This paper describes a novel evolutionary data-driven model (DDM) identification framework using the NSGA-II multi-objective genetic algorithm. The central concept of this paper is the employment of evolutionary computation to search for model structures among a catalog of models, while honoring the physical principles and the constitutive theories commonly used to represent the system/ process...

Multiagent systems have had a powerful impact on the real world. Many of the systems it studies (air traffic, satellite coordination, rover exploration) are inherently multi-objective, but they are often treated as single-objective problems within the research. A key concept within multiagent systems is that of credit assignment: quantifying an individual agent’s impact on the overall system pe...

....... An important problem in the realm of evolutionary multi-objective optimization (MOO) is that of finding all non-dominated fronts (NDFs). We specifically address the computational efficiency of the non-dominated sorting algorithm for finding the non-dominated fronts for the non-dominated sorting genetic algorithm II (NSGA-II) algorithm. We introduce the Limiting Index Sort (LIS) algorith...

One aspect that is often disregarded in evolutionary multiobjective research is the fact that the solution of a problem involves not only search but decision making. Most of approaches concentrate on adapting an evolutionary algorithm to generate the Pareto frontier. In this work we present a new idea to incorporate preferences in MOEA. We introduce a binary fuzzy preference relation that expre...

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to ac...

This paper proposes a new multi-objective evolutionary algorithm, called neighborhood exploring evolution strategy (NEES). This approach incorporates the idea of neighborhood exploration together with other techniques commonly used in the multi-objective evolutionary optimization literature (namely, non-dominated sorting and diversity preservation mechanisms). This idea of the proposed approach...

As a new model of networked manufacturing services, cloud (CMfg) aims to allocate enterprise resources, realize rational utilization and adapt increasingly complex user needs. However, previous studies on service composition optimal selection (SCOS) in CMfg environments do not incorporate carbon emissions into the quality (QoS) evaluation indicators. Therefore, SCOS for under low-carbon environ...

Polygonal surface models are typically used in three dimensional (3D) visualizations and simulations. They are obtained by laser scanners, computer vision systems or medical imaging devices to model highly detailed object surfaces. Surface mesh simplification aims to reduce the number of faces used in a 3D model while keeping the overall shape, boundaries and volume. In this work, we propose to...

To solve single and multi-objective optimization problems, evolutionary algorithms have been created. We use the non-dominated sorting genetic algorithm (NSGA-II) to find Pareto front in a two-objective portfolio query, its extended variant NSGA-III three-objective problem, this article. Furthermore, both we quantify Karush-Kuhn-Tucker Proximity Measure (KKTPM) for each generation determine how...

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...