Using genetic algorithms to solve the multi-product JIT sequencing problemwith set-ups

This paper presents a methodology to solve the Just-in-Time (JIT) sequencin g problem for multiple product scenarios when set-ups between products are required. Problems of this type are combinatorial, and complete enumeration of all possible solutions is computationally prohibitive. Therefore, Genet ic Algorithms are often employed to rnd desirable, although not necessarily optimal, solutions. This research, through experimentation, shows that Gen etic Algorithms provide formidable solutions to the multi-product JIT seque ncing problem with set-ups. The results also compare favourably to those fo und using the search techniques of Tabu Search and Simulated Annealing.