The 2D Bin Packing Problem (2DBPP) is an NP-hard combinatorial optimization problem, where common heuristic algorithms often exhibit characteristics of greedy strategy scoring during the selection of items and the det...
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Real Coded Genetic algorithms (RCGAs) are pop-ular, versatile, non-traditional optimization techniques and can be applicable to a numerous variety of optimization problems. The performance of RCGAs depends on the choi...
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In this contribution we consider Max-LL-DUP, an optimization problem that asks for a letter-duplicated subsequence of an input string that contains the maximum number of letters of the alphabet over which the input st...
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A critical optimization job in power system operation is the Optimal Power Dispatch (OPD) problem, which aims to minimize the total generation cost while meeting power demand and system constraints. The complicated, n...
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Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogene...
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Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogeneous visualization model that clearly conveys both an overview of the network and the internal structure of its communities at the same time. As a consequence, the use of hybrid visualizations has been proposed. For instance, NodeTrix combines node-link and matrix-based representations (Henry et al., 2007). In this article we describe ChordLink, a hybrid visualization model that embeds chord diagrams, used to represent dense subgraphs, into a node-link diagram, which shows the global network structure. The visualization makes it possible to interactively highlight the structure of a community while keeping the rest of the layout stable. We discuss the intriguing algorithmic challenges behind the ChordLink model, present a prototype system that implements it, and illustrate case studies on real-world networks.
Swarm-based optimization algorithms (SBOAs) have demonstrated effectiveness in solving complex problems within a reasonable time. Among these algorithms, the intelligent water drops algorithm (IWD) has recently gained...
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In order to solve the problem that the particle swarm algorithm does not have high search ability in the late iteration and the particles tend to fall into the local optimum when it is introduced into a nonlinear fina...
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The basic slime mold algorithm tends to become trapped in local optima during the optimization process, and the convergence rate is slow, so an improved slime mold algorithm is used. Firstly, a low difference sequence...
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The growing adoption of Electric Vehicles (EVs) poses challenges to distribution networks, such as voltage instability, increased losses, and overload conditions. This study proposes an optimization-based network reco...
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Algorithm selection, i.e., selecting the most suitable algorithm for a specific problem, is a vital task in continuous black-box optimization. A popular strategy used to address this task is to characterize optimizati...
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