic Algorithm (GA is a well-known member of evolutionary algorithms that widely are utilized to solve NP-hard problems. Herein, GA is implemented in a hypothetical Two-Dimensional (2D copper orebody model. The orebody is featured as two-dimensional (2D array of blocks. Likewise, counterpart 2D GA array was used to represent the OPPS problem’s solution space. Thereupon, the fitness function is defined according to the OPPS problem’s objective function to assess the solution domain. Also, new normalization method was used for the handling of block sequencing constraint. A numerical study is performed to compare the solutions of the exact and GA-based methods. It is shown that the gap between GA and the optimal solution by the exact method is less than % 5; hereupon GA is found to be efficiently in solving OPPS problem.

Specific energy use in Swedish and Norwegian shopping malls

Energy Technology Data Exchange (ETDEWEB)

Stensson, Sofia; Axell, Monica (SP Energy Technology, Boraas (Sweden)); Smaage, Kjell Petter (Evotek AS (Norway)); Fahlen, Per (Chalmers Univ. of Technology, Building Services Engineering, Goeteborg (Sweden))

2009-07-01

The prevalence of shopping malls is growing worldwide. Internationally, there are differences in energy use and system solutions due to local outdoor climate, available energy resources, prices, national building regulations, traditions etc. On the other hand, tenants are usually international chains and they often have the same demands regarding indoor climate, system solutions etc. irrespective of the national differences. Shopping malls overall tends to have large lighting loads, high population density and, hence, a large air conditioning demand. There is also an apparent trend towards increasing glass surfaces and such design feature affects the energy balance of the building. For those interested in the energy efficiency of the building and its installations, it is interesting to know how different system solutions affect the energy use. Benchmarking between buildings gives valuable insight to energy efficient design and operation. However, available information on energy use for such benchmarking in shopping malls is still rather limited. This study investigates shopping malls in Sweden and Norway. Available national statistical data on retail and shopping malls are reviewed. Further building statistical data were collected from building owners and managers, covering energy use in 41 shopping malls. Additional energy use data for 115 shops, within three of these shopping malls were also collected. The building statistical data shows that the average energy use in Norwegian and Swedish shopping malls are approximately 291 and 279 kWh/m2/year respectively. The highest energy use exceeds the lowest figure by approximately 50 percent, indicating a significant potential for improvement. Results also show a wide deviation in energy use of the different shops in a shopping mall. The paper further provides a discussion concerning alternative benchmarking methods and necessary improvements to make valid conclusions regarding energy use in shopping malls.

Turning shopping habits of young consumers into green

NARCIS (Netherlands)

Bialkova, Svetlana; van 't Erve, Sanne; van Hoof, Joris Jasper; Pruyn, Adriaan T.H.; Bigné, Enrique

2014-01-01

Consumers have strong shopping habits, and although being aware of sustainable issues, they hardly do green shopping. Therefore, a challenging question is: how to break the old shopping habits and turn those into green? The current study addresses this question looking at barriers and potential

Typically Female Features in Hungarian Shopping Tourism

Directory of Open Access Journals (Sweden)

Gábor Michalkó

2006-06-01

Full Text Available Although shopping has been long acknowledged as a major tourist activity, the extent and characteristics of shopping tourism have only recently become the subject of academic research and discussion. As a contribution to this field of knowledge, the paper presents the characteristics of shopping tourism in Hungary, and discusses the typically female features of outbound Hungarian shopping tourism. The research is based on a survey of 2473 Hungarian tourists carried out in 2005. As the findings of the study indicate, while female respondents were altogether more likely to be involved in tourist shopping than male travellers, no significant difference was experienced between the genders concerning the share of shopping expenses compared to their total travel budget. In their shopping behaviour, women were typically affected by price levels, and they proved to be both more selfish and more altruistic than men by purchasing more products for themselves and for their family members. The most significant differences between men and women were found in their product preferences as female tourists were more likely to purchase typically feminine goods such as clothes, shoes, bags and accessories, in the timing of shopping activities while abroad, and in the information sources used by tourists, since interpersonal influences such as friends’, guides’ and fellow travellers’ recommendations played a higher role in female travellers’ decisions.

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

OpenAIRE

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 and customers, and second, the ‘solution’ to this problem depends on the specific cost structure of stores and the preferences of customers. In particular, it may happen that, even if extended shoppi...

Retailing and Shopping on the Internet.

Science.gov (United States)

Rowley, Jennifer

1996-01-01

Internet advertising and commercial activity are increasing. This article examines challenges facing the retail industry on the Internet: location; comparison shopping; security, especially financial transactions; customer base and profile; nature of the shopping experience; and legal and marketplace controls. (PEN)

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

Directory of Open Access Journals (Sweden)

Logan D. R. Beal

2017-12-01

Full Text Available Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC and continuous-time scheduling are combined.

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

Science.gov (United States)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

Impact of e-shopping on shopping-related travel behaviour: Analyses of the Netherlands Mobility Panel data.

NARCIS (Netherlands)

Hoogendoorn-Lanser, S.; Olde Kalter, Marie-José José Theresia; Schaap, Nina

2015-01-01

From the moment e-shopping emerged, there are speculations about the impact that would have on personal mobility. Questions about the impact of e-shopping on mobility increase due to media coverage on the sharp increase in turnover of Internet purchases and the increasing number of consumers that

Measuring consumer perceptions of online shopping convenience

OpenAIRE

Ferreira, Margarida Bernardo

2016-01-01

The aim of this master thesis is to identify which dimensions of convenience affect consumers’ intention of using online shopping. Also it explores a conceptual model to measuring consumer perceptions of online shopping convenience. This paper contains prospects about online consumer behavior, and the results have important implications for retailers, managers and marketers, related to online shopping strategies. An empirical investigation was carried out to test the hypotheses. In order t...

CERN SHOP CHRISTMAS SALE

CERN Multimedia

Visits & Exhibition Service

2000-01-01

Looking for Christmas present ideas? Come to the Reception Shop Special Stand in Meyrin, Main Building, ground floor, from Tuesday 12 to Thursday 14 December from 10.00 to 16.00.   Sweat-shirt col zippé, grey, blue, black (M, L, XL) 30.- Sweat-shirt col polo, grey, collar blue (M, L, XL) 30.- T-shirt, black, (M, L, XL) 15.- WWW T-shirt, white, bordeau (M, L, XL) 15.- CERN silk tie (3 colours) 33.- Fancy silk tie (blue, bordeau 25.- Silk scarf (blue, red, yellow) 35.- Swiss army knife with CERN logo 25.- New model of CERN watch 25.- New CERN baseball cap 10.- Antimatter (English/anglais) 30.- The Search for Infinity (French, Italian, English,) 35.- Auf der Suche nach dem Unendlichen 45.- If you miss this special occasion, the articles are also available at the Reception Shop in Building 33 from Monday to Saturday between 08.30 and 17.30 hrs (Shop will be closed at 12.00 on 22.12.).

Risk factors associated with purchasing pesticide from shops for self-poisoning: a protocol for a population-based case-control study.

Science.gov (United States)

Weerasinghe, Manjula; Konradsen, Flemming; Eddleston, Michael; Pearson, Melissa; Gunnell, David; Hawton, Keith; Jayamanne, Shaluka; Pabasara, Chathurani; Jayathilaka, Tharidu; Dissanayaka, Kalpani; Rajapaksha, Sandamali; Thilakarathna, Prasanna; Agampodi, Suneth

2015-05-20

Pesticide self-poisoning is one of the most frequently used methods of suicide worldwide, killing over 300,000 people annually. Around 15-20% of pesticide self-poisonings occur soon after the person has bought the pesticide from a shop. We aim to determine the characteristics of individuals who purchase pesticides directly from shops and how they differ from individuals who access pesticides from other sources such as home, home garden or farmland. This information will help inform possible vendor/shop-based intervention strategies aimed at reducing access to pesticides used for self-harm. This study will investigate risk factors associated with purchasing pesticides for acts of self-poisoning from pesticide shops, including cases identified over a 9-month period using a population-based case-control group approach. Four interviewer-administered data collection tools will be used for this study: a semistructured questionnaire, Beck Suicidal Intent Scale (SIS), Clinical Interview Schedule-Sinhalese version (CIS-Sn) and Alcohol Use Disorders Identification Test (AUDIT). Each case (expected n=33) will be compared with two groups of individuals: (1) those who have self-poisoned using pesticides from the home, home garden or farmland and (2) those who bought pesticides from the same shops as the above cases, but not did not self-poison. Logistic regression models will be used to identify risk factors of purchasing pesticides for self-poisoning from shops. The study has received ethical approval from the Ethical Review Committee of the Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka. A sensitive data collection technique will be used and ethical issues will be considered throughout the study. Results will be disseminated in scientific peer-reviewed articles. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

An architecture for agile shop floor control systems

DEFF Research Database (Denmark)

Langer, Gilad; Alting, Leo

2000-01-01

as shop floor control. This paper presents the Holonic Multi-cell Control System (HoMuCS) architecture that allows for design and development of holonic shop floor control systems. The HoMuCS is a shop floor control system which is sometimes referred to as a manufacturing execution system...

Tourist shopping behavior in a historic downtown area

NARCIS (Netherlands)

Kemperman, A.D.A.M.; Borgers, A.W.J.; Timmermans, H.J.P.

2009-01-01

Shopping is one of the most important activities for tourists. The purpose of this study is to describe and predict tourist shopping route choice behavior in a downtown historic center. Reported routes of tourists in the downtown shopping area of Maastricht, located in the Southern part of the

The impact of science shops on university research and education

DEFF Research Database (Denmark)

Hende, Merete; Jørgensen, Michael Søgaard

This report discusses the impact from university-based science shops on curricula and research. Experience from science shops show that besides assisting citizen groups, science shops can also contribute to the development of university curricula and research. This impact has been investigated...... through the SCIPAS questionnaire sent out to science shops and through follow-up interviews with employees from nine different university-based science shops and one university researcher. Not all the cases call themselves science shops, but in the report the term 'science shop' will be used most...... way or the other has had impact on university curricula and/or research. The analysis and the case studies have theoretically been based on literature on universities and education and research as institutions and a few articles about the impact of science shops on education and research. The analysis...

E-COMMERCE FACTORS INFLUENCING CONSUMERS‘ ONLINE SHOPPING DECISION

Directory of Open Access Journals (Sweden)

Živilė Baubonienė

2015-12-01

Full Text Available Purpose – The purpose of this paper is to look at the factors driving online shopping and to develop an understanding of the factors influencing the online shopping by the consumers. This is done by exploring the factors that encourage consumers to shop online through analysis of such advantages as security, fast delivery, comparable price, convenience, cheaper prices and a wider choice. At the same time, the research project reveals the factors that are discouraging for consumers and the benefits received by buyers making purchases online. Specifically, the research explores how online shopping can be affected by such factors as age, gender or occupation. Design/methodology/approach – The factors that affect the consumer online shopping have been disclosed through quantitative research by analysing data collected via a web‐based questionnaire survey. The sample consisted of 183 Lithuanian consumers who were purchasing online. Findings –The empirical findings of this study indicate that the main factors influencing consumers to shop online are convenience, simplicity and better price. Analysis of socio-demographical characteristics such as gender has shown that men shop more often online because of the lower price. Respondents of the 25–35 year age group more often choose shopping online for such reasons as lack of time and a wide range of products. The most beneficial factor of shopping online was identified as a possibility to compare prices and buy at a lower price. Research limitations/implications – This study was done regarding only general conditions and the findings may not necessarily be applicable to a particular e-business. Therefore, in the future it would be highly encouraged to examine consumers’ attitudes towards specialized online shopping websites to look for differences by kind of products or services.Practical implications – Attributes identified by this study could help e-business developers to forme their

KASS v.2.2. scheduling software for construction

Directory of Open Access Journals (Sweden)

Krzemiński Michał

2016-01-01

Full Text Available 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 production. The minimal time, the minimal slack of brigades, the minimal slacks of the chosen working brigade and costs of the transfer operation of working fronts are included in operational research criteria between work centers. It is possible to enter data into the program both by hand as well as to load the Excel from files, similarly is with results, they are presented on-screen as well as a possibility of enrolling them in the file exists Excel. An element is very valid for it since allows for further simple processing of received results. In providing software for performing operational research calculations a technique of the complete review and simulation technology are being exploited. Described algorithms a program is using which will stay in the article as well as shown computational examples will remain.