In low-thrust, gravity-assist trajectory design, two objectives are often equally important: maximization of final spacecraft mass and minimization of time-of-flight. Generally, these objectives are coupled and competing. Designing the trajectory that is best-suited for a mission typically requires a compromise between the objectives. However, optimizing even a single objective in the complex d...

This paper demonstrates that the self-adaptive technique of Differential Evolution (DE) can be simply used for solving a multiobjective optimization problem where parameters are interdependent. The real-coded crossover and mutation rates within the NSGA-II have been replaced with a simple Differential Evolution scheme, and results are reported on a rotated problem which has presented difficulti...

In this paper we present a study of the application of Evolutionary Computation methods to the optimisation of the start-up of a combined cycle power plant. We propose a multiobjective approach considering different objectives for the optimisation in order to reduce the pollution emissions and to maximise the efficiency of the plant. We compare a multiobjective evolutionary algorithm (NSGA-II) ...

This paper presents a comprehensive comparison between the performance of state-of-the-art genetic algorithms NSGA-II, SPEA2 and IBEA and their differential evolution based variants DEMO, DEMO and DEMO. Experimental results on 16 numerical multiobjective test problems show that on the majority of problems, the algorithms based on differential evolution perform significantly better than the corr...

The 0/1 knapsack problem is a well-known problem, which appears in many real domains with practical importance. The problem is NP-complete. The multiobjective 0/1 knapsack problem is a generalization of the 0/1 knapsack problem in which multiple knapsacks are considered. Many algorithms have been proposed in the past five decades for both single and multiobjective knapsack problems. A new versi...

We are interested in this paper in solving a multiobjective hybrid flowshop scheduling problem (HFS). The problem has different parameters and constraints such as release dates, due dates and sequence dependent setup times. Two different objectives should be optimized at once: the makespan and the total tardiness to be minimized. To solve the problem, we have developed two versions of a new dec...

Harmony Search metaheuristic is successfully used in several applications of science and engineering. However, its effectiveness in solving multiobjective optimization problems using the concepts of Pareto optimality, remains unproved. This paper presents two proposals of the Harmony Search metaheuristic for multiobjective optimization, using the ZDT functions as a test bed. Performance metrics...

It is a known fact that the performance of optimization algorithms for NP-Hard problems vary from instance to instance. We observed the same trend when we comprehensively studied multiobjective evolutionary algorithms (MOEAs) on a six benchmark instances of discrete time-cost trade-off problem (DTCTP) in a construction project. In this paper, instead of using a single algorithm to solve DTCTP, ...

This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite e...