This research is concerned with finding the optimal solution of a job shop scheduling problem (JSSP) in a shorter time. As a result of recent trends such as Industry 4.0, machine learning has received a lot of attenti...
详细信息
This research is concerned with finding the optimal solution of a job shop scheduling problem (JSSP) in a shorter time. As a result of recent trends such as Industry 4.0, machine learning has received a lot of attention, and job shop scheduling methods using machine learning techniques have been developed. We have focused on hybridization of machine learning and mathematical optimization. A JSSP can be formulated as a 0-1 mixed integer programming, and it is expected that the optimal solution can be obtained in a shorter time by providing a good initial solution for the optimization algorithm by means of a learner constructed with data of scheduling performed previously. In our method based on this idea, the processing times of all operations are used as input features to predict a good value of each binary variable which represents the precedence relationship between two operations processed on the same machine. However, the information about the operations which are not related to the intended two operations may work as noise in learning and prediction. In this paper, two limitation methods of input features are proposed. In one of the methods, the processing times of only the operations processed on the same machine that the intended operations are processed are input to the learner. In the other methods, the processing times of those operations and their pre/post operations are input. Numerical experiments showed that these methods are effective at least from the point of view of efficient construction of a learner, because the number of nodes in the input and hidden layers can be reduced. From the aspect of better learning and prediction, both of the methods worked well, that is, they could find the optimal solution in a shorter time than the previous method in the cases where the previous method could not achieve good prediction and took a relatively long solution time. However, in the cases where the previous method could solve the problem in a relatively sho
This research is concerned with finding the optimal solution of a job shop scheduling problem (JSSP) in as short time as possible. A JSSP can be formulated as a 0-1 mixed integer programming (0-1 MIP), and it is expec...
详细信息
This research is concerned with finding the optimal solution of a job shop scheduling problem (JSSP) in as short time as possible. A JSSP can be formulated as a 0-1 mixed integer programming (0-1 MIP), and it is expected that the optimal schedule can be obtained in a shorter time by predicting a good solution based on data of scheduling performed previously and using the solution as the initial solution for the optimization algorithm. In this concept, it is an important point to predict a solution which satisfy constraints of the 0-1 MIP. This paper provides an improved method based on this concept where the prediction is carried out so that the constraints are always satisfied. Numerical experiments showed that solution time of the proposed method is shorter than that of the previous method, which does not assure the constraints are satisfied, and learning time reduces about half. In addition, it turned out that there is a reason of the shorter solution time other than that the predicted solution always satisfies the constraints. One possible reason is that the number of circular sequences tends to be smaller than the previous method. Further analysis and additional evaluations from this point of view will be performed in a future work.
With economic expansion having moderated to a "new normal" pace,the railway freight market share continues to be sluggish,and China's railways are transforming into modern logistics and carrying out pick...
详细信息
ISBN:
(纸本)9781510876996
With economic expansion having moderated to a "new normal" pace,the railway freight market share continues to be sluggish,and China's railways are transforming into modern logistics and carrying out pickup and delivery *** paper mainly focuses on the transportation lines of the external operations of the *** is fully analyzing that the transferring of the railway is highway transportation for the connection between the customer and the *** to the mixedinteger linear programming model with 0-1 variables based on comprehensive cost optimization,this paper built the model of pickup and delivery route selection,to determine the running route of the vehicle during the service process,as well as make sure the requirements of each customer can be satisfied and the total cost is ***12.0 is used to calculate the optimal solution,and we optimized the railway pickup and delivery service ***,the model is validated by the data of one day's bulk cargo pickup and delivery at a railway station of Shanghai as an example.
暂无评论