Abstract
In this paper we studied, the problem of scheduling jobs on a single machine to minimize the multiple objective function and family setup time. This objective function is (total discount completion time and maximum tardiness respectively) which formulated as . for solving this problem, we derived a lower bound to be used in a branch and bound algorithm. We also proposed heuristic method in order to get an upper bound (near optimal solution). the proposed is number of dominance rules are considered to reduce the number of branches in the search tree. The genetic algorithm (GA) is used to obtain one of the upper bounds is used. The computational results are calculated by coding (programing) the algorithms using (MATLAP) and the final results up to (17) product (jobs) in a reasonable time are introduced by tables and added at the end of the research.
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