16 Result(s)
within
Bilel Derbel
Computer Science
Discrete Mathematics in Computer Science
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Chapter and Conference Paper
Dynamic Compartmental Models for Large Multi-objective Landscapes and Performance Estimation
Dynamic Compartmental Models are linear models inspired by epidemiology models to study Multi- and Many-Objective Evolutionary Algorithms dynamics. So far they have been tested on small MNK-Landscapes problems...
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Chapter and Conference Paper
On Stochastic Fitness Landscapes: Local Optimality and Fitness Landscape Analysis for Stochastic Search Operators
Fitness landscape analysis is a well-established tool for gaining insights about optimization problems and informing about the behavior of local and evolutionary search algorithms. In the conventional definiti...
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Chapter and Conference Paper
On the Design of a Partition Crossover for the Quadratic Assignment Problem
We conduct a study on the design of a partition crossover for the QAP. On the basis of a bipartite graph representation, we propose to recombine the unshared components from parents, while enabling their fast ...
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Chapter and Conference Paper
On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D
This paper intends to understand and to improve the working principle of decomposition-based multi-objective evolutionary algorithms. We review the design of the well-established Moea/d framework to support the s...
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Chapter and Conference Paper
Dominance, Indicator and Decomposition Based Search for Multi-objective QAP: Landscape Analysis and Automated Algorithm Selection
We investigate the properties of large-scale multi-objective quadratic assignment problems (mQAP) and how they impact the performance of multi-objective evolutionary algorithms. The landscape of a diversified ...
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Chapter and Conference Paper
On Pareto Local Optimal Solutions Networks
Pareto local optimal solutions (PLOS) are believed to highly influence the dynamics and the performance of multi-objective optimization algorithms, especially those based on local search and Pareto dominance. ...
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Chapter and Conference Paper
On the Design of a Master-Worker Adaptive Algorithm Selection Framework
We investigate the design of a master-worker schemes for adaptive algorithm selection with the following two-fold goal: (i) choose accurately from a given portfolio a set of operators to be executed in paralle...
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Chapter and Conference Paper
A Surrogate Model Based on Walsh Decomposition for Pseudo-Boolean Functions
Extensive efforts so far have been devoted to the design of effective surrogate models aiming at reducing the computational cost for solving expensive black-box continuous optimization problems. There are, how...
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Chapter and Conference Paper
Towards Landscape-Aware Automatic Algorithm Configuration: Preliminary Experiments on Neutral and Rugged Landscapes
The proper setting of algorithm parameters is a well-known issue that gave rise to recent research investigations from the (offline) automatic algorithm configuration perspective. Besides, the characteristics ...
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Chapter and Conference Paper
A Fitness Cloud Model for Adaptive Metaheuristic Selection Methods
Designing portfolio adaptive selection strategies is a promising approach to gain in generality when tackling a given optimization problem. However, we still lack much understanding of what makes a strategy ef...
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Chapter and Conference Paper
Multi-objective Local Search Based on Decomposition
It is generally believed that Local search (Ls) should be used as a basic tool in multi-objective evolutionary computation for combinatorial optimization. However, not much effort has been made to investigate how...
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Chapter and Conference Paper
Shake Them All!
In this paper, we build upon the previous efforts to enhance the search ability of Moea/d (a multi-objective decomposition-based algorithm), by investigating the idea of evolving the whole population simultaneous...
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Chapter and Conference Paper
An Analysis of Differential Evolution Parameters on Rotated Bi-objective Optimization Functions
Differential evolution (DE) is a very powerful and simple algorithm for single- and multi-objective continuous optimization problems. However, its success is highly affected by the right choice of parameters. ...
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Chapter and Conference Paper
On the Impact of Multiobjective Scalarizing Functions
Recently, there has been a renewed interest in decomposition-based approaches for evolutionary multiobjective optimization. However, the impact of the choice of the underlying scalarizing function(s) is still ...
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Chapter and Conference Paper
Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search
The emergence of new hybrid and heterogenous multi-GPUs multi-CPUs large scale platforms offers new opportunities and poses new challenges when solving difficult optimization problems. This paper targets irreg...
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Chapter and Conference Paper
Fast Deterministic Distributed Algorithms for Sparse Spanners
This paper concerns the efficient construction of sparse and low stretch spanners for unweighted arbitrary graphs with n nodes. All previous deterministic distributed algorithms, for constant stretch spanner of o
