Loading...

Table of Content

    30 March 2023, Volume 11 Issue 1
    A Polynomial-Time Algorithm with Tight Error Bounds for Single-Period Unit Commitment Problem
    Ruo-Tian Gao, Shu-Cherng Fang, Cheng Lu, Wen-Xun Xing
    2023, 11(1):  1-28.  doi:10.1007/s40305-021-00376-3
    Asbtract ( 1521 )   PDF  
    References | Related Articles | Metrics
    This paper proposes a Lagrangian dual-based polynomial-time approximation algorithm for solving the single-period unit commitment problem, which can be formulated as a mixed-integer quadratic programming problem and proven to be NP-hard. Tight theoretical bounds for the absolute errors and relative errors of the approximate solutions generated by the proposed algorithm are provided. Computational results support the effectiveness and efficiency of the proposed algorithm for solving large-scale problems.
    Strategic Admission Behavior and Its Implications: Evidence from a Cardiac Surgery Department
    Yan-Ying Zhao, Pei-Wen Yu, Jian-Qiang Hu
    2023, 11(1):  29-50.  doi:10.1007/s40305-021-00377-2
    Asbtract ( 1529 )   PDF  
    References | Related Articles | Metrics
    This paper examines a decentralized admission control system with partial capacity sharing in a hospital setting. The admission decision is made by each physician who is assigned a number of dedicated inpatient beds. A physician can "borrow" beds from other physicians if his dedicated beds are all occupied. We seek to understand the impact of the "borrowing cost" on physicians' admission behavior.We find that(i) If the borrowing cost is low, a physician tends to admit lower-risk patients when either his or others' capacity utilization is higher; (ii) If the borrowing cost is moderate, a physician tends to admit higher (lower)-risk patients when his (others') capacity utilization is higher; and (iii) If the borrowing cost is high, a physician tends to admit higher-risk patients when either his or others' capacity utilization is higher. We then empirically test and validate these findings. Our work demonstrates that when designing strategic admission control systems, it is important to quantify and perhaps then influence the magnitude of the borrowing cost to induce a proper level of competition without sacrificing the benefit of resource pooling.
    Reliability Enhanced Multi-objective Economic Dispatch Strategy for Hybrid Renewable Energy System with Storage
    Anongpun Man-Im, Weerakorn Ongsakul, Nimal Madhu
    2023, 11(1):  51-82.  doi:10.1007/s40305-020-00308-7
    Asbtract ( 1496 )   PDF  
    References | Related Articles | Metrics
    An optimal dispatch strategy for the economic operation of hybrid renewable energy system with storage is presented in this paper. Solar photovoltaic (PV), Wind and Battery Storage are the prime components of interest constituting the hybrid system. In addition to the economic aspect of the systems, the formulation focuses on renewable prioritized operation, system reliability and environmental sustainability enhancement. Being a multi-objective (MO) problem, a modified non-dominated sorting particle swarm optimization is used for solving the problem, considering operational cost, pollutant emission, and expected energy not served as operational objectives. The non-dominated sorting particle swarm optimization (NSPSO) is augmented with crowding distance technique, stochastic weight trade-off and chaotic mutation approaches, to control the exploration of global and particle bests, alleviating premature convergence, and enhancing solution search capability. A two-stage approach is used to derive the best solution. A modified IEEE 30-bus test system is used to demonstrate the results. By using the proposed approach, a lower and wider Pareto front is obtained, in comparison with prominent optimization approaches.
    Optimal Consumption, Leisure and Job Choice under Inflationary Environment
    Yu-Song Zhang, Chen Fei, Hai-Feng Pan, Jian Huang
    2023, 11(1):  83-108.  doi:10.1007/s40305-021-00369-2
    Asbtract ( 1494 )   PDF  
    References | Related Articles | Metrics
    The optimal job choice, consumption and portfolio decision-making of economic agents under inflationary environment for a continuous infinite time are studied. The agent's preference is characterized by the Cobb-Douglas utility function with two variables of consumption and leisure. The economic agent invests in three kinds of assets:risk-free bonds, inflation index bonds and risky assets. The agent has two kinds of working conditions:One is the work with high income and little leisure time, and the other is the work with low income and much leisure time. Firstly, the real wealth process after inflation discount is derived by using Itô formula. Then, based on the expected utility maximization standard under any working state, martingale method is adopted to obtain the closed form solution of optimal job choice, consumption and portfolio decision-making. Finally, the effects of wealth and inflation volatility on the optimal consumption and portfolio strategies are quantitatively analyzed by numerical simulation with given parameters.
    Approximation Algorithms for Multi-vehicle Stacker Crane Problems
    Wei Yu, Rui-Yong Dai, Zhao-Hui Liu
    2023, 11(1):  109-132.  doi:10.1007/s40305-021-00372-7
    Asbtract ( 1471 )   PDF  
    References | Related Articles | Metrics
    We study a variety of multi-vehicle generalizations of the Stacker Crane Problem (SCP). The input consists of a mixed graph G=(V, E, A) with vertex set V, edge set E and arc set A, and a nonnegative integer cost function c on EA. We consider the following three problems:(1) k-depot SCP (k-DSCP). There is a depot set DV containing k distinct depots. The goal is to determine a collection of k closed walks including all the arcs of A such that the total cost of the closed walks is minimized, where each closed walk corresponds to the route of one vehicle and has to start from a distinct depot and return to it. (2) k-SCP. There are no given depots, and each vehicle may start from any vertex and then go back to it. The objective is to find a collection of k closed walks including all the arcs of A such that the total cost of the closed walks is minimized. (3) k-depot Stacker Crane Path Problem (k-DSCPP). There is a depot set DV containing k distinct depots. The aim is to find k (open) walks including all the arcs of A such that the total cost of the walks is minimized, where each (open) walk has to start from a distinct depot but may end at any vertex. We present the first constantfactor approximation algorithms for all the above three problems. To be specific, we give 3-approximation algorithms for the k-DSCP, the k-SCP and the k-DSCPP. If the costs of the arcs are symmetric, i.e., for every arc there is a parallel edge of no greater cost, we develop better algorithms with approximation ratios max{ 9/5, 2-1/2k +1}, 2, 2, respectively. All the proposed algorithms have a time complexity of O(|V|3) except that the two 2-approximation algorithms run in O(|V|2 log|V|) time.
    Performance Analysis of a Markovian Queue with Impatient Customers and Working Vacation
    Shakir Majid
    2023, 11(1):  133-156.  doi:10.1007/s40305-021-00361-w
    Asbtract ( 1459 )   PDF  
    References | Related Articles | Metrics
    In this paper, we consider the impatient customers in M/M/1 queueing model under variant working vacation policy. The customer's impatience is due to its arrival during a working vacation period, where the service rate of the customer is lower than a normal busy period. If the system is non-empty when the server returns from the working vacation, the server resumes the normal service period. Otherwise, the server will take successive working vacations till it reaches the maximum number of K working vacations and then the server remains idle until the next arrival. Closed-form probabilities are obtained by using the identities involving beta functions and degenerate hypergeometric functions, and the performance measures of the system are derived using generating functions. The stochastic decomposition structures of the mean queue length and mean waiting time are verified. The effects of the system parameters on some performance measures had been numerically illustrated.
    A K-Means Clustering-Based Multiple Importance Sampling Algorithm for Integral Global Optimization
    Chen Wang, Dong-Hua Wu
    2023, 11(1):  157-176.  doi:10.1007/s40305-021-00353-w
    Asbtract ( 1476 )   PDF  
    References | Related Articles | Metrics
    In this paper, we propose a K-means clustering-based integral level-value estimation algorithm tosolveakindof box-constrainedglobal optimizationproblem. For this purpose, we introduce the generalized variance function associated with the level-value of the objective function to be minimized. The variance function has a good property when Newton's method is used to solve a variance equation resulting by setting the variance function to zero. We prove that the largest root of the variance equation is equal to the global minimum value of the corresponding optimization problem. Based on the K-means clustering algorithm, the multiple importance sampling technique is proposed in the implementable algorithm. The main idea of the cross-entropy method is used to update the parameters of sampling density function. The asymptotic convergence of the algorithm is proved, and the validity of the algorithm is verified by numerical experiments.
    Prediction of Listed Company Innovation Ability Based on Attention Mechanism
    Huan-Yu Ma, Yan Xu, Yu-Long Liu
    2023, 11(1):  177-188.  doi:10.1007/s40305-022-00431-7
    Asbtract ( 1476 )   PDF  
    References | Related Articles | Metrics
    Innovation is the center of the enterprise development, which is the main driving force of enterprises' competitiveness. To evaluate the enterprises' innovation ability, we firstly establish an index system which aims at analyzing the enterprise innovation ability. We also retrieve the data of the listed companies in Wind database from 2015 to 2019 and label them using factor analysis method. Then, a new deep learning classificational framework with attention mechanism and LSTM is established. The results show that when attention mechanism and LSTM are added into the convolutional neural network(CNN), the model's prediction performance is better improved, and the accuracy, recall, precision and F-score are 0.914, 0.914, 0.916 and 0.915, respectively. This indicates the strong generalization ability of our new model. Finally, we also find that patents and R&D expenditures are the most important factor affecting the corporate innovation ability through SHapley Additive exPlanations(SHAP). Companies with more patents and R&D expenditures are generally considered to be more innovative.
    Lower Bounds of Distance Laplacian Spectral Radii of n-Vertex Graphs in Terms of Fractional Matching Number
    Jin Yan, Yan Liu, Xue-Li Su
    2023, 11(1):  189-196.  doi:10.1007/s40305-021-00358-5
    Asbtract ( 1552 )   PDF  
    References | Related Articles | Metrics
    A fractional matching of a graph G is a function f:E(G) →[0, 1] such that for each vertex v, Σe∈ΓG(v) f (e) ≤ 1. The fractional matching number of G is the maximum value of ΣeE(G) f (e) over all fractional matchings f. Tian et al. (Linear Algebra Appl 506:579-587, 2016) determined the extremal graphs with minimum distance Laplacian spectral radius among n-vertex graphs with given matching number. However, a natural problem is left open:among all n-vertex graphs with given fractional matching number, how about the lower bound of their distance Laplacian spectral radii and which graphs minimize the distance Laplacian spectral radii? In this paper, we solve these problems completely.
    Toughness for Fractional (2, b, k)-Critical Covered Graphs
    Su-Fang Wang, Wei Zhang
    2023, 11(1):  197-206.  doi:10.1007/s40305-021-00359-4
    Asbtract ( 1636 )   PDF  
    References | Related Articles | Metrics
    Let h:E(G) →[0, 1] be a function. If a Σ ex h(e) ≤ b holds for each xV(G), then we call G[Fh] a fractional[a, b]-factor of G with indicator function h, where Fh={e:eE(G), h(e) > 0}. A graph G is called a fractional[a, b]-covered graph if for every edge e of G, there is a fractional[a, b]-factor G[Fh] with h(e)=1. Zhou, Xu and Sun[S. Zhou, Y. Xu, Z. Sun, Degree conditions for fractional (a, b, k)- critical covered graphs, Information Processing Letters 152(2019)105838] defined the concept of a fractional (a, b, k)-critical covered graph, i.e., for every vertex subset Q with|Q|=k of G, G-Q is a fractional[a, b]-covered graph. In this article, we study the problem of a fractional (2, b, k)-critical covered graph, and verify that a graph G with δ(G) ≥ 3 + k is a fractional (2, b, k)-critical covered graph if its toughness t(G) ≥ 1 + 1/b + k/2b, where b and k are two nonnegative integers with b ≥ 2 + k/2.
    An Approximation Algorithm for P-prize-collecting Set Cover Problem
    Jin-Shuang Guo, Wen Liu, Bo Hou
    2023, 11(1):  207-218.  doi:10.1007/s40305-021-00364-7
    Asbtract ( 1617 )   PDF  
    References | Related Articles | Metrics
    In this paper, we consider the P-prize-collecting set cover (P-PCSC) problem, which is a generalization of the set cover problem. In this problem, we are given a set system (U, S), where U is a ground set and S ⊆ 2U is a collection of subsets satisfying ∪SS S=U. Every subset in S has a nonnegative cost, and every element in U has a nonnegative penalty cost and a nonnegative profit. Our goal is to find a subcollection CS such that the total cost, consisting of the cost of subsets in C and the penalty cost of the elements not covered by C, is minimized and at the same time the combined profit of the elements covered by C is at least P, a specified profit bound. Our main work is to obtain a 2 f + ε-approximation algorithm for the P-PCSC problem by using the primal-dual and Lagrangian relaxation methods, where f is the maximum frequency of an element in the given set system (U, S) and ε is a fixed positive number.
    Marriage Market with Indifferences: A Linear Programming Approach
    Noelia Juarez, Pablo A. Neme, Jorge Oviedo
    2023, 11(1):  219-242.  doi:10.1007/s40305-021-00360-x
    Asbtract ( 1622 )   PDF  
    References | Related Articles | Metrics
    We study stable and strongly stable matchings in the marriage market with indifference in their preferences. We characterize the stable matchings as integer extreme points of a convex polytope. We give an alternative proof for the integrity of the strongly stable matching polytope. Also, we compute men-optimal (women-optimal) stable and strongly stable matchings using linear programming. When preferences are strict, we find the men-optimal (women-optimal) stable matching.