Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming

Li, Haitao; Womer, Norman Keith

doi:10.1016/j.ejor.2015.04.015

Cited by 94 publications

(58 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The number of execution modes was fixed ( = 3) for each activity. The shortest duration derived from the PTS project's real duration ( ) was considered as the execution time of the first mode ( 1); while the execution time of second mode( 2) is derived from a uniform distribution from ( − � ) to ( + � ) and the execution time of the third mode( 3) is derived from the interval of ( 2 , 2 * ), motivated from the work of Li and Womer (2015). To determine the resource requirements for each resource type for 1, we used the resource usage values from the resource distribution table A2.…”

Section: Case Studymentioning

confidence: 99%

A Modified Variable Neighbourhood Search Heuristic for the Multi‐Mode Resource Constrained Project Scheduling Problem with A Case Study

Chakrabortt

Abbasi

Ryan

2019

INCOSE International Symp

View full text Add to dashboard Cite

This paper provides a fast near‐optimum solution to the Multi‐Mode Resource Constrained Project Scheduling Problem (MRCPSP), for projects with activities that have known deterministic renewable and non‐renewable resource requirements. Multi‐modes allows any activity to execute one of many alternative combinations of resource usages and durations, while each activity needs to pick the most feasible one. This type of setting is more prevalent for real‐life project schedules, which necessitates systematic methodologies and advanced solution approaches in harmony with real‐world implementations. This study proposes a Modified Variable Neighbourhood Search Heuristic (MVNSH) algorithm as an advanced optimization technique for scheduling projects. To validate our approach, exhaustive computational tests were carried out by using relevant benchmark instances. The MVNSH algorithm has been shown to be faster and more accurate than many existing heuristic methods. This research also contributes to developing a practical decision support system for resolving real‐life constraints in multi‐mode resource‐constrained projects.

show abstract

Section: Case Studymentioning

confidence: 99%

A Modified Variable Neighbourhood Search Heuristic for the Multi‐Mode Resource Constrained Project Scheduling Problem with A Case Study

Chakrabortt

Abbasi

Ryan

2019

INCOSE International Symp

View full text Add to dashboard Cite

show abstract

“…Choi, Realff and Lee (2004), combined heuristics procedures through Dynamic Programming; Tereso, Araujo, and Elmaghraby (2004) suggested approximation schemes to reduce the computational effort; Li and Womer (2015) developed efficient algorithms support on the rollout policy; and Creemers (2014Creemers ( , 2015 proposed algorithms based on Stochastic Dynamic Programming and their results were evaluated using computational experiments.…”

Section: Dynamic Programming Techniquementioning

confidence: 99%

The project scheduling problem with non-deterministic activities duration: A literature review

Pimiento

Serna

2018

JIEM

View full text Add to dashboard Cite

Abstract:Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration.Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved.Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends.Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.

show abstract

“…In [12,13,14,17,25], multi-skill project scheduling problems with different optimization objectives are formally described. In these problems, project activities require a given set of skills for their development, and also a given number of human resources for each skill into such set.…”

Section: Related Workmentioning

confidence: 99%

Project Scheduling: A Memetic Algorithm with Diversity-Adaptive Components that Optimizes the Effectiveness of Human Resources

Yannibelli

Amandi

2015

Polibits

View full text Add to dashboard Cite

Abstract-In this paper, a project scheduling problem is addressed. This problem supposes valuable assumptions about the effectiveness of human resources, and also considers a priority optimization objective for project managers. This objective is optimizing the effectiveness levels of the sets of human resources defined for the project activities. A memetic algorithm is proposed for solving the addressed problem. This memetic algorithm incorporates diversity-adaptive components into the framework of an evolutionary algorithm. The incorporation of these components is meant for improving the performance of the evolutionary-based search, in both exploitation and exploration. The performance of the memetic algorithm on instance sets with different complexity levels is compared with those of the heuristic search and optimization algorithms reported until now in the literature for the addressed problem. The results obtained from the performance comparison indicate that the memetic algorithm significantly outperforms the algorithms previously reported.Index Terms-Project scheduling, human resource assignment, multi-skilled resources, memetic algorithms, evolutionary algorithms, simulated annealing algorithms.

show abstract

Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming

Cited by 94 publications

References 41 publications

A Modified Variable Neighbourhood Search Heuristic for the Multi‐Mode Resource Constrained Project Scheduling Problem with A Case Study

A Modified Variable Neighbourhood Search Heuristic for the Multi‐Mode Resource Constrained Project Scheduling Problem with A Case Study

The project scheduling problem with non-deterministic activities duration: A literature review

Project Scheduling: A Memetic Algorithm with Diversity-Adaptive Components that Optimizes the Effectiveness of Human Resources

Contact Info

Product

Resources

About