Research On Storage Optimization Algorithm Of Automatic Solid Warehouse

The storage optimization confirmed the right store location of every material basis definite storage strategy and storage rule, in order to replenishment faster and storage more material. I researched a warehouse which is special in this article. This warehouse contains some cabins which disperse in some elevator vertical shaft, every cabin storage unique material type. It is difficult to achieve because of huge restrict conditions, storage rule and so many material types.Along with the development of intelligent optimization algorithm, solving this kind of multiple target optimization such as storage optimization. The main works in this paper as follows:1st. Building the math model of storage optimization issueAim at the special cabins and materials, taking into account of restrict conditions,for example,different cabins and different materials, building the math model and designing the following model.2nd.Creating a concept of abundance coefficientAfter we get the initialization solution or the Pareto concourse, in order to satisfy the demand of every task, should adjust the storage materials in cabins according to the abundance coefficient. But the adjustment can not be aimlessly. The abundance coefficient giving directions of adjustment,if a material which abundance coefficient value less than other materials, should increase storage amount, else, should decrease storage amount.3rd.Ameliorate the simple Genetic AlgorithmThe simple Genetic Algorithm exist many problems to solving storage optimization in this article; the most obviously is the convergent issue. So, advanced the simple GA in this article; using real number matrix encoding, easily to see and calculate, saving coding space; designing select function and crossover and mutation operation to suit the real number matrix encoding and the restrict conditions, decreasing the arises of occur that breach restrict conditions; aim at the occur that breach restrict conditions back of the operation GA,designing a adjustment function, satisfying the precondition of pattern stabilization for the most part, increase diversity of population; be cognizant of advantage and disadvantage of GA and Simulated Annealing Algorithm, blending this two optimization algorithm, exerted their predominance,get better effect; designing end conditions with self-adaption, increased calculated efficiency.