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When some coefficients involved in nonlinear programming problems are taken as interval numbers, the problem becomes more challengeable than the original one. In the paper, a nonlinear programming problem with interval objective coefficients is considered, and a genetic algorithm is presented. Firstly, the original problem is transformed into a bilevel programming model without interval coefficients. In addition, a genetic algorithm is designed and used to deal with the transformed problem, in which the search space is decided by these intervals given in the original problem. Based on the proposed approach, the best and the worst optimal solutions as well as some intermediate solutions can be obtained. Finally, a computational example is solved and the results show that the proposed algorithm is efficient and robust.

An Optimization Approach for Nonlinear Programming Problems with Interval Coefficients