This paper considers a single machine scheduling problem with the learning effect and multiple availability constraints that minimizes the total completion time. To solve this problem, a new binary integer programming model is presented, and a branch-and-bound algorithm is also developed for solving the given problem optimally. Since the problem is strongly NP-hard, to find the near-optimal solution for large-sized problems within a reasonable time, two meta-heuristics; namely, genetic algorithm and simulated annealing are developed. Finally, the computational results are provided to compare the result of the binary integer programming, branch-and-bound algorithm, genetic algorithm and simulated annealing. Then, the efficiency of the proposed algorithms is discussed. © 2012 Elsevier Inc.
Vahedi-Nouri, B., Fattahi, P., Rohaninejad, M., & Tavakkoli-Moghaddam, R. (2013). Minimizing the total completion time on a single machine with the learning effect and multiple availability constraints. Applied Mathematical Modelling, 37(5), 3126–3137. https://doi.org/10.1016/j.apm.2012.07.028