Multi-objective Flowshop Scheduling

This work attempts to develop an algorithm in the area of multiobjective genetic algorithms by analyzing flowshop and kanban-controlled flowshop scheduling problems. The objectives of this research effort are two-fold: first, the development of the proposed Non-Dominated and Normalized-Distance-ranked-Sorting based Multi-objective Genetic Algorithm (NDSMGA) to generate non-dominated solutions; second, a detailed investigation of the proposed algorithm by considering the conventional flowshop scheduling problem and the kanban-controlled flowshop scheduling problem. The generation of a non-dominated solution set is quite useful to any decision maker. Given the set of non-dominated sequences, the decision maker can choose the sequence that satisfies his/her preference vector with respect to the objectives. It is noteworthy that the NDSMGA can handle any number of objectives due to the non-dominated sorting, and the computation of distance metric can be extended to address any number of objectives.

Autorentext

Dr S. Deva Prasad, Professor, Annamacharya Institute of Tech & Sciences (Autonomous), Rajampet, YSR Dist, AP, India, has received doctoral degree from Indian Institute of Technology Madras (2005). He received ME from MNNIT Allahabad (formerly MNREC), UP, India. He worked as a Research Analyst at M/s Lakshmi Machine Works, Coimbatore (2005-2009).