.png){kind=icon}
Return
Solving project scheduling problems with resource constraints via an event list-based evolutionary algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2011.09.062.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
There are various scheduling problems with resource limitations and constraints in the literature that can be modeled as variations of the Resource Constrained Project Scheduling Problem (RCPSP). This paper proposes a new solution representation and an evolutionary algorithm for solving the RCPSP. The representation scheme is based on an ordered list of events, that are sets of activities that start (or finish) at the same time. The proposed solution methodology, namely SAILS, operates on the event list and relies on a scatter search framework. The latter incorporates an Adaptive Iterated Local Search (AILS), as an improvement method, and integrates an event-list based solution combination method. AILS utilizes new enriched neighborhoods, guides the search via a long term memory and applies an efficient perturbation strategy. Computational results on benchmark instances of the literature indicate that both AILS and SAILS produce consistently high quality solutions, while the best results are derived for most problem data sets. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords:
Project scheduling
Resource constraints
Evolutionary algorithms
Iterated Local Search
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
Organization
No organization information available
Cited Papers
.png){kind=icon}
Chaos-based improved immune algorithm (CBIIA) for resource-constrained project scheduling problems
PREAI
ShareSaveShareSaveShareSave
View more