This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decide...

The primary goal of the research reported in this thesis is to identify what criteria are responsible for the good performance of a heuristic rule evaluation function in a greedy top-down covering algorithm both in classification and regression. We first argue that search heuristics for inductive rule learning algorithms typically trade off consistency and coverage, and we investigate this trad...

This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term contain...