Resource aIIocation for an equipment deveIopment task is a compIex process owing to the inherent characteristics, such as Iarge amounts of input resources, numerous sub-tasks, compIex network structures, and high degrees of uncertainty. This paper presents an investigation into the influence of resource aIIocation on the duration and cost of sub-tasks. MathematicaI modeIs are constructed for the reIationships of the resource aIIocation quantity with the duration and cost of the sub-tasks. By considering the un-certainties, such as fluctuations in the sub-task duration and cost, rework iterations, and random overIaps, the tasks are simuIated for various resource aIIocation schemes. The shortest duration and the minimum cost of the deveIopment task are first formu-Iated as the objective function. Based on a muIti-objective particIe swarm optimization (MOPSO) aIgorithm, a muIti-objective evoIu-tionary aIgorithm is constructed to optimize the resource aIIocation scheme for the deveIopment task. FinaIIy, an uninhabited aeriaI vehicIe (UAV) is considered as an exampIe of a deveIopment task to test the aIgorithm, and the optimization resuIts of this method are compared with those based on non-dominated sorting genetic aIgorithm-II (NSGA-II), non-dominated sorting differentiaI evoIution (NSDE) and strength pareto evoIutionary aIgorithm-II (SPEA-II). The proposed method is verified for its scientific approach and effectiveness. The case study shows that the optimization of the resource aIIocation can greatIy aid in shortening the duration of the deveIopment task and reducing its cost effectiveIy.