Study on resource allocation scheduling problem with learning factors and group technology

This paper investigates the single-machine resource allocation scheduling problem with learning effects and group technology. The objective is to determine optimal job schedules, allocations such that total completion time minimized subject limited availability. For some special cases, we show remains polynomially solvable. general case of problem, propose heuristic algorithm, tabu search algorithm branch-and-bound algorithm. Numerical experiments are tested evaluate performance algorithms.