Skip to Main content Skip to Navigation
Journal articles

A new shortest path algorithm to solve the resource-constrained project scheduling problem with routing from a flow solution

Abstract : In this study, the definition of a RCPSPR (Resource-Constrained Project Scheduling Problem with Routing) solution from a flow solution of the RCPSP is investigated. This new problem consists in defining a solution of RCPSPR that considers both routing and scheduling and that complies with a RCPSP flow, i.e., a solution where the loaded vehicle moves are achieved between activity and with a non-null flow. A shortest path algorithm is proposed to solve this problem with a labeling dynamic approach where a label provides all of the information about a solution, including the objective function, the system state and the remaining resources that allow the use of a dominance rule. The system state, described by the label, encompasses both the activities and the vehicle fleet information, including vehicle position and availability dates. Numerical experiments are limited to a comparative study with a proposed linear formulation since no previous publications exist on this problem. A time performance analysis of the proposed algorithm is carried out, proving the efficiency of the algorithm and clearing the way for integration into global iterative optimization schemes that will solve the RCPSPR to optimality.
Document type :
Journal articles
Complete list of metadatas

Cited literature [31 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01698361
Contributor : Mohamed Amine Mkadem <>
Submitted on : Tuesday, February 4, 2020 - 9:47:23 AM
Last modification on : Wednesday, February 5, 2020 - 2:56:21 PM
Long-term archiving on: : Tuesday, May 5, 2020 - 1:36:44 PM

File

Exact_RCPSPR_V27.pdf
Files produced by the author(s)

Identifiers

Citation

Philippe Lacomme, Aziz Moukrim, Alain Quilliot, Marina Vinot. A new shortest path algorithm to solve the resource-constrained project scheduling problem with routing from a flow solution. Engineering Applications of Artificial Intelligence, Elsevier, 2017, 66, pp.75-86. ⟨10.1016/j.engappai.2017.08.017⟩. ⟨hal-01698361⟩

Share

Metrics

Record views

431

Files downloads

180