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The social cognitive optimization algorithm is one of the newest intelligent algorithms, and this algorithm can help the solvers to avoid tripping in local optimization when solving the nonlinear constraint problems effectively. The algorithm is based on the social cognitive theory and the key point of the ergodicity is the process of refreshing the knowledge points. Modified and optimized the conditions...
This paper studies the loading problems of Multi-category Goods under the limited loading capacity. According to the characteristics of model, hybrid heuristic algorithm is used to get the optimization solution. Firstly, adopt binary code so as to make the problem more succinctly. On the basis of cubage-weight balance algorithm, construct initial solution to improve the feasibility. Through adopting...
We give the first black-box reduction from arbitrary approximation algorithms to truthful approximation mechanisms for a non-trivial class of multi-parameter problems. Specifically, we prove that every packing problem that admits an FPTAS also admits a truthful-in-expectation randomized mechanism that is an FPTAS. Our reduction makes novel use of smoothed analysis, by employing small perturbations...
We give sub linear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclosing balls. Our algorithms can be extended to some kernelized versions of these problems, such as SVDD, hard margin SVM, and L2-SVM, for which sub linear-time algorithms were not known before. These new algorithms use a combination...
The notion of vertex sparsification (in particular cut-sparsification) is introduced in, where it was shown that for any graph G = (V, E) and any subset of k terminals K ⊂ V, there is a polynomial time algorithm to construct a graph H = (K, EH) on just the terminal set so that simultaneously for all cuts (A,K-A), the value of the minimum cut in G separating A from K-A is approximately the same as...
Scientific task allocation and knowledge workers scheduling is an important part of rational human resources management in enterprises. In this paper, ant colony algorithm is used to research task allocation and knowledge workers scheduling. Ant colony optimization algorithm can reduce the number of optimization iteration and computing time. Elite solution retention tactics is used in iterating process...
Theoretical analysis of mataheuristic algorithms is believed to be very important for understanding their internal search mechanism and thus to develop more efficient algorithms. In this article we present a simple mathematical analysis of the explorative search behavior of a recently developed metaheuristic algorithm called invasive weed optimization (IWO). IWO is a novel ecologically inspired algorithm...
The design of resource efficient integrated circuits (IC) requires solving a minimization problem of more than one objective given as measures of available resources. This multiobjective optimization problem (MOP) can be solved on the smallest unit, the standard cells, to improve the performance of the entire IC. The traditional way of sizing the transistors of a standard logic cell does not focus...
Designing appropriate graphs is a problem frequently occurring in several common applications ranging from designing communication and transportation networks to discovering new drugs. More often than not the graphs to be designed need to satisfy multiple, sometimes conflicting, objectives e.g. total length, cost, complexity or other shape and property limitations. In this paper we present our approach...
We consider a problem of significant practical importance, namely, the reconstruction of a low-rank data matrix from a small subset of its entries. This problem appears in many areas such as collaborative filtering, computer vision and wireless sensor networks. In this paper, we focus on the matrix completion problem in the case when the observed samples are corrupted by noise. We compare the performance...
Resource reserved network can provide guaranteed quality of service to end users, especially those services requiring high bandwidth and short delay, such as video conferencing, video on demand, etc. In this paper, we consider the multicast packing problem, where multiple multicast sessions request network services simultaneously. To maximize the profit, network service provider need to carefully...
This paper presents a fast global optimal method for the optimization design of electromagnetic device, which based on the approximation models and the global optimization algorithms. Two approximate models, radial basis functions model and compactly supported radial basis functions model, are fully discussed in this paper. In order to illustrate the efficiency and robustness of the proposed method,...
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