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

This paper studies a single-machine problem with resource allocation ( R A ) and deteriorating effect ( D E ). Under group technology ( G T ) and limited resource availability, our goal is to determine the schedules of groups and jobs within each group such that the total completion time is minimized. For three special cases, polynomial time algorithms are given. For a general case, a heuristic, a tabu search algorithm, and an exact (i.e., branch-and-bound) algorithm are proposed to solve this problem. [ABSTRACT FROM AUTHOR]