Generalized robotic assembly line balancing problem

The aim of this thesis is to investigate robotic assembly line balancing problem and its extensions also to develop efficient solution methods. Firstly, robotic mixed-model assembly line balancing problem is studied and two mathematical models are presented for solving the problem. Moreover, a beam search algorithm is proposed to solve the large-size test problem. Secondly, a new mathematical model is developed for robotic parallel assembly line balancing problem. In addition, several improvement tools are enhanced to increase solution performance of the algorithm. The performances of the developed algorithms are measured on the test-problems. Thirdly, according to industry 4.0 concepts, a new line design is proposed, in which robots and human work together. In the proposed new line design, the human-robot interaction is analyzed. Mathematical models are proposed for a real and generalized case. For the large size problems, the improved beam search algorithm is proposed to solve the problem. The mathematical models are solved by using GAMS-CPLEX mathematical programming package and the heuristic algorithms have been compiled in MATLAB.