[BOOK][B] Evolutionary algorithms for solving multi-objective problems
CAC Coello - 2007 - Springer
Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …
solution has been a challenge to researchers for a long time. Despite the considerable …
Multi-objective optimisation using evolutionary algorithms: an introduction
K Deb - Multi-objective evolutionary optimisation for product …, 2011 - Springer
As the name suggests, multi-objective optimisation involves optimising a number of
objectives simultaneously. The problem becomes challenging when the objectives are of …
objectives simultaneously. The problem becomes challenging when the objectives are of …
A Diffused Memetic Optimizer for reactive berth allocation and scheduling at marine container terminals in response to disruptions
MA Dulebenets - Swarm and Evolutionary Computation, 2023 - Elsevier
The economic development of numerous countries is defined by maritime supply chains to a
great extent. Substantial volumes of containerized cargoes delivered by ships are handled …
great extent. Substantial volumes of containerized cargoes delivered by ships are handled …
Multi-objective optimization
CONTENTS 3.1 Introduction.................................................... 146 3.2 MO
Basics..................................................... 1463.2. 1 Principles of MO............................................ 147 …
Basics..................................................... 1463.2. 1 Principles of MO............................................ 147 …
Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems
This letter suggests an approach for decomposing a multiobjective optimization problem
(MOP) into a set of simple multiobjective optimization subproblems. Using this approach, it …
(MOP) into a set of simple multiobjective optimization subproblems. Using this approach, it …
Reference point based multi-objective optimization using evolutionary algorithms
Evolutionary multi-objective optimization (EMO) methodologies have been amply applied to
find a representative set of Pareto-optimal solutions in the past decade and beyond …
find a representative set of Pareto-optimal solutions in the past decade and beyond …
Decomposition-based algorithms using Pareto adaptive scalarizing methods
Decomposition-based algorithms have become increasingly popular for evolutionary
multiobjective optimization. However, the effect of scalarizing methods used in these …
multiobjective optimization. However, the effect of scalarizing methods used in these …
A multi-objective evolutionary algorithm for energy management of agricultural systems—a case study in Iran
Energy consumption and its negative environmental impacts are of interesting topics in the
recent centuries. Agricultural systems are both energy users and suppliers in the form of bio …
recent centuries. Agricultural systems are both energy users and suppliers in the form of bio …
A new many-objective evolutionary algorithm based on generalized Pareto dominance
In the past several years, it has become apparent that the effectiveness of Pareto-dominance-
based multiobjective evolutionary algorithms deteriorates progressively as the number of …
based multiobjective evolutionary algorithms deteriorates progressively as the number of …
Energy consumption enhancement and environmental life cycle assessment in paddy production using optimization techniques
In recent years, environmental impacts of energy consumption in different production
systems have become more adverse. Agricultural systems, as results of food security and …
systems have become more adverse. Agricultural systems, as results of food security and …