Problem Structure and Owshop Scheduling

Many algorithms leverage structure to solve problems. In owshop scheduling , we study two types of structure. First, for each job, we generate processing times that are similar across all machines (job-correlated problems). Then, for each machine, we generate processing times that are similar for all the jobs (machine-correlated problems). For these types of problems, we study the innu-ence of structure on the search landscape generated by local search operators. It has been shown that for randomly generated problems the shift operator induces a big-valley structure. We show that for both job-correlated and machine-correlated problems the big-valley structure degrades into a stepped-valley structure composed of plateaus of equivalent tness solutions. A good lower bound is useful when assessing the quality of a owshop scheduling solution. For job-correlated owshop problems, the traditional lower bound computation is extremely poor. We present a new, tighter lower bound computation and prove its correctness.