Research And Implementation Of Container Loading Problem Based On Application Constraint

Container loading is a kind of combinatorial optimization problems that loads a largenumber of heterogeneous goods, which have their volumes, weights, values and numbers,into the container with the given space size and weight limitation. Loading schemeconsiders not only improving of space utilization and safe factors in transportation, but alsomaximizing the value of the goods with different types and numbers.Although the research on container loading has put forward some feasible solutions sofar, the aim of most research is only to improve the space utilization. A small number ofresearches consider application constraints. Few researches focused on the constraint ofload bearing strength which is one of important practical factors required in the case wherethere are different types of goods. Due to the consideration of application constraints, thisleads to reduce the space utilization and change the solution objective. Moreover, solvingthe problem is getting more difficult. This paper introduces an ant colony optimizationalgorithm to solve container loading problem with the constraints of stability and loadbearing strength from the viewpoint of global optimization.This paper puts forward an ant colony algorithm based on a three-space description.Through simulating the process of ant foraging, transfer and barrier, the algorithmgenerates loading sequence of goods. Meanwhile, a number of goods with identical typeare combined to form a block and the block is loaded into the residual space according todesigning position rules, space handling and constraint conditions handling methods.Finally, the algorithm produces the best loading scheme. Furthermore, the algorithmexploits six space partitions, and analyses and evaluates the influence of the spaceutilization under the conditions of six partitions. Two space partitions which ensure thegoods stability are presented.According to the weight of loading goods, the definition of constraints of load bearingstrength is described. This algorithm combines load bearing strength with space partitions and designs the related strategies. It effectively integrates the handling method for loadbearing strength into the ant colony algorithm. It not only improves the space utilizationbut also avoids the damage of the goods.The algorithm is tested by using the benchmark data set. Through comparison amongthe published literature, and test and analysis of the ant colony algorithm, the experimentalresults have shown that the ant colony algorithm can effectively solve the container loadingproblem based on load bearing strength and stability. The graphical layout has greatsignificance application for the container loading system. In addition, the advantages anddisadvantages of the algorithm are pointed to and the future research field and work aredrawn.