98 research outputs found
Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives
The properties of local optimal solutions in multi-objective combinatorial
optimization problems are crucial for the effectiveness of local search
algorithms, particularly when these algorithms are based on Pareto dominance.
Such local search algorithms typically return a set of mutually nondominated
Pareto local optimal (PLO) solutions, that is, a PLO-set. This paper
investigates two aspects of PLO-sets by means of experiments with Pareto local
search (PLS). First, we examine the impact of several problem characteristics
on the properties of PLO-sets for multi-objective NK-landscapes with correlated
objectives. In particular, we report that either increasing the number of
objectives or decreasing the correlation between objectives leads to an
exponential increment on the size of PLO-sets, whereas the variable correlation
has only a minor effect. Second, we study the running time and the quality
reached when using bounding archiving methods to limit the size of the archive
handled by PLS, and thus, the maximum size of the PLO-set found. We argue that
there is a clear relationship between the running time of PLS and the
difficulty of a problem instance.Comment: appears in Parallel Problem Solving from Nature - PPSN XIII,
Ljubljana : Slovenia (2014
Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives
The properties of local optimal solutions in multi-objective combinatorial
optimization problems are crucial for the effectiveness of local search
algorithms, particularly when these algorithms are based on Pareto dominance.
Such local search algorithms typically return a set of mutually nondominated
Pareto local optimal (PLO) solutions, that is, a PLO-set. This paper
investigates two aspects of PLO-sets by means of experiments with Pareto local
search (PLS). First, we examine the impact of several problem characteristics
on the properties of PLO-sets for multi-objective NK-landscapes with correlated
objectives. In particular, we report that either increasing the number of
objectives or decreasing the correlation between objectives leads to an
exponential increment on the size of PLO-sets, whereas the variable correlation
has only a minor effect. Second, we study the running time and the quality
reached when using bounding archiving methods to limit the size of the archive
handled by PLS, and thus, the maximum size of the PLO-set found. We argue that
there is a clear relationship between the running time of PLS and the
difficulty of a problem instance.Comment: appears in Parallel Problem Solving from Nature - PPSN XIII,
Ljubljana : Slovenia (2014
Experiments on local search for bi-objective unconstrained binary quadratic programming
International audienceThis article reports an experimental analysis on stochastic local search for approximating the Pareto set of bi-objective unconstrained binary quadratic programming problems. First, we investigate two scalarizing strategies that iteratively identify a high-quality solution for a sequence of sub-problems. Each sub-problem is based on a static or adaptive definition of weighted-sum aggregation coefficients, and is addressed by means of a state-of-the-art single-objective tabu search procedure. Next, we design a Pareto local search that iteratively improves a set of solutions based on a neighborhood structure and on the Pareto dominance relation. At last, we hybridize both classes of algorithms by combining a scalarizing and a Pareto local search in a sequential way. A comprehensive experimental analysis reveals the high performance of the proposed approaches, which substantially improve upon previous best-known solutions. Moreover, the obtained results show the superiority of the hybrid algorithm over non-hybrid ones in terms of solution quality, while requiring a competitive computational cost. In addition, a number of structural properties of the problem instances allow us to explain the main difficulties that the different classes of local search algorithms have to face
Pareto Local Optima of Multiobjective NK-Landscapes with Correlated Objectives
International audienceIn this paper, we conduct a fitness landscape analysis for multiobjective combinatorial optimization, based on the local optima of multiobjective NK-landscapes with objective correlation. In single-objective optimization, it has become clear that local optima have a strong impact on the performance of metaheuristics. Here, we propose an extension to the multiobjective case, based on the Pareto dominance. We study the co-influence of the problem dimension, the degree of non-linearity, the number of objectives and the correlation degree between objective functions on the number of Pareto local optima
On the Effect of Connectedness for Biobjective Multiple and Long Path Problems
Recently, the property of connectedness has been claimed to give a strong
motivation on the design of local search techniques for multiobjective
combinatorial optimization (MOCO). Indeed, when connectedness holds, a basic
Pareto local search, initialized with at least one non-dominated solution,
allows to identify the efficient set exhaustively. However, this becomes
quickly infeasible in practice as the number of efficient solutions typically
grows exponentially with the instance size. As a consequence, we generally have
to deal with a limited-size approximation, where a good sample set has to be
found. In this paper, we propose the biobjective multiple and long path
problems to show experimentally that, on the first problems, even if the
efficient set is connected, a local search may be outperformed by a simple
evolutionary algorithm in the sampling of the efficient set. At the opposite,
on the second problems, a local search algorithm may successfully approximate a
disconnected efficient set. Then, we argue that connectedness is not the single
property to study for the design of local search heuristics for MOCO. This work
opens new discussions on a proper definition of the multiobjective fitness
landscape.Comment: Learning and Intelligent OptimizatioN Conference (LION 5), Rome :
Italy (2011
GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem
International audienceMultiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances
Electron transfer process in microbial electrochemical technologies: the role of cell-surface exposed conductive proteins
Electroactive microorganisms have attracted significant interest for the development of novel biotechnological systems of low ecological footprint. These can be used for the sustainable production of energy, bioremediation of metal-contaminated environments and production of added-value products. Currently, almost 100 microorganisms from the Bacterial and Archaeal domains are considered electroactive, given their ability to efficiently interact with electrodes in microbial electrochemical technologies. Cell-surface exposed conductive proteins are key players in the electron transfer between cells and electrodes. Interestingly, it seems that among the electroactive organisms identified so far, these cell-surface proteins fall into one of four groups. In this review, the different types of cell-surface conductive proteins found in electroactive organisms will be overviewed, focusing on their structural and functional properties
A practical case of the multiobjective knapsack problem: Design, modelling, tests and analysis
In this paper, we present a practical case of the multiobjective knapsack problem which concerns the elaboration of the optimal action plan in the social and medico-social sector. We provide a description and a formal model of the problem as well as some preliminary computational results. We perform an empirical analysis of the behavior of three metaheuristic approaches: a fast and elitist multiobjective genetic algorithm (NSGA-II), a Pareto Local Search (PLS) algorithm and an Indicator-Based Multi-Objective Local Search (IBMOLS)
Characterization of the multiheme cytochromes involved in the extracellular electron transfer pathway of Thermincola ferriacetica
Bioelectrochemical systems (BES) are emerging as a suite of versatile sustainable technologies to produce electricity and added‐value compounds from renewable and carbon‐neutral sources using electroactive organisms. The incomplete knowledge on the molecular processes that allow electroactive organisms to exchange electrons with electrodes has prevented their real‐world implementation. In this manuscript we investigate the extracellular electron transfer processes performed by the thermophilic Gram‐positive bacteria belonging to the Thermincola genus, which were found to produce higher levels of current and tolerate higher temperatures in BES than mesophilic Gram‐negative bacteria. In our study, three multiheme c‐type cytochromes, Tfer_0070, Tfer_0075, and Tfer_1887, proposed to be involved in the extracellular electron transfer pathway of T. ferri-acetica, were cloned and over‐expressed in E. coli. Tfer_0070 (ImdcA) and Tfer_1887 (PdcA) were purified and biochemically characterized. The electrochemical characterization of these proteins supports a pathway of extracellular electron transfer via these two proteins. By contrast, Tfer_0075 (CwcA) could not be stabilized in solution, in agreement with its proposed insertion in the pepti-doglycan wall. However, based on the homology with the outer‐membrane cytochrome OmcS, a structural model for CwcA was developed, providing a molecular perspective into the mechanisms of electron transfer across the peptidoglycan layer in Thermincola.publishersversionpublishe
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