Project scheduling in supply chain environment

In this paper, we study scheduling of several projects in supply chain environment; activities of these projects are performed by some contractor companies. We present a new practical model for solving project scheduling problem in supply chain environment. A genetic algorithm and a simulated annealing algorithm are proposed for solving our model. The elements of genetic algorithm such as generation, mutation, crossover, and also the elements of simulated annealing algorithm like each neighborhood are explained. Our proposed algorithms in comparison with one of the most powerful solvers (Lingo) generate appropriate solutions where Lingo cannot generate optimal solution for large size problems in a reasonable time. Some numerical examples are solved, and results show that these two algorithms can find promising solutions.