An exchange heuristic imbedded with simulated annealing for due-dates job-shop scheduling

Abstract

The generalized job shop scheduling (GJSS) problem with due dates is considered. Herein the objective is to minimize total job tardiness. An effective heuristic algorithm referred to as the Enhanced Exchange Heuristic Algorithm (EEHA) is presented for solving this type of problem. This algorithm integrates simulated annealing and the exchange heuristic algorithm by employing an insertion technique. It is shown that the algorithm is completed in polynomial time. Experimental results, generated over a range of shop sizes with different due date tightness, indicate that the proposed technique is competent to attain significant reductions in total tardiness in relation to initial schedules for relatively large-sized problems. Therefore, we would suggest that the approach presents an efficient scheduling alternative for this class of complex optimization problems.