COTS software integration for simulation optimization coupling: case of ARENA and CPLEX products

Borodin, Valeria; Bourtembourg, Jean; Hnaien, Faicel; Labadie, Nacima

doi:10.1080/02286203.2018.1547814

Cited by 13 publications

(7 citation statements)

References 31 publications

(33 reference statements)

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“…Scatter search is a population-based meta-heuristic, while black-box is a context-dependent meta-heuristics algorithm (Guo et al , 2016). Scatter search is a sequential strategy that relaxes many combinatorial decision problems (Borodin et al , 2018). Those methods can solve non-linear systems' issues, even though they have various mechanisms (Li et al , 2017).…”

Section: Resultsmentioning

confidence: 99%

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Nwadigo

Naismith

Ghaffarianhoseini

et al. 2021

SASBE

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PurposeDynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.Design/methodology/approachThe authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.FindingsThe content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.Originality/valueThis research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.

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Section: Resultsmentioning

confidence: 99%

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Nwadigo

Naismith

Ghaffarianhoseini

et al. 2021

SASBE

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“…Similarly, Elnaggar 63 used Arena and OptQuest to determine the best number of workstations in garment assembly line. Furthermore, Borodin et al 64 demonstrated the possibility of integrating Arena and CPLEX software tools for SBO.…”

Section: Literature Reviewmentioning

confidence: 99%

A complex garment assembly line balancing using simulation‐based optimization

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation-based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

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“…Simulation optimization coupling [2], illustrated in Fig. 2, is an active area in the field of stochastic programming.…”

Section: Stochastic Simulationmentioning

confidence: 99%

“…2, is an active area in the field of stochastic programming. In this connection, the simulation is generally used to generate scenarios in accordance with the probability distributions data [2].…”

Section: Stochastic Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Modified L-shaped Decomposition Method with Scenario Aggregation for a Two-Stage Stochastic Programming Problem

Ušpurienė

Sakalauskas

Gricius

2018

ITC

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This paper introduces a method which is developed to solve two-stage stochastic programming problems in which first-stage region is unbounded and cannot be solved using traditional decomposition. We are using our proposed L-shaped decomposition method modification to solve such problems. In order to achieve a more accurate result, the number of scenarios generated in the optimization process must be large enough. If there is a large number of target variables, optimization takes a long time and uses a lot of resources. Thus, in order to reduce the number of iterations of the optimization process, the amount of resources used, and the calculating time needed to get the optimal solution, the aggregation approach is applied. This paper also presents results of our research on optimal parameters setting of the proposed method.

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COTS software integration for simulation optimization coupling: case of ARENA and CPLEX products

Cited by 13 publications

References 31 publications

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

A complex garment assembly line balancing using simulation‐based optimization

Modified L-shaped Decomposition Method with Scenario Aggregation for a Two-Stage Stochastic Programming Problem

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