A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

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Metaheuristics: From Design to Implementation

http://www.vliz.be/imisdocs/publications/242609.pdf

Seawater intrusion processes, investigation and management: Recent advances and future challenges

A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering

We present a new global model of plate motions and strain rates in plate boundary zones constrained by horizontal geodetic velocities. This Global Strain Rate Model (GSRM v.2.1) is a vast improvement over its predecessor both in terms of amount of data input as in an increase in spatial model resolution by factor of ∼2.5 in areas with dense data coverage. We determined 6739 velocities from time series of (mostly) continuous GPS measurements; i.e., by far the largest global velocity solution to date. We transformed 15,772 velocities from 233 (mostly) published studies onto our core solution to obtain 22,511 velocities in the same reference frame. Care is taken to not use velocities from stations (or time periods) that are affected by transient phenomena; i.e., this data set consists of velocities best representing the interseismic plate velocity. About 14% of the Earth is allowed to deform in 145,086 deforming grid cells (0.25° longitude by 0.2° latitude in dimension). The remainder of the Earth's surface is modeled as rigid spherical caps representing 50 tectonic plates. For 36 plates we present new GPS-derived angular velocities. For all the plates that can be compared with the most recent geologic plate motion model, we find that the difference in angular velocity is significant. The rigid-body rotations are used as boundary conditions in the strain rate calculations. The strain rate field is modeled using the Haines and Holt method, which uses splines to obtain an self-consistent interpolated velocity gradient tensor field, from which strain rates, vorticity rates, and expected velocities are derived. We also present expected faulting orientations in areas with significant vorticity, and update the no-net rotation reference frame associated with our global velocity gradient field. Finally, we present a global map of recurrence times for Mw=7.5 characteristic earthquakes.

A geodetic plate motion and Global Strain Rate Model

Multi-objective meta-heuristics: An overview of the current state-of-the-art

The importance of water distribution network rehabilitation, replacement, and expansion is discussed The problem of choosing the best possible set of network improvements to make with a limited budget is presented as a large optimization problem to which conventional optimization techniques are poorly suited A multiobjective approach is described, using capital cost and benefit as dual objectives, enabling a range of noninferior solutions of varying cost to be derived A structured messy genetic algorithm is developed, incorporating some of the principles of the messy genetic algorithm, such as strings that increase in length during the evolution of designs The algorithm is shown to be an effective tool for the current optimization problem, being particularly suited both to the multiobjective approach and to problems that involve the selection of small sets of variables from large numbers of possibilities Two examples are included that demonstrate the features of the method and show that the algorithm performs much better than a standard genetic algorithm for a large network

Water network rehabilitation with structured messy genetic algorithm

This paper investigates the effectiveness of the genetic algorithm (GA) evolved neural network for rainfall-runoff forecasting and its application to predict the runoff in a catchment located in a semi-arid climate in Morocco. To predict the runoff at given moment, the input variables are the rainfall and the runoff values observed on the previous time period. Our methodology adopts a real coded GA strategy and hybrid with a back-propagation (BP) algorithm. The genetic operators are carefully designed to optimize the neural network, avoiding premature convergence and permutation problems. To evaluate the performance of the genetic algorithm-based neural network, BP neural network is also involved for a comparison purpose. The results showed that the GA-based neural network model gives superior predictions. The well-trained neural network can be used as a useful tool for runoff forecasting.

Driss Ouazar

Papers

Water network rehabilitation with structured messy genetic algorithm

Evolving neural network using real coded genetic algorithm for daily rainfall-runoff forecasting

New GPS constraints on active deformation along the Africa-Iberia plate boundary

Improved design of “Anytown” distribution network using structured messy genetic algorithms

Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems