One-dimensional Cutting Stock Problem With Capacity Constraints Based On Bee-swarm Genetic Algorithm

The one-dimensional cutting stock problem is a classic NP-Hard problem,One-dimensional cutting stock problem will processing the raw materials into partsof different lengths based on the dimension of raw materials for theone-dimensional case. when the problem is small-scale, using integer programming,dynamic programming and other traditional methods will be able to solve it. But forthe large-scale problem, because of its complexity situation, we need to useheuristic algorithms and intelligent algorithms to solve the problem. But mostresearches are built on the basis of actual production in stable condition, there islittle consider the enterprises are facing a lack of productivity, if companies stillfollowing the plan without adjusting it, maybe unable to complete the task on timeand cause loss or profit decline. Therefore, this paper take the limiting factor intoaccount to study this limited production capacity problem, the results show that themodel has some theoretical value and practical significance.First, a brief overview of the background and the present situation will begiven, then the overall structural of the paper is showing. After it, the paperintroduced the problem with capacity constraints and established the mathematicalmodel. Last, designed the algorithm which is suitable for the special problem andthe simulation results were given.