A SEARCH HEURISTIC FOR JUST-IN-TIME SCHEDULING IN PARALLEL MACHINES

In recent years the Just-in-Time (JIT) production philosophy as been adopted by many companies around the world. This has motivated the study of scheduling models that embrace the essential components of JIT systems. In this paper, we present a search heurustic for the weighted earliness penalty problem with deadlines in parallel identical machines. Our approach combines elements of the solution methods known as greedy randomized adaptive search procedure (GRASP) and tabu search. It also uses a branch-and-bound post-processor to optimize individually the sequence of the jobs assigned to each machine.