A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem

Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches.

Self-ordered pointing as a test of working memory in typically developing children

The self-ordered pointing test (SOPT; Petrides & Milner, 1982) is a test of non-spatial executive working memory requiring the ability to generate and monitor a sequence of responses. Although used with developmental clinical populations there are few normative data against which to compare atypical performance. Typically developing children (5!11 years) and young adults performed two versions of the SOPT, one using pictures of familiar objects and the other hard-to-verbalise abstract designs. Performance improved with age but the children did not reach adult levels of performance. Participants of all ages found the object condition easier than the abstract condition, suggesting that verbal processes are utilised by the SOPT. However, performance on the task was largely independent from verbal and nonverbal cognitive ability. Overall the results suggest that the SOPT is a sensitive measure of executive working memory.