Job shop scheduling using genetic algorithm incorporating priority rule

– Learning the priority rule using neural network –

Abstract

This paper deals with job shop scheduling problem with average weighted tardiness. An effective priority rule for this problem is constructed using a neural network. The neural network is learned from the input-output pairs obtained from schedules optimized using a genetic algorithm. Numerical experiments show that the neural network can generate better schedules than ATC rule which has three tuning parameters.