Multi-objective loading of goods is a complicated combinatorial optimization problems are NP hard problems, this paper, hybrid particle swarm algorithm to solve multi-objective problem loading cargo. Hybrid Particle Swarm Algorithm in elementary particle swarm optimization based on genetic algorithm through the introduction of crossover and mutation of the strategy to avoid a fall into local optimum, global optimum to achieve accelerated convergence. In addition, this paper, the weight factor used to balance the various objectives so that the objectives can be achieved relatively better results.

Goods Allocating Problem with Multi-Aims based on The Hybrid Particle Swarm Algorithm
.....................................................................................\crossover.m
.....................................................................................\fitness.m
.....................................................................................\HPSO.m
.....................................................................................\mutation.m
.....................................................................................\PSO.m
.....................................................................................\PSOdata.mat
.....................................................................................\PSO_con.m
.....................................................................................\PSO_conV.m

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