Schedule control model for linear projects based on linear scheduling method and constraint programming

Tang, Yuanjie; Liu, Rengkui; Sun, Qiang

doi:10.1016/j.autcon.2013.09.008

Cited by 45 publications

(43 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some studies focusing resource leveling of linear projects have been performed based on linear scheduling techniques, such as those by Georgy (), Mattila and Abraham (), Tang et al. (, b), and Hsie et al. (); however, these studies were all LSM‐based rather than LOB‐based.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In recent years, some researchers have applied CP to scheduling problems in civil engineering (Chan and Hu, ; Liu and Wang, , , ; Menesi and Hegazy, ; Menesi et al., ). In particular, (Liu and Wang, ; Tang et al., , b) performed linear project schedule optimization using CP and the LSM. However, to the best of our knowledge, CP has not been yet applied to schedule optimization problems under the LOB scheme.…”

Section: Constraint Programmingmentioning

confidence: 99%

See 1 more Smart Citation

Resource Leveling Based on Line of Balance and Constraint Programming

Tang

Sun

Liu

et al. 2018

Computer aided Civil Eng

Self Cite

View full text Add to dashboard Cite

This study investigated resource leveling problems concerning linear construction projects based on the line of balance (LOB) technique and constraint programming. In addition, an LOB‐based scheduling optimization model for resource leveling is proposed. This model retains the advantages of the conventional models, including multiple‐resource management and natural rhythm concept, and showcases new abilities: scheduling optimization without specifying a fixed schedule; scheduling optimization on more comprehensive optimization objects and variable values; maintaining continuity of resource while completely eliminating the occurrence of idle time; handling more comprehensive constraints after the addition of logical constraints and explicit expression of certain new constraints. The flexibility, practicality, and solution quality of the proposed model were enhanced accordingly. Further, a scheduling system was developed to assist in schedule optimization and visualization. Lastly, effectiveness of the proposed model was verified based on four case studies involving three case projects investigated in extant LOB‐based studies.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Constraint Programmingmentioning

confidence: 99%

Resource Leveling Based on Line of Balance and Constraint Programming

Tang

Sun

Liu

et al. 2018

Computer aided Civil Eng

Self Cite

View full text Add to dashboard Cite

show abstract

“…The model integrates three branch and bound methods and considers precedence constraints, capacity constraints, release time and due date. Tang, Liu and Sun (2014) integrated the linear scheduling and CP to solve schedule control problems faced during railroad construction.…”

Section: Literature Reviewmentioning

confidence: 99%

A Constraint programming-based genetic algorithm for capacity output optimization

Goh

Feng

Loh

et al. 2014

JIEM

View full text Add to dashboard Cite

Purpose:The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company.Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm.Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively. Research limitations/implications:The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.-1222-Journal of Industrial Engineering and Management -http://dx. Practical implications:Capacity planning in a semiconductor manufacturing facility need to consider multiple mutually influenced constraints in resource availability, process flow and product demand. The findings prove that CPGA is a practical and an efficient alternative to optimize the capacity output and to allow the company to review its capacity with quick feedback.Originality/value: The work integrates two contemporary computational methods for a real industry application conventionally reliant on human judgement.

show abstract

“…Nowadays, simulation models have been proved not just as efficient in solving large problem of TP, but as well as a visualization tool of the material flow, resource allocation, bottlenecks detection and prevention, and various scenarios simulation (i.e. what-if scenarios) noted by authors (AbouRizk, 2010;Mariz et al, 2013;Tang et al, 2014). However, authors (Tang et al, 2014) have underlined that available simulation software often tends to have complicated input and export of the data, and suggests that further researchers should detect alternative software and work on more general approach of processes modelling in order to be more understandable and user-friendly.…”

Section: Literature Reviewmentioning

confidence: 99%

Scenario Simulation Model of the Production, Transportation and Asphalt Paving

Galić¹,

Završki²,

Dolaček-Alduk³

2015

OTMCJ

View full text Add to dashboard Cite

Organizational processes modelling and scenario simulation is proved to be an efficient tool for the quantitative strengthening of the decision making process. In business of production, transportation and paving of great quantities of asphalt mixture, solving problem of project's fragmented sub-processes has been emphasized by previous researchers as a high priority. Detached process modeling and optimization without taking into account constraints of interrelations among sub-processes cannot offer the optimal or quality solution. Thus, it is necessary to structure a developing and easily adjustable model which will be able to integrate all sub-processes with their interrelations. In this paper authors gave a review of the findings and recommendations of the previous researches. Based on the recommendations, authors structured a developing simulation model for planning and optimization "just in time" chain of processes of production, transportation and paving of great quantities of asphalt mixture. Suggested model is based on the algorithm for scenario simulations which is dynamic and adjustable for changes and updates of the input parameters.

show abstract

Schedule control model for linear projects based on linear scheduling method and constraint programming

Cited by 45 publications

References 24 publications

Resource Leveling Based on Line of Balance and Constraint Programming

Resource Leveling Based on Line of Balance and Constraint Programming

A Constraint programming-based genetic algorithm for capacity output optimization

Scenario Simulation Model of the Production, Transportation and Asphalt Paving

Contact Info

Product

Resources

About