Hybrid Genetic Algorithm for Solving Job Scheduling Problem on Non-identical Parallel Machines Based on JIT Technique
Haidong Guo · Computer Integrated Manufacturing Systems · 2004
A hybrid genetic algorithm (HGA) is presented for the problem of minimizing the range of lateness and make-span on parallel non-identical machines, which is a NP-complete. There are two new method presented for the HGA. Firstly, a dynamic fitness function is introduced according to the requirement of the scheduling problem. Secondly, a simple coding method for the HGA is given. This new coding method does not include the ranking information of job list, and it embeds the optimal effective algorithm for solving the corresponding single machine problem, which makes the HGA easy programming and enhances the efficiency of the HGA. Numerical simulations illustrate that the HGA has the properties of fast convergence, and can be used to solve larger size problems.