Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering

This paper focuses on a multiproject resource allocation problem ina bilevel organization. To solve this problem, a bilevel multiproject resource allocation model under a fuzzy randomenvironment is proposed. Two levels of decision makers areconsidered in the model. On the upper level, the company manageraims to allocate the company's resources to multiple projects toachieve the lowest cost, which include resource costs and atardiness penalty. On the lower level, each project manager attemptsto schedule their resource-constrained project, with minimization ofproject duration as the main objective. In contrast to priorstudies, uncertainty in resource allocation has been explicitlyconsidered. Specifically, our research uses fuzzy random variablesto model uncertain activity durations and resource costs. To searchfor the optimal solution of the bilevel model, a hybrid algorithmmade up of an adaptive particle swarm optimization, an adaptivehybrid genetic algorithm, and a fuzzy random simulation algorithm isalso proposed. Finally, the efficiency of the proposed model andalgorithm is evaluated through a practical case from an industrialequipment installation company. The results show that the proposedmodel is efficient in dealing with practical resource allocation problems in a bilevel organization