In many real-world optimization problems the quality of solutions is determined with several fundamentally different objectives, such as, for example, cost, performance and profit. These objectives are often mutually conflicting thus yielding several optimal solutions, where each of them represents a different tradeoff between the objectives. Classicalmethods solve multiobjective optimization p...

The design of a water distribution system (WDS) involves finding an acceptable trade-off between multiple conflicting objectives, particularly in terms of minimizing cost and maximizing system benefits (such as hydraulic reliability). The goal in multi-objective optimization is to find a set of design solutions which embodies an acceptable trade-off between these costs and benefits, enabling th...

Railway electrification has attracted substantial interest in recent years as a key part of the global effort to achieve transport decarbonization. To improve energy efficiency train operations, particular is optimization speed trajectories. However, most studies formulate problem single-objective model and do not take into account mass uncertainty associated with passenger load variations. Thi...

This paper proposes a novel Multi-Objective Evolutionary Algorithm for hardware software partitioning of embedded systems. Customized genetic algorithms (GA) have been effectively used for solving complex optimization problems (NP Hard) but are mainly applied to optimize a particular solution with respect to a single objective. Many real world problems in embedded systems have multiple objectiv...

The problem of Scheduling Hot Rolling Pass of Steels is very complex because it has large spaces search for solutions. The aim of this work was the Multi-Objective Optimization (MOO) of hot rolling steel sheets in a finishing train of six steps, implementing the second generation of Nondominated Sorting Genetic Algorithm (NSGA-II). It was used two different crossover (AG1 y AG2) operators and t...

The simulation of land combat operations is a complex task. The space of possibilities is exponential and the performance criteria are usually in conflict; thus finding a sweet spot in this complex search space is a hard task. This paper focuses on the effect of population size and mutation rate on the performance of NSGA–II, as the evolutionary multiobjective optimization technique, to decide ...

In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-ba...

The QoS-driven Service Selection (QSS) problem is a wellknown NP-hard problem in the combinatorial optimization field. Although the QSS problem is naturally multi-objective optimization problem, most of the existing approaches solve the problem in single-objective optimization context. In the recent years, there have been some efforts to tackle the problem in multi-objective optimization contex...

Abstract This work addresses the use of a MO optimization algorithm to deal with reliability problem in order determine redundancy and each component system. Often, these problems are formulated as single-objective mixed variables (real-integer) is subject various design constraints. Classical solution approaches were limited most recent based on nature-inspired algorithms which belong artifici...

Process planning is an important function in a manufacturing system; it specifies the manufacturing requirements and details for the shop floor to convert a part from raw material to the finished form. However, considering only economical criterion with technological constraints is not enough in sustainable manufacturing practice; formerly, criteria about low carbon emission awareness have seld...