Date of Award
2014
Document Type
Dissertation
Degree Name
Ph.D. in Business Administration
Department
Marketing
First Advisor
Cesar Rego
Second Advisor
Hugh Sloan
Third Advisor
Philip J. Rhodes
Relational Format
dissertation/thesis
Abstract
The resource constrained project scheduling problem (RCPSP) is one of the most intractable problems in operations research; it is NP-hard in the strong sense. Due to the hardness of the problem, exact solution methods can only tackle instances of relatively small size. For larger instances commonly found in real applications heuristic solution methods are necessary to find near-optimal solutions within acceptable computation time limits. In this study algorithms based on the relaxation adaptive memory programming (RAMP) method (Rego, 2005) are developed for the purpose of solving the RCPSP. The RAMP algorithms developed here combine mathematical relaxation, including Lagrangian relaxation and surrogate constraint relaxation, with tabu search and genetic algorithms. Computational tests are performed on an extensive set of benchmark instances. The results demonstrate the capability of the proposed approaches to the solution of RCPSPs of different sizes and characteristics and provide meaningful insights to the potential application of these approaches to other more complex resource-constrained scheduling problems.
Recommended Citation
Riley, Robert Christopher-Lee, "Relaxation Adaptive Memory Programming For The Resource Constrained Project Scheduling Problem" (2014). Electronic Theses and Dissertations. 392.
https://egrove.olemiss.edu/etd/392
Concentration/Emphasis
Emphasis: Marketing