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Table of Content

    15 June 2021, Volume 25 Issue 2
    Combined response surface method with adaptive sampling for expensive black-box global optimization
    Fusheng BAI, Dan FENG, Ke ZHANG
    2021, 25(2):  1-14.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.001
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    A combined response surface method is presented for expensive black-box global optimization, which can adaptively take sampling points during iterations. Under the framework of response surface method, the convex combination of the cubic radial basis function and the thin plate spline radial basis function is adopted as the response surface. In the initial phase of the algorithm, the global optimizer of the auxiliary function formed by the product of the response surface model and the power of the distance indicator function will be taken as the new sample point. In the following iterations, if the distance between the two response surface models of the two consecutive iterations is smaller than a given threshold, then the global optimizer of the current response surface model will be taken as the next sample point, otherwise the sampling strategy of the initial phase will be adopted. The effectiveness of the proposed algorithm is demonstrated by the results of the numerical experiments carried respectively on 7 standard test problems and 22 standard test problems.

    An improved immune algorithm for solving hierarchical and progressive location problem of emergency medical facilities
    Yuyang ZHOU, Huizhen ZHANG, Liang MA
    2021, 25(2):  15-34.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.002
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    According to the characteristics of emergency medical facilities, a hierarchical and progressive location method is proposed to reasonably locating them. Firstly, the entropy weight method is used to calculate the weight of factors related to the location problem, and the preliminary location is also carried out. Secondly, a two-level integer programming model is formulated, which considers the service capacity of the facility, and the actual situation of treating and transferring the mild and severe patients under major public health events. Thirdly, according to the characteristics of the proposed model, an improved immune optimization algorithm is designed to effectively solve it. Finally, the location of emergency medical facilities for public health events in Xiaogan City, Hubei Province is studied as a case, and the reasonable location scheme is obtained for it, which verifies the feasibility of the proposed model and algorithm.

    Non-zero-sum investment and reinsurance game with delay effect and mean-variance utility
    Huainian ZHU, Hui ZHONG, Ning BIN
    2021, 25(2):  35-54.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.003
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    This paper investigates a non-zero-sum stochastic differential investment and reinsurance game with delay effect between two competitive insurers, who aim to maximize the mean-variance utility of his terminal wealth relative to that of his competitor. By applying stochastic control theory, corresponding extended Hamilton-Jacobi-Bellman (HJB) system of equations are established. Furthermore, closed-form expressions for the Nash equilibrium investment and reinsurance strategies and the corresponding value functions are derived both in the classical risk model and its diffusion approximation. Finally, some numerical examples are conducted to illustrate the influence of model parameters on the equilibrium investment and reinsurance strategies and draw some economic interpretations from these results.

    Face recognition algorithm based on orthogonal and sparse constrained nonnegative tensor factorization
    Shan SONG, Yan FENG, Changqing XU
    2021, 25(2):  55-66.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.004
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    As a feature extraction method, nonnegative tensor factorization has been widely used in image processing and pattern recognition for its advantages of preserving the internal structural features of data and strong interpretability. However, there are two problems in this method: one is that there is unnecessary correlation between the decomposed base images, which leads to more redundant information and takes up a lot of memory; the other is that the coding is not sparse enough, which leads to the expression of the image is not concise enough. These problems will greatly affect the accuracy of face recognition. In order to improve the accuracy of face recognition, a face recognition algorithm based on orthogonal and sparse constrained nonnegative tensor factorization is proposed. Firstly, orthogonal and sparse constraints are added to the traditional nonnegative tensor factorization to reduce the correlation between the base images and obtain sparse coding. Secondly, the original face image and the decomposed base image are used to calculate the low dimensional feature representation of the face. Finally, cosine similarity is used to measure the similarity between low-dimensional features and judge whether two face images represent the same person. Through experiments in AR database and ORL database, it is found that the improved algorithm can achieve better recognition effect.

    Research on price difference compensation mechanism of supply chain based on optimal concession equilibrium coordination strategy
    Min JIANG, Zhiqing MENG, Rui SHEN
    2021, 25(2):  67-80.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.005
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    In the supply chain, suppliers provide retailers with a compensation mechanism after the price of products is reduced, so as to encourage retailers to order more products. Therefore, we establish a price difference compensation mechanism model between manufacturer and retailer about a two stage sales. Firstly, we analyze results of the Nash equilibrium strategy and Stackelberg equilibrium strategy under the manufacturer to the retailer's price difference compensation mechanism of decision-making behavior. And then we obtain quantitative relationship of the price difference compensation mechanism under the optimal compromise equilibrium strategies. An algorithm of the approximate optimal compromise equilibrium strategy is proposed at a given price difference compensation coefficient. The case study of intelligent products shows that the mechanism of price difference compensation can improve the expected revenue of supply chain and increase the order quantity of retailers. It shows that the mechanism of price difference compensation can effectively improve relationships between suppliers and retailers.

    A scaled incremental gradient method
    Xiaohui QIAN, Xiangmei WANG
    2021, 25(2):  81-92.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.006
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    A scaled incremental gradient algorithm for minimizing a sum of continuously differentiable functions is presented. At each iteration of the algorithm, the iterate is updated incrementally by a sequence of some steps, and each step is cyclically evaluates a normalized gradient of a single component function (or several component functions). Under some moderate assumptions, the convergence result of the algorithm employing the divergence step sizes is established. As applications, the new algorithm and the (unscaled) one proposed by Bertsekas D P, Tsitsikils J N are applied to solve the robust estimation problem and the source localization problem, respectively. Some numerical experiments show that the new algorithm is more effective and robust than the corresponding (unscaled) one.

    Successive relaxed projection algorithm for multiple-sets split equality problem
    Xueling ZHOU, Meixia LI, Haitao CHE
    2021, 25(2):  93-103.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.007
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    The multiple-sets split equality problem is an extended split feasibility problem, which has a wide application in image reconstruction, language processing, and seismic exploration. In order to solve this problem, we propose a successive relaxed projection algorithm with a variable stepsize which can fully use the information of the current iteration point and does not need the calculation of the operator norm. Furthermore the weak convergence of the algorithm is proved. The numerical examples show the superiority of the algorithm in the number of iterations and the running time.

    Approximation scheme for rescheduling on a single machine with job delay and rejection
    Shanshan YU, Miaomiao JIN, Wenchang LUO
    2021, 25(2):  104-114.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.008
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    In this paper, we investigate a rescheduling problem with rejection on a single machine due to the disruption of job delay. In this problem, we are given a set of jobs that are available at time zero in the planning horizon to be processed on a single machine. Each job has its processing time and weight. Before the formal processing begins, an original schedule according to the shortest weighted processing time first order is given with the goal to minimize the total weighted completion time. Based on the original schedule, the promised due date for each job is also given. However, when the formal processing starts, some jobs are delayed, which creates a disruption to the original schedule. Thus, it is necessary to adjust the original schedule, i.e., rescheduling. To achieve a reasonable service level, we are allowed to reject some delayed jobs by paying the corresponding rejection costs. In the adjusted schedule, the overall objective function is to minimize the sum of the total weighted completion time of the accepted jobs, the total rejection cost of the rejected jobs, and the weighted penalty for the maximum tardiness of the accepted jobs, while keeping the maximum tardiness no more than the given upper bound. For this problem, we design a dynamic programming exact algorithm running in pseudo-polynomial time. Furthermore, we derive a fully polynomial time approximation scheme by using the sparse technique.

    On (1, 0)-relaxed strong edge-coloring of graphs
    Yao LIU
    2021, 25(2):  115-126.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.009
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    Let G be a graph. For two nonnegative integers s and t, an (s, t)-relaxed strong k-edge-coloring is a mapping c : E(G) → [k], such that for any edge e, there are at most s edges adjacent to e and t edges which are distance two apart from e having the color c(e). The (s, t)-relaxed strong chromatic index, denoted by χ' (s, t)(G), is the minimum number k such that G admits an (s, t)-relaxed strong k-edge-coloring. We prove that if G is a graph with mad(G) < 3 and Δ ≤ 4, then χ'(1, 0)(G) ≤ 3Δ. In addition, we prove that if G is a planar graph with Δ ≥ 4 and girth at least 7, then χ'(1, 0)(G) ≤ 3Δ - 1.

    k-tuple domination in generalized de Bruijn digraphs
    Yanxia DONG, Tao XUE, Guang ZHANG
    2021, 25(2):  127-134.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.010
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    Let $G=(V, A)$ be a digraph with vertex set $V$ and arc set $A$. A set $D_{k}$ of vertices of $G$ is a $k$-tuple dominating set of $G$ if for every vertex $v\in V(G)\setminus D_{k}$, there exists $u_{i}\in D_{k}$ (possibly some vertex $u_{i}=v$) such that arcs $(u_{i},v)\in A(G)$ for $1\leq i\leq k$. The $k$-tuple domination number $\gamma_{\times k}(G)$ of $G$ is the cardinality of a minimum $k$-tuple dominating set of $G$. In this paper we present a new upper bound on the $k$-tuple domination number of generalized de Bruijn digraphs $G_B(n,d)$. Furthermore, the method of constructing a $k$-tuple dominating set of generalized de Bruijn digraph is given. %which improves the known upper bound in previous literature. For special generalized de Bruijn digraphs, we further improve the bounds on $k$-tuple domination number by directly constructing $k$-tuple dominating sets.

    The equivalent representation of co-radiant sets and its application in multi-objective optimization problems
    Wenyi WANG, Ying GAO, Fuping LIU
    2021, 25(2):  135-143.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.011
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    As a special abstract convex (concave) sets, radiant sets and co-radiant sets play the important roles in abstract convex analysis and the theory of multiobjective optimization problems. We first establish the equivalent characterizations for the radiant sets and co-radiant sets. Finally, we apply important properties to the characterization of the approximate solutions of the vector optimization problems, and obtain the equivalent characterization of the approximate solution sets.

    A remark on the convergence of the two-subgradient extragradient algorithm for the variational inequality problem
    Biao QU, Wei XU, Xinyan WANG
    2021, 25(2):  144-148.  doi:10.15960/j.cnki.issn.1007-6093.2021.02.012
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    The two-subgradient extragradient algorithm was proposed by Yair Censor, Aviv Gibali and Simeon Reich for solving the variational inequality problem. A question about the convergence of this algorithm, that is, whether the sequences generated by the algorithm converge to a solution of the variational inequality problem, was raised as an open problem in the paper "Extensions of Korpelevich's extragradient method for the variational inequality problem in Euclidean space" (Optimization, 61(9): 1119-1132, 2012). Our goal in this short remark is to give an answer to this question and give an integrated proof of the full convergence of the algorithm.