This paper uses a modified Ant Colony Optimization (ACO) algorithm to price simple financial derivatives. We use ants to find the optimum time to exercise an option. Our algorithm searches the solution space to find optimum solution under some user defined constraints. In this preliminary study we show that the modified ACO works in predicting an optimum exercise time of a simple vanilla option.

The increased use of private vehicles has caused significant traffic congestion, noise and air pollution. Public transport is often incapable of effectively servicing non-urban areas. Car pooling, where sets of car owners having the same travel destination share their vehicles, has emerged to be a viable possibility for reducing private vehicle usage around the world. This paper describes a clu...

The car sequencing problem involves scheduling cars along an assembly line while satisfying capacity constraints. In this paper, we describe an Ant Colony Optimization (ACO) algorithm for solving this problem, and we introduce two different pheromone structures for this algorithm: the first pheromone structure aims at learning for “good” sequences of cars, whereas the second pheromone structure...

Rich vehicle routing problems try to represent situations that can be found in reality. Starting from a case study, in this paper a rich vehicle routing problem is analyzed. The elements that characterize it are mainly the presence of multiple objectives, constraints concerning multiple time windows, heterogeneous fleet, maximum duration of the subtours, and multiple visits. Two variants of the...

The Vehicle Routing Problem with Time Windows relates to frequently occuring real world problems in logistics. Much work has been done on solving static routing problems but solving the dynamic variants has not been given an equal amount of attention, while these are even more relevant to most companies in logistics and transportation. In this work an Ant Colony Optimization algorithm for solvi...

Ant Colony Optimization (ACO) algorithms belong to class of metaheuristic algorithms, where a search is made for optimized solution rather than exact solution, based on the knowledge of the problem domain. ACO algorithms are iterative in nature. As the iteration proceeds, solution converges to the optimized solution. In this paper, we propose new updation mechanism based 1 / 4

Creative product is special product, which has characteristics like short product life cycle, big market risk and so on. The market is changed very soon, and the needs of customers are changed quickly, too. In order to increase the profit and decrease the cost, it is necessary to forecast the demand and make production plan. The product plan is developed according to the quantity of demand, but...

This paper introduces a centralized approach to data gathering and communication for wireless sensor networks. Inspired by the social behaviors of natural ants, we clearly partition the task for the base station and sensor nodes in a wireless sensor network according to their different functions and capabilities. An ant colony optimization method is employed at the base station to form a near-o...

In this paper a Population-based Ant Colony Optimization approach is proposed to solve multi-criteria optimization problems where the population of solutions is chosen from the set of all non-dominated solutions found so far. We investigate different maximum sizes for this population. The algorithm employs one pheromone matrix for each type of optimization criterion. The matrices are derived fr...

K e y words: Vehicle Routing Problems, backhauling strategies, Ant Colony Optimization