A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version-Reference-Cited by-同舟云学术

A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version

Published:2003-09 Issue:2 Volume:149 Page:268-281
ISSN:0377-2217
Container-title:European Journal of Operational Research
language:en
Short-container-title:European Journal of Operational Research

Author:

Bouleimen K.,Lecocq H.

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modelling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference34 articles.

1. Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Computing;Aarts,1989

2. A robust genetic algorithm for resource allocation in project scheduling;Alcaraz;Annals of Operations Research,2001

3. Tabu search algorithms for resource-constrained project scheduling problems;Baar,1997

4. Some efficient multi-heuristic procedures for the resource-constrained project scheduling problem;Boctor;European Journal of Operational Research,1990

5. Heuristics for scheduling projects with resource restrictions and several resource-duration modes;Boctor;International Journal of Production Research,1993

Cited by 334 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Simulation of autonomous resource allocation through deep reinforcement learning-based portfolio-project integration;Automation in Construction;2024-06

2. A branch-and-bound algorithm for the proactive resource-constrained project scheduling problem with a robustness maximization objective;Computers & Operations Research;2024-06

3. The IoT resource allocation and scheduling using Elephant Herding Optimization (EHO-RAS) in IoT environment;International Journal of Information Technology;2024-03-27

4. Bi-objective multi-mode resource-constrained multi-project scheduling using combined NSGA II and Q-learning algorithm;Applied Soft Computing;2024-02

5. Solving a real-life multi-skill resource-constrained multi-project scheduling problem;Annals of Operations Research;2024-01-30