@inproceedings { , title = {Estimation of distribution algorithms for the multi-mode resource constrained project scheduling problem.}, abstract = {Multi-Mode Resource Constrained Project Problem (MRCPSP) is a multi-component problem which combines two interacting sub-problems; activity scheduling and mode assignment. Multi-component problems have been of research interest to the evolutionary computation community as they are more complex to solve. Estimation of Distribution Algorithms (EDAs) generate solutions by sampling a probabilistic model that captures key features of good solutions. Often they can significantly improve search efficiency and solution quality. Previous research has shown that the mode assignment sub-problem can be more effectively solved with an EDA. Also, a competitive Random Key based EDA (RK-EDA) for permutation problems has recently been proposed. In this paper, activity and mode solutions are respectively generated using the RK-EDA and an integer based EDA. This approach is competitive with leading approaches of solving the MRCPSP.}, conference = {2017 IEEE congress on evolutionary computation (CEC 2017)}, doi = {10.1109/CEC.2017.7969491}, note = {COMPLETED -- Still not on IEEExplore website 26/6/2017, 23/5/2017, 25/4/2017 LM -- Need to replace and update info once on IEEEXPLORE (mark Uploaded -Pending), possible pub on website Nov 2017 3/4/2017 LM -- Info via contact 29/3/2017 LM ADDITIONAL INFORMATION: Ayodele, Mayowa}, pages = {1579-1586}, publicationstatus = {Published}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, url = {http://hdl.handle.net/10059/2284}, keyword = {Multicomponent problems, Activity scheduling, Mode assignment, Multimode resource constrained projecte problem (MRCPSP)}, year = {2017}, author = {Ayodele, Mayowa and McCall, John and Regnier-Coudert, Olivier} }