Development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems

Mahdavi, Iraj; Shirazi, Babak; Solimanpur, Maghsud

doi:10.1016/j.simpat.2010.01.015

Cited by 62 publications

(26 citation statements)

References 48 publications

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“…Mahdavi et al [39] developed a real-time simulation-based decision support system for production control of the stochastic FJSP under stochastic processing time of machines. Wang and Yu [40] proposed a beam search-based heuristic algorithm to tackle the FJSP with machine availability constraints due to maintenance activities.…”

Section: Related Literaturementioning

confidence: 99%

Evolutionary Fleet Sizing in Static and Uncertain Environments with Shuttle Transportation Tasks-The Case Studies of Container Terminals [Application Notes]

Kavakeb

Nguyễn

Yang

et al. 2016

IEEE Comput. Intell. Mag.

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Evolutionary fleet sizing in static and uncertain environments with shuttle transportation tasks -the case studies of container terminals http://researchonline.ljmu.ac.uk/1851/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LJMU Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain.The version presented here may differ from the published version or from the version of the record. Please see the repository URL above for details on accessing the published version and note that access may require a subscription. These factors, however, have not been fully considered previously, leaving an important gap in the current research. This paper attempts to close this gap by taking into account the aforementioned factors. An evolutionary algorithm was proposed to solve this problem under static and uncertain situations. Two container ports were selected as case studies for this research. For the static cases, the state-of-the-art CPLEX solver was considered as the benchmark. Comparison results on real-world scenarios show that in the majority of cases the proposed algorithm outperforms CPLEX in terms of solvability and processing time. For the uncertain cases, a high-fidelity simulation model was considered as the benchmark. Comparison results on real-world scenarios with uncertainty show that in most cases the proposed algorithm could provide an accurate robust fleet size. These results also show that uncertainty can have a significant impact on the optimal fleet size.

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Section: Related Literaturementioning

confidence: 99%

Evolutionary Fleet Sizing in Static and Uncertain Environments with Shuttle Transportation Tasks-The Case Studies of Container Terminals [Application Notes]

Kavakeb

Nguyễn

Yang

et al. 2016

IEEE Comput. Intell. Mag.

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“…They evaluated their method based on an industrial case study. Mahdavi et al [35] development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems. Savory and Williams [36] describe a discreteevent simulation model of a U-shaped manufacturing cell and the integration of it with activity-based costing (ABC) concepts cost estimation and analysis of the manufacturing cell design.…”

Section: Background Of the Researchmentioning

confidence: 99%

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

Saidabad¹,

Taghizadeh²

2015

AJCM

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Using the accurate methods and tools for evaluation of function in different areas is of great importance. In recent years, much more studies have been done on the nature and methodology of function evaluation in organizations and its improvement. This study aimed to evaluate and improve the function of production line through computer simulation in one of the iron foundries in Iran. For this purpose, at first data has been gathered on the basis of timing with chronometer for each one of the production line machineries and using this data, distribution functions governing the activity cycle of each one of these machineries have been determined; and then, using the required gathered data for computer simulation (taking the advantage of "ED" simulation software), a model was simulated to introduce the current situation of production line and the validity of simulated model was measured on the basis of production rate. And then, considering the criteria such as the production rate, average waiting time, machine utilization coefficient, production yield, production cost, production income and the production time production line function was evaluated. Finally, applying amendment changes on the simulated model improved model was offered.

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“…Rajinder Singh Virk and Dr. Gurvinder Singh [23] have demonstrated that a key component of any Relational Distributed Database Query Optimizer was to fragment various tables and distribute fragmented Data over the sites of network. Then find a near optimal or best possible sub query operation allocation plan in a stipulated time period.…”

Section: Abbe Mowshowitz Et Almentioning

confidence: 99%

Data Replication for the Distributed Database using Decision Support Systems

Kuppusamy¹,

Elango²

2013

IJCA

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Replication is a topic of interest in the distributed computing, distributed systems, and database communities. Decision support systems became practical with the development of minicomputer, timeshare operating systems and distributed computing. Replicated data may get insufficient due to system failure, fault tolerance, and reliability. A partial Replication is quantized in the replication system will increase the non replicated system. Fault tolerance is the property that enables a system (often computer-based) to continue operating properly. Transaction Processing Replication (TP-R) and Decision-support replication schema (DDS-R) will clear the non replica and it is used to clear the server problems and system error. This process is well executed in distributed systems and it doesn't fail to detect the system errors when multiple access are multiplexed.

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Development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems

Cited by 62 publications

References 48 publications

Evolutionary Fleet Sizing in Static and Uncertain Environments with Shuttle Transportation Tasks-The Case Studies of Container Terminals [Application Notes]

Evolutionary Fleet Sizing in Static and Uncertain Environments with Shuttle Transportation Tasks-The Case Studies of Container Terminals [Application Notes]

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

Data Replication for the Distributed Database using Decision Support Systems

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