Robust optimization models for project scheduling with resource availability cost

Yamashita, Denise Sato; Armentano, Vinı́cius Amaral; Laguna, Manuel

doi:10.1007/s10951-006-0326-4

Cited by 75 publications

(32 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…(10). Constraint (11) mentions that the tardiness of projects cannot be negative. Constraints (12) and (13) introduce the nonnegative decision variables of the start time of activities and the resource flow between the activities, respectively.…”

Section: The Notationsmentioning

confidence: 99%

“…The major advantages of robust optimization compared to stochastic programming are that no assumptions are needed regarding the underlying probability distribution of the uncertain data [11]. It is also true when comparing the robust optimization approach with the fuzzy approach because there is no need for RO to define membership function for the uncertain parameter.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Optimization for the Resource Constrained Multi-Project Scheduling Problem with Uncertain Activity Durations

2018

View full text Add to dashboard Cite

This paper studies the multi-project scheduling problem which involves multiple projects with different importance weight; with predefined assigned due dates; with activities that have uncertain durations; and with renewable resources that are constrained. The resource sharing policy is applied to share the resources among projects. Due to the environmental rapid changes and also the uniqueness of projects, the probability distribution function of uncertain durations cannot be estimated with confidence. Besides, the multi-project scheduling problem with its large scale investment dictates a conservative approach to deal with the existing uncertainty. Therefore, the Robust Resource-Constrained Multi-Project Scheduling Problem (RRCMPSP) is studied in this paper while the maximum total weighted tardiness of the projects should be minimized. A scenario-relaxation algorithm is implemented which results in optimal solutions for the RRCMPSP. The aim is to find an optimal structure containing all the projects in such a way that it transfers the resources between the activities based on the resource sharing policy while the maximum weighted differences between the projects finish times and their assigned due dates will be minimum.

show abstract

Section: The Notationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Optimization for the Resource Constrained Multi-Project Scheduling Problem with Uncertain Activity Durations

2018

View full text Add to dashboard Cite

show abstract

“…∑ k C k (R k ), where C k is a discrete non-decreasing cost function of resource k and the capacity levels R k are variables. A special case is obtained from the linear cost function C k (R k ) = c k · R k , where c k is the per-unit cost of resource k. The resource investment problem has recently been tackled by Drexl and Kimms [61], Neumann and Zimmermann [137], Neumann et al [138], Ranjbar et al [152], and Yamashita et al [195].…”

Section: Objectives Based On Renewable Resourcesmentioning

confidence: 99%

A survey of variants and extensions of the resource-constrained project scheduling problem

Hartmann

Briskorn

2010

European Journal of Operational Research

745

356

View full text Add to dashboard Cite

“…(Yamashita, Armentano, & Laguna, 2007) have discussed the difference between solution-robust solutions (Which is defined as the solution which remains optimal or close to optimal for any problem scenario), and model-robust solutions (defined as the solution which remains feasible or almost feasible for any scenario).…”

Section: Robust Resource Investment Problemmentioning

confidence: 99%

Robust Resource Investment Problem with Time-Dependent Resource Cost and Tardiness Penalty

Hattab¹,

Haouari

2016

2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

View full text Add to dashboard Cite

The Resource Investment Problem (RIP) is a variant of the well-known Resource Constraint Project Scheduling Problem (RCPSP) that requires finding the optimal resource allocation, given a preset completion date, with the objective of minimizing the total cost.The practical relevance of RIP is very obvious; since the decision maker (the project manager for example) wants to know what resources are required to achieve the targeted project completion date. RIP helps to decide the amount of investment in resources that yield the optimal solution, in addition to the optimal tradeoff between completion time and resource investment.In practice, most of the projects are associated with due dates beyond which a tardiness penalty may be applied. To avoid the tardiness penalty, project managers sometimes decide to add more resources, thereby increasing resource investment cost, to the project to finish earlier. The experiments revealed the usefulness of the algorithm in finding relatively robust solution for small problem sizes.

show abstract

Robust optimization models for project scheduling with resource availability cost

Cited by 75 publications

References 30 publications

Robust Optimization for the Resource Constrained Multi-Project Scheduling Problem with Uncertain Activity Durations

Robust Optimization for the Resource Constrained Multi-Project Scheduling Problem with Uncertain Activity Durations

A survey of variants and extensions of the resource-constrained project scheduling problem

Robust Resource Investment Problem with Time-Dependent Resource Cost and Tardiness Penalty

Contact Info

Product

Resources

About