Development of a Resource Scheduling Model Using Optimization

The CPM has proven to be helpful only when the project deadline is not fixed and the resources are not constrained by either availability or time. Resource-constrained scheduling arises as a result of problems with the availability of resources. It is necessary to apply the availability of resources into a scheduling process for this reason. The objective of this paper is to present an optimal algorithm for a resource allocation model, which would be implemented into a framework for the development of an integration model. This framework for the development of an integration model for the resource-constrained scheduling is discussed. An optimal resource allocation model is presented within the framework of an integration model. Unlike present heuristic-based resource allocation models, the model does not depend on any set of heuristic rules, but adopts the concept of future float to set the order of priority when activities compete for resources. The model determines the shortest duration by allocating available resources to a set of activities simultaneously. Genetic algorithms (GAs) are adopted to search near-optimal solutions. A case example is solved to illustrate the performance and effectiveness of the resource allocation model. The results indicate that the model is capable of producing near-optimal scheduling alternatives, compared to a single solution that is produced by either the total float model or the least impact model.