Research To The Hybrid Flow Shop Scheduling Base On The Adaptive Genetic Algorithms

With the market to fieriness, it has being become the main product model that facing to customer'order, many kinds and small batch producing. JIT is just for this. But how do about to realize delivery just in time? The product schedule how about to be disassembled to the idiographic machines? How about do to seek for the rational scheduling? Realizing the delivery and workshop's finish time is the same time. So that can achieve the resource and schedule perfectly matching, this is a complicated problem.Constitutionally speak: the scheduling belongs to combinatorics category. The scheduling number of combinations is rapid rise suddenly and sharply when the task and resource being extending, that just is NP questions. How do about to look for the best scheduling from so many. That is an important question of optimize algorithms.Nowdays among so many optimum algorithms, GA as a non-confirm, bionic-zoology, randomicity perfect algorithms has been wide applied. Because of it have some characters as the independent of the question's model, the whole area best, being connotative and side-by-side etc. that can be applied in workshop scheduling.The rational scheduling is set down base on delivery time, so can controll it to minimum which difference degree between finish time and delivery time. So it could brings profit from two sides: one side, the start time of each job can be obtained accurately, it will be realized to control exactly the time of raw materials arriving the storage and decreasing the storage fares in this way, at one time accelerateing the flow speed for raw materials and capital, improving the rate production; on the other hand, it can be minimized which the punishing as delay. So established the basic to realize the JIT, because these are decrease on storage cost and funishing cost two sides.In this paper, to raise a sort of Adaptive Genetic Algorithms (AGA) base on large mutation operator for the hybrid flow shop scheduling. There are chromosome coding and corresponding arithmetic operators, to do simulation using MATLAB programme. As follows points are the primary works in this paper:1. Established the mathematic model for workshop scheduling of Leadframe produaction by the goal of just in time delivery.2. To rise a sort of Genetic Algorithms to hybrid flow shop problem, gived the encoding and decoding method to chromosome and the each genetic operator.3. Improved the crossing and mutation operators to adaptive the condition by self for enhancing the search ability of algorithms in whole area.4. To inset the local search algorithms into the AGA for strengthening the local search ability of AGA.5. For increasing the search speed of algorithms: one good unit is beded the original colony which be constructed heuristic algorithms, and the programme is vectized, so accelerated the convergences speed of AGA.6. The AGA algorithms performance had been attested by simulation in the matlab, the validity of AGA algorithms have been showed from practice application.