An adaptive crossover genetic algorithm with simulated annealing for multi mode resource constrained project scheduling with discounted cash flows

This paper presents an adaptive crossover genetic algorithm with simulated annealing metaheuristic procedure for solving a multimode resource‐constrained project scheduling problem with discounted cash flows for minimising costs. To solve the problem, a genetic algorithm is proposed for the global search, and simulated annealing is used for the local search. Two crossover operators are employed. A mathematical model is developed for the problem. Detailed computational experiments are performed on a standard problem set with randomly generated resource costs to evaluate the performance of the proposed hybrid approach.