Job-Shop Scheduling Using a Neural Network to Estimate Margins to Due-Dates
نویسندگان
چکیده
منابع مشابه
Using neural network to estimate weibull parameters
As is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. Weibull distribution involves in reliability studies frequently and has many applications in engineering. However estimating the parameters of Weibull distribution is crucial in classical ways. This distribution has t...
متن کاملJob Shop Scheduling with Fixed Delivery Dates
Abstract—In most classical scheduling models, a job is assumed to deliver to a customer at the instant of a job processing completion. In numerous practical situations, however, multiple delivery dates exist, where the time interval between any two consecutive delivery dates is constant. This type of fixed delivery strategy results in substantial cost savings for transportation and handling. Th...
متن کاملusing neural network to estimate weibull parameters
as is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. weibull distribution involves in reliability studies frequently and has many applications in engineering. however estimating the parameters of weibull distribution is crucial in classical ways. this distribution has t...
متن کاملArchitectural Design of Neural Network Hardware for Job Shop Scheduling
By combining neural network optimization ideas with “Lagrangian relaxation” for constraint handling, a novel Lagrangian relaxation neural network (LRNN) has recently been developed for job shop scheduling. This paper is to explore architectural design issues for the hardware implementation of such neural networks. A digital circuitry with a micro-controller and an optimization chip is designed,...
متن کاملA Novel Hopfield Neural Network Approach to Job-Shop Scheduling Problems
This paper proposes a novel method based on Hopfield neural networks (HNNs) for solving job-shop scheduling problems (JSPs). The JSP constraints are analyzed and their permutation matrix express is developed. A new calculation energy function is also proposed, which includes all JSP constraints. A novel Hopfield neural network for such JSP problems is constructed and the effect of its weights f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEJ Transactions on Electronics, Information and Systems
سال: 1995
ISSN: 0385-4221,1348-8155
DOI: 10.1541/ieejeiss1987.115.5_744