Abstract
This paper attempts to model capital budgeting problems by a new technique of dependent-chance integer programming as well as dependent-chance multiobjective programming and goal programming. Some examples are provided to illustrate the potential applications in the area of capital budgeting. A stochastic simulation based genetic algorithm is also designed to solve both chance constrained integer programming and dependent-chance integer programming models.
