DEPENDENT-CHANCE INTEGER PROGRAMMING APPLIED TO CAPITAL BUDGETING

Genetic Programming Applied to Mixed Integer Programming

We present the application of Genetic Programming (GP) in Branch and Bound (B&B) based Mixed Integer Linear Programming (MIP). The hybrid architecture introduced employs GP as a node selection expression generator: a GP run, embedded into the B&B process, exploits the characteristics of the particular MIP problem being solved, evolving a problem-specific node selection method. The evolved metho...

Linear Programming and Capital Budgeting: Commeke

Firefly Algorithm Applied to Integer Programming Problems

Firefly algorithm is a recently added member of the swarm intelligence heuristics family. In this paper the firefly algorithm is adjusted and applied to integer programming problems. In order to deal with integer programming problems, firefly algorithm rounds the parameter values to the closest integer after producing new solutions. The performance of firefly algorithm is tested on seven proble...

Improved Integer Programming Approaches for Chance-Constrained Stochastic Programming

The Chance-Constrained Stochastic Programming (CCSP) is one of the models for decision making under uncertainty. In this paper, we consider the special case of the CCSP in which only the righthand side vector is random with a discrete distribution having a finite support. The unit commitment problem is one of the applications of the special case of the CCSP. Existing methods for exactly solving...

A Chance Constrained Integer Programming Model for Open Pit Long-Term Production Planning

The mine production planning defines a sequence of block extraction to obtain the highest NPV under a number of constraints. Mathematical programming has become a widespread approach to optimize production planning, for open pit mines since the 1960s. However, the previous and existing models are found to be limited in their ability to explicitly incorporate the ore grade uncertainty into the p...