The paper incorporates new extensional strategies into the traditional multi-objective optimization algorithms to proficiently obtain the Pareto-optimal solutions in the presence of noise in the fitness landscapes. The first strategy, referred to as adaptive selection of sample size, is employed to assess the trade-off between accuracy in fitness estimation and the associated run-time complexit...

This paper introduces the basic theory and procedure for working out solutions of ant colony genetic algorithm, describes optimization, constraints and objectives of construction project scheduling, then establishes basic model for scheduling optimization of construction project, and put forward improved ant colony genetic algorithm for solving the basic model. Performance of ant colony genetic...

Fact Gathering means generating rule base from available numerical data or data base. The intelligence of a fuzzy system lies in its rule base. Generating rule base is one of the most important and difficult tasks when designing fuzzy systems. Various rule base generation methods are used such as Neural networks, genetic algorithms, biogeography based optimization approach, ant colony optimizat...

Ant colony optimization (ACO) is a technique for optimization that was introduced in the early 1990’s. The inspiring source o f ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete and continuous optimization problems and to important problems in telecommunications, such a...

the vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. in this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (nsga-ii) for pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. in thi...

Research in software testing has experienced a significant growth in recent years. One topic of special interest is fault detection techniques to reduce human interference and detect maximum faults. Priority is given to these techniques so that only higher priority techniques should be used instead of using individual techniques of lower priority. Bee Colony Optimization based upon natural phen...

The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Prob...

This chapter presents three MS Excel programs, namely, EMOO (Excel based Multi-Objective Optimization), NDS (Non-Dominated Sorting) and PM (Performance Metrics) useful for Multi-Objective Optimization (MOO) studies. The EMOO program is for finding non-dominated solutions of a given MOO problem. It has both binary-coded and realcoded NSGA-II (Elitist Non-Dominated Sorting Genetic Algorithm), and...