A self-adaptive Pareto Evolutionary Multiobjective Optimization (EMO) algorithm based on differential evolution is proposed for evolving locomotion controllers in an artificially embodied legged creature. The objective of this paper is to demonstrate the trade-off between quality of solutions and computational cost. We show empirically that evolving controllers using the proposed algorithm incu...

In this work we present two new multiobjective proposals based on ant colony optimisation and random greedy search algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. Some variants of these algorithms have been compared in order to find out the impact of different design configurations and the use of heuristic information. Go...

The multiobjective evolutionary algorithm SMS-EMOA was shown by Emmerich et al. to outperform the well-established NSGA-II on a range of common test problems, using the S metric as comparison criterion. This study assesses which of the two algorithms performs best with respect to the optimization of water distribution networks, using the unconstrained three objective reformulation by Formiga et...

In this paper, we propose a new genetic algorithm for multi-objective optimization problems. That is called “Neighborhood Cultivation Genetic Algorithm (NCGA)”. NCGA includes the mechanisms of other methods such as SPEA2 and NSGA-II. Moreover, NCGA has the mechanism of neighborhood crossover. Because of the neighborhood crossover, the effective search can be performed and good results can be de...

Multiobjective optimization is increasingly used in engineering to design new systems and identify tradeoffs. Yet, problems often have objective functions constraints that are expensive highly nonlinear. Combinations of these features lead poor convergence diversity loss with common algorithms not been specifically designed for constrained optimization. Constrained benchmark exist, but they do ...

With the improvement of complexity and reliability mechanical equipment, it has been difficult for commonly used variational modal decomposition method vibration signal rotating machinery to meet current practical engineering requirements. In order further improve adaptability, processing efficiency, robustness fault diagnosis methods, a collaborative hybrid element heuristic multiobjective opt...

A well-designed battery thermal management system (BTMS) can achieve optimal cooling performance with less power consumption than a poorly-designed system. However, it is difficult to use the computational fluid dynamics (CFD) method perform an effective and design of BTMSs when there are several structural parameters multiple evaluation criteria. In this paper, instead CFD, compound surrogate ...

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several mult...

The Protein Structure Prediction problem, which involves correctly predicting the geometrical conformation of a fully folded protein, is extremely difficult to solve and there currently is no “best” method of generating solutions. This paper focuses on an energy minimization technique and the use of a multiobjective genetic algorithm, the multiobjective fast messy genetic algorithm (fmGA) to ob...