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This paper concerns the total weighted tardiness on single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, 4 (four) heuristic methods are developed to solve real size applications including the size of 1000 jobs. The applied heuristics are: genetic, genetic with solution combination, kangaroo and genetic-kangaroo hybrid algorithms. Solutions denote that developed heuristics are efficient for the proposed model. Research of this topic shows that, no study exists on the total weighted tardiness problem with learning effect and unequal release dates together asserted in this paper.

RETRACTED ARTICLE: Approach towards problem solving on single machine scheduling with unequal release dates and learning effect