A simultaneous transit network design and frequency setting: Computing with bees

• The transit network design problem with simultaneous frequency setting is considered in the paper.
• Greedy heuristic and Bee Colony Optimization (BCO) metaheuristic are developed for the problem considered.
• The numerical experiments are performed on the well-known benchmark problem.
• The proposed model outperformed the other models known from the literature.

The transit network design problem belongs to the class of hard combinatorial optimization problem, whose optimal solution is not easy to find out. We consider in this paper the transit network design problem in a way that we simultaneously determine the links to be included in the transit network, assemble chosen links into bus routes, and determine bus frequency on each of the designed routes. Our approach to the transit network design problem is based on the Bee Colony Optimization (BCO) metaheuristic. The BCO algorithm is a stochastic, random-search technique that belongs to the class of population-based algorithms. This technique uses a similarity among the way in which bees in nature look for food, and the way in which optimization algorithms search for an optimum of a combinatorial optimization problem. The numerical experiments are performed on known benchmark problems. We clearly show that our approach, based on the BCO algorithm is competitive with the other approaches in the literature and that can generate high-quality solutions.