The capacitated lot sizing problem with setup carryover deals with the issue of planning multiple products on a single machine. A setup can be carried over from one period to the next by incorporating the partial sequencing of the first and last product. This study proposes a novel hybrid approach by combining Genetic Algorithms (GAs) and a Fix-and-Optimise heuristic to solve the capacitated lot sizing problem with setup carryover. Besides this, a new initialisation scheme is suggested to reduce the solution space and to ensure a feasible solution. A comparative experimental study is carried out using some benchmark problem instances. The results indicate that the performance of the pure GAs improves when hybridised with the Fix-and-Optimise heuristic. Moreover, in terms of solution quality, promising results are obtained when compared with the recent results in the literature.
In today’s competitive and high technology world, companies are forced to differentiate themselves with continuous improvement. They need creative, well-educated and self-confident human resource more than ever. Hiring the right person to the right job plays a significant role on firm’s growth. The goal of this paper is to propose a systematic approach for personnel selection problem (PSP) of a textile company in Turkey by considering various performance requirements and criteria. The proposed framework consists of three phases. Initially, Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is used for weighting social criteria. Then, weights of technical requirements are calculated by applying Fuzzy Quality Function Deployment (QFD) method allowing to evaluate the interrelationships and correlation of social and technical criteria. Finally, Fuzzy Grey Relational Analysis (GRA) method has been applied to rank the alternatives by considering criteria scores acquired in the previous phase. The method has been illustrated by a case study and compared to the current approach used in the company. The results indicate that this proposed approach can deal with the PSP effectively and help companies to establish a systematic and unbiased way for the problem.