A heuristic genetic algorithm for product portfolio planning

For any manufacturing company, product portfolio planning constitutes one of the most important decisions regarding how to offer the "right" products to the target market. Essentially, such decisions exhibit a typical combinatorial optimization problem, which deems to be very complex and hard to solve using conventional optimization techniques. Enumeration is inhibitive if the problem size is extremely large. Genetic algorithms (GAs) have been proven to excel in solving combinatorial optimization problems. This paper develops a heuristic GA to tackle the product portfolio planning problem.