The production scheduling is a decision making process that plays an important role in the open pit mine operation. One of the most difficult problems in the area of production scheduling is the long-term production scheduling (LTPS). It is well known that this problem is complicated and large scale. The classical LTPS consists of scheduling a set of blocks on a set of push-backs with the objective to minimize/maximize a certain criterion, subjected to the constraint that each block has a specific processing order through cut-off grades, which are variable and known in advance. The flexible long-term production scheduling (FLTPS) problem is an extension of the classical LTPS that allows an operation to be processed on any block from a given set of alternative destinations. FLTPS is more complex than classical LTPS because of the additional need to determine the assignment of blocks for each destination. Later 90’s many researchers addressed long-term production scheduling (LTPS) by using simulated annealing, genetic algorithm, taboo search algorithm and ant colony algorithm. Known as meta-heuristic algorithms were proved most efficient algorithms to solve LTPS so far. In recent years, with the need of optimization problems in reality, all kinds of bioinspired optimization algorithms or swarm intelligence optimization algorithms have been proposed, such as the genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), simulated annealing (SA), dynamic programming and artificial intelligence (AI).

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