To address the issue that static densest subgraph mining algorithms often exhibit low efficiency when handling large scale dynamic graphs,this paper proposes a heuristic approximation algorithm.The algorithm approxima...To address the issue that static densest subgraph mining algorithms often exhibit low efficiency when handling large scale dynamic graphs,this paper proposes a heuristic approximation algorithm.The algorithm approximates the densest k-subgraphs of the entire graph through four steps:partitioning the large-scale dynamic graph,constructing a partial set of the densest k-subgraphs,heuristically merging the subgraph sets,and finally extracting the densest k-subgraphs.This approach significantly reduces the computational time for large-scale dynamic graphs while simultaneously improving the quality of the resulting subgraphs.This algorithm is applicable to various definitions of“density”and can accommodate diverse requirements on the number of edges.When integrated with existing static densest subgraph detection algorithms,it achieves scalability and computational efficiency.Theoretical analysis demonstrates that the optimal density of the densest k-subgraphs extracted by the proposed algorithm reaches 0.9.To evaluate the performance of the algorithm,experiments were conducted on four billion-scale datasets:Friendster,Orkut,YouTube,and DBLP.The results indicate that the proposed algorithm outperforms static methods in both runtime efficiency and subgraph quality on large-scale dynamic graphs.展开更多
develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining...develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.展开更多
In this paper, we propose a model for the epidemic control problem, the goal of which is to minimize the total cost of quarantining, vaccination and cure under the constraint on the maximum number of infected people a...In this paper, we propose a model for the epidemic control problem, the goal of which is to minimize the total cost of quarantining, vaccination and cure under the constraint on the maximum number of infected people allowed. A (1+ε+ε3 , 1+ ε+1/ε )- bicriteria approximation algorithm is given.展开更多
In this paper,attention is paid to study an algorithm for the common due datetotal weighted tardiness problem of single machine scheduling. Anapproximation alsorithm is given. It performs well in the sense of worst-ca...In this paper,attention is paid to study an algorithm for the common due datetotal weighted tardiness problem of single machine scheduling. Anapproximation alsorithm is given. It performs well in the sense of worst-casebehaviour and its worst-case performance ratio is 2.展开更多
The connected dominating set(CDS)problem,which consists of finding a smallest connected dominating set for graphs is an NP-hard problem in the unit disk graphs(UDGs).This paper focuses on the CDS problem in wireless n...The connected dominating set(CDS)problem,which consists of finding a smallest connected dominating set for graphs is an NP-hard problem in the unit disk graphs(UDGs).This paper focuses on the CDS problem in wireless networks.Investigation of some properties of independent set(IS)in UDGs shows that geometric features of nodes distribution like angle and area can be used to design efficient heuristics for the approximation algorithms.Several constant factor approximation algorithms are presented for the CDS problem in UDGs.Simulation results show that the proposed algorithms perform better than some known ones.展开更多
In the k-product uncapacitated facility location problem with penalties,we are given a set of demand points where clients are located and a set of potential sites where facilities with unlimited capacities can be open...In the k-product uncapacitated facility location problem with penalties,we are given a set of demand points where clients are located and a set of potential sites where facilities with unlimited capacities can be opened.There are k different kinds of products to be supplied by a set of open facilities.Each open facility can supply only a distinct product with a non-negative fixed cost determined by the product it wants to supply.Each client is either supplied with k kinds of products by a set of k different open facilities or completely rejected.There is a non-negative service cost between each pair of locations and also a penalty cost for each client if its service is rejected.These service costs are assumed to be symmetric and satisfy the triangle inequality.The goal is to select a set of clients to reject their service and then choose a set of facilities to be opened to service the remaining clients so that the total cost of opening facilities,servicing the clients,and the penalty is minimized.We address two different integer programs to describe the problem.Based on the linear programming rounding technique,we propose a(2k+1)-approximation algorithm for this problem.展开更多
In this paper,we address the k-Chinese postman problem under interdiction budget constraints(the k-CPIBC problem,for short),which is a further generalization of the k-Chinese postman problem and has many practical app...In this paper,we address the k-Chinese postman problem under interdiction budget constraints(the k-CPIBC problem,for short),which is a further generalization of the k-Chinese postman problem and has many practical applications in real life.Specifically,given a weighted graph G=(V,E;w,c;v_(1))equipped with a weight function w:E→R^(+)that satisfies the triangle inequality,an interdiction cost function c:E→Z^(+),a fixed depot v_(1)∈V,an integer k∈^Z^(+)and a budget B∈N,we are asked to find a subset S_(K)■E such that c(S_(K))=∑_(e∈S_(k)c_(e))≤B and that the subgraph G\S_(k)is connected,the objective is to minimize the value min_(C_(E)\S_(k))max{w(C_(i))|C_(i)∈C_(E)\S_(K)}among such all aforementioned subsets S_(k),where C_(E)S_(k)is a set of k-tours(of G\S_(k))starting and ending at the depot v_(1),jointly traversing each edge in G\S_(k)at least once,and w(C_(i))=∑e∈C_(i)w(e)for each tour C_(i)∈C_(E)\S_(k).We obtain the following main results:(1)Given an-approximation algorithm to solve the minimization knapsack problem,we design an(α+β)-approximation algorithm to solve the k-CPIBC problem,whereβ=7/2-1/k-[1/k].(2)We present aβ-approximation algorithm to solve the special version of the k-CPIBC problem,where c(e)1 for each edge e in G and is defined in(1).展开更多
We consider the Max Directed 3-Section problem,which is closely connected to other well-known graph partition problems,such as Max Cut and Max Bisection.Given an arc-weighted directed graph,the goal of the Max Directe...We consider the Max Directed 3-Section problem,which is closely connected to other well-known graph partition problems,such as Max Cut and Max Bisection.Given an arc-weighted directed graph,the goal of the Max Directed 3-Section problem is to partition the vertex set into three disjoint subsets with equal size,while maximizing the total weight of arcs crossing different vertex subsets.By combining the Lasserre hierarchy with the random hyperplane rounding strategy,we propose a polynomial-time algorithm with approximation ratio of 0.489.展开更多
This paper investigates a two-stage flow shop scheduling model incorporating transportation after the job is complete.The system configuration comprises dual processing machines and a single automated transporter with...This paper investigates a two-stage flow shop scheduling model incorporating transportation after the job is complete.The system configuration comprises dual processing machines and a single automated transporter with unit capacity.Each job in the production sequence is defined by distinct physical size,and the transporter can load multiple jobs in a batch at the same time.All jobs follow identical processing order across both machines before they are transported to the destination.The goal of this problem is to determine a schedule and the batch scheme for transport,such that the makespan is minimum,where the makespan represents the minimum completion time required for full job processing and delivery operations.We present a novel approximation algorithm achieving a performance ratio of(1+ε+2B∗−1/2),where is an arbitrary positive number in(0,1]and B∗is the number of batches in an optimal solution.The ratio is asymptotically optimal when B∗tends toward infinity and the parameter approaches 0.Empirical validation through numerical simulations confirms that our methodology efficiently produces solutions approaching optimality within practical computation times.展开更多
The problem of efficiently monitoring the network flow is regarded as the problem to find out the minimum weighted weak vertex cover set for a given graphG=(V,E). In this paper, we give an approximation algorithm to s...The problem of efficiently monitoring the network flow is regarded as the problem to find out the minimum weighted weak vertex cover set for a given graphG=(V,E). In this paper, we give an approximation algorithm to solve it, which has the approximation ratio lnd+1, whered is the maximum degree of the vertex in graphG, and improve the previous work. Keywords weak vertex cover - NP-hard - approximation algorithm NoteThis work is supported by the Ministry of Science and Technology of China (Grant No.2001CCA03000), the National Natural Science Foundation of China (Grant No.60273045), and the Shanghai Science and Technology Development Foundation (Grant No.025115032).展开更多
In this work,we investigate a generalization of the classical capacitated arc routing problem,called the Multi-depot Capacitated Arc Routing Problem(MCARP).We give exact and approximation algorithms for different vari...In this work,we investigate a generalization of the classical capacitated arc routing problem,called the Multi-depot Capacitated Arc Routing Problem(MCARP).We give exact and approximation algorithms for different variants of the MCARP.First,we obtain the first constant-ratio approximation algorithms for the MCARP and its nonfixed destination version.Second,for the multi-depot rural postman problem,i.e.,a special case of the MCARP where the vehicles have infinite capacity,we develop a(2-1/2k+1)-approximation algorithm(k denotes the number of depots).Third,we show the polynomial solvability of the equal-demand MCARP on a line and devise a 2-approximation algorithm for the multi-depot capacitated vehicle routing problem on a line.Lastly,we conduct extensive numerical experiments on the algorithms for the multi-depot rural postman problem to show their effectiveness.展开更多
A special case of the bottleneck Steiner tree problem in the Euclidean plane was considered in this paper. The problem has applications in the design of wireless communication networks, multifacility location, VLSI ro...A special case of the bottleneck Steiner tree problem in the Euclidean plane was considered in this paper. The problem has applications in the design of wireless communication networks, multifacility location, VLSI routing and network routing. For the special case which requires that there should be no edge connecting any two Steiner points in the optimal solution, a 3-restricted Steiner tree can be found indicating the existence of the performance ratio root2. In this paper, the special case of the problem is proved to be NP-hard and cannot be approximated within ratio root2. First a simple polynomial time approximation algorithm with performance ratio root3 is presented. Then based on this algorithm and the existence of the 3-restricted Steiner tree, a polynomial time approximation algorithm with performance ratio-root2 + epsilon is proposed, for any epsilon > 0.展开更多
Using outward rotations, we obtain an approximation algorithm for Max-Bisection problem, i.e., partitioning the vertices of an undirected graph into two blocks of equal cardinality so as to maximize the weights of cro...Using outward rotations, we obtain an approximation algorithm for Max-Bisection problem, i.e., partitioning the vertices of an undirected graph into two blocks of equal cardinality so as to maximize the weights of crossing edges. In many interesting cases, the algorithm performs better than the algorithms of Ye and of Halperin and Zwick. The main tool used to obtain this result is semidefinite programming.展开更多
In this paper,we consider the-prize-collecting minimum vertex cover problem with submodular penalties,which generalizes the well-known minimum vertex cover problem,minimum partial vertex cover problem and minimum vert...In this paper,we consider the-prize-collecting minimum vertex cover problem with submodular penalties,which generalizes the well-known minimum vertex cover problem,minimum partial vertex cover problem and minimum vertex cover problem with submodular penalties.We are given a cost graph and an integer.This problem determines a vertex set such that covers at least edges.The objective is to minimize the total cost of the vertices in plus the penalty of the uncovered edge set,where the penalty is determined by a submodular function.We design a two-phase combinatorial algorithm based on the guessing technique and the primal-dual framework to address the problem.When the submodular penalty cost function is normalized and nondecreasing,the proposed algorithm has an approximation factor of.When the submodular penalty cost function is linear,the approximation factor of the proposed algorithm is reduced to,which is the best factor if the unique game conjecture holds.展开更多
We consider the design of semidefinite programming （SDP） based approximation algorithm for the problem Max Hypergraph Cut with Limited Unbalance （MHC-LU）： Find a partition of the vertices of a weighted hypergraph...We consider the design of semidefinite programming （SDP） based approximation algorithm for the problem Max Hypergraph Cut with Limited Unbalance （MHC-LU）： Find a partition of the vertices of a weighted hypergraph H = （V, E） into two subsets V1, V2 with ｜｜V2｜ - ｜1/1 ｜｜ ≤ u for some given u and maximizing the total weight of the edges meeting both V1 and V2. The problem MHC-LU generalizes several other combinatorial optimization problems including Max Cut, Max Cut with Limited Unbalance （MC-LU）, Max Set Splitting, Max Ek-Set Splitting and Max Hypergraph Bisection. By generalizing several earlier ideas, we present an SDP randomized approximation algorithm for MHC-LU with guaranteed worst-case performance ratios for various unbalance parameters τ = u/｜V｜. We also give the worst-case performance ratio of the SDP-algorithm for approximating MHC-LU regardless of the value of τ. Our strengthened SDP relaxation and rounding method improve a result of Ageev and Sviridenko （2000） on Max Hypergraph Bisection （MHC-LU with u = 0）, and results of Andersson and Engebretsen （1999）, Gaur and Krishnamurti （2001） and Zhang et al. （2004） on Max Set Splitting （MHC-LU with u = ｜V｜）. Furthermore, our new formula for the performance ratio by a tighter analysis compared with that in Galbiati and Maffioli （2007） is responsible for the improvement of a result of Galbiati and Maffioli （2007） on MC-LU for some range of τ.展开更多
In this paper,we consider approximation algorithms for optimizing a generic multivariate polynomial function in discrete(typically binary)variables.Such models have natural applications in graph theory,neural networks...In this paper,we consider approximation algorithms for optimizing a generic multivariate polynomial function in discrete(typically binary)variables.Such models have natural applications in graph theory,neural networks,error-correcting codes,among many others.In particular,we focus on three types of optimization models:(1)maximizing a homogeneous polynomial function in binary variables;(2)maximizing a homogeneous polynomial function in binary variables,mixed with variables under spherical constraints;(3)maximizing an inhomogeneous polynomial function in binary variables.We propose polynomial-time randomized approximation algorithms for such polynomial optimizationmodels,and establish the approximation ratios(or relative approximation ratios whenever appropriate)for the proposed algorithms.Some examples of applications for these models and algorithms are discussed as well.展开更多
Stochastic optimization has established itself as a major method to handle uncertainty in various optimization problems by modeling the uncertainty by a probability distribution over possible realizations.Traditional...Stochastic optimization has established itself as a major method to handle uncertainty in various optimization problems by modeling the uncertainty by a probability distribution over possible realizations.Traditionally,the main focus in stochastic optimization has been various stochastic mathematical programming(such as linear programming,convex programming).In recent years,there has been a surge of interest in stochastic combinatorial optimization problems from the theoretical computer science community.In this article,we survey some of the recent results on various stochastic versions of classical combinatorial optimization problems.Since most problems in this domain are NP-hard(or#P-hard,or even PSPACE-hard),we focus on the results which provide polynomial time approximation algorithms with provable approximation guarantees.Our discussions are centered around a few representative problems,such as stochastic knapsack,stochastic matching,multi-armed bandit etc.We use these examples to introduce several popular stochastic models,such as the fixed-set model,2-stage stochastic optimization model,stochastic adaptive probing model etc,as well as some useful techniques for designing approximation algorithms for stochastic combinatorial optimization problems,including the linear programming relaxation approach,boosted sampling,content resolution schemes,Poisson approximation etc.We also provide some open research questions along the way.Our purpose is to provide readers a quick glimpse to the models,problems,and techniques in this area,and hopefully inspire new contributions.展开更多
This paper considers the integrated production and delivery scheduling on a serial batch machine,in which split is allowed in the delivery of the jobs.The objective is to minimize the makespan,i.e.,the maximum deliver...This paper considers the integrated production and delivery scheduling on a serial batch machine,in which split is allowed in the delivery of the jobs.The objective is to minimize the makespan,i.e.,the maximum delivery completion time of the jobs.Lu et al.(Theor Comput Sci 572:50–57,2015)showed that this problem is strongly NP-hard,and presented a 32-approximation algorithm.In this paper,we present an improved 43-approximation algorithm for this problem.We also present a polynomial-time algorithm for the special case when all jobs have the identical weight.展开更多
In this paper,we consider the parallel-machine customer order scheduling with delivery time and submodular rejection penalties.In this problem,we are given m dedicated machines in parallel and n customer orders.Each o...In this paper,we consider the parallel-machine customer order scheduling with delivery time and submodular rejection penalties.In this problem,we are given m dedicated machines in parallel and n customer orders.Each order has a delivery time and consists of m product types and each product type should be manufactured on a dedicated machine.An order is either rejected,in which case a rejection penalty has to be paid,or accepted and manufactured on the m dedicated machines.The objective is to find a solution to minimize the sum of the maximum delivery completion time of the accepted orders and the penalty of the rejected orders which is determined by a submodular function.We design an LP rounding algorithm with approximation ratio of n+1 for this problem.展开更多
Abstract We study the fleet size and mix vehicle routing problem with constraints on the capacity of each vehicle. The objective is to minimize the total cost including fixed utilization cost of vehicles and traveling...Abstract We study the fleet size and mix vehicle routing problem with constraints on the capacity of each vehicle. The objective is to minimize the total cost including fixed utilization cost of vehicles and traveling cost by vehicles. We give differential approximation algorithms for the fleet size and mix vehicle routing problem （FSMVRP） with two kinds of vehicles, the capacities of which are respectively nlk and n2k, n2 〉 nl ≥ 1, k ≥ 1. Using existing theories for vehicle routing problems and feature of the algorithms represented in the paper, we also prove that the algorithms give（1-6n＋3/（n＋1）2k＋n＋1）differential approximation ratio for （k, nk） VRP, n 〉 1and （1-6n2＋3n/n1k＋n2k）2k）differential approximation ratio for （nlk, n2k）VRP, n2 〉 nl 〉 1.展开更多
基金The National Natural Science Foundation of China(No.62172443).
文摘To address the issue that static densest subgraph mining algorithms often exhibit low efficiency when handling large scale dynamic graphs,this paper proposes a heuristic approximation algorithm.The algorithm approximates the densest k-subgraphs of the entire graph through four steps:partitioning the large-scale dynamic graph,constructing a partial set of the densest k-subgraphs,heuristically merging the subgraph sets,and finally extracting the densest k-subgraphs.This approach significantly reduces the computational time for large-scale dynamic graphs while simultaneously improving the quality of the resulting subgraphs.This algorithm is applicable to various definitions of“density”and can accommodate diverse requirements on the number of edges.When integrated with existing static densest subgraph detection algorithms,it achieves scalability and computational efficiency.Theoretical analysis demonstrates that the optimal density of the densest k-subgraphs extracted by the proposed algorithm reaches 0.9.To evaluate the performance of the algorithm,experiments were conducted on four billion-scale datasets:Friendster,Orkut,YouTube,and DBLP.The results indicate that the proposed algorithm outperforms static methods in both runtime efficiency and subgraph quality on large-scale dynamic graphs.
基金supported by the National Natural Science Foundation of China under Grant No.11371001
文摘develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.
文摘In this paper, we propose a model for the epidemic control problem, the goal of which is to minimize the total cost of quarantining, vaccination and cure under the constraint on the maximum number of infected people allowed. A (1+ε+ε3 , 1+ ε+1/ε )- bicriteria approximation algorithm is given.
文摘In this paper,attention is paid to study an algorithm for the common due datetotal weighted tardiness problem of single machine scheduling. Anapproximation alsorithm is given. It performs well in the sense of worst-casebehaviour and its worst-case performance ratio is 2.
基金supported by the National Natural Science Foundation of China under Grant No 60473090the National"11th Five-Year-Supporting-Plan"of China under Grant No 2006BAH02A0407
文摘The connected dominating set(CDS)problem,which consists of finding a smallest connected dominating set for graphs is an NP-hard problem in the unit disk graphs(UDGs).This paper focuses on the CDS problem in wireless networks.Investigation of some properties of independent set(IS)in UDGs shows that geometric features of nodes distribution like angle and area can be used to design efficient heuristics for the approximation algorithms.Several constant factor approximation algorithms are presented for the CDS problem in UDGs.Simulation results show that the proposed algorithms perform better than some known ones.
基金supported by the National Natural Science Foundation of China(No.11971252)。
文摘In the k-product uncapacitated facility location problem with penalties,we are given a set of demand points where clients are located and a set of potential sites where facilities with unlimited capacities can be opened.There are k different kinds of products to be supplied by a set of open facilities.Each open facility can supply only a distinct product with a non-negative fixed cost determined by the product it wants to supply.Each client is either supplied with k kinds of products by a set of k different open facilities or completely rejected.There is a non-negative service cost between each pair of locations and also a penalty cost for each client if its service is rejected.These service costs are assumed to be symmetric and satisfy the triangle inequality.The goal is to select a set of clients to reject their service and then choose a set of facilities to be opened to service the remaining clients so that the total cost of opening facilities,servicing the clients,and the penalty is minimized.We address two different integer programs to describe the problem.Based on the linear programming rounding technique,we propose a(2k+1)-approximation algorithm for this problem.
基金supported by the National Natural Science Foundation of China(Nos.11861075,12101593)Project for Innovation Team(Cultivation)of Yunnan Province(No.202005AE-160006)+2 种基金Peng-Xiang Pan is also supported by Project of Yunnan Provincial Department of Education Science Research Fund(No.2020Y0040)Jun-Ran Lichen is also supported by Fundamental Research Funds for the Central Universities(No.buctrc202219)Jian-Ping Li is also supported by Project of Yunling Scholars Training of Yunnan Province(No.K264202011820).
文摘In this paper,we address the k-Chinese postman problem under interdiction budget constraints(the k-CPIBC problem,for short),which is a further generalization of the k-Chinese postman problem and has many practical applications in real life.Specifically,given a weighted graph G=(V,E;w,c;v_(1))equipped with a weight function w:E→R^(+)that satisfies the triangle inequality,an interdiction cost function c:E→Z^(+),a fixed depot v_(1)∈V,an integer k∈^Z^(+)and a budget B∈N,we are asked to find a subset S_(K)■E such that c(S_(K))=∑_(e∈S_(k)c_(e))≤B and that the subgraph G\S_(k)is connected,the objective is to minimize the value min_(C_(E)\S_(k))max{w(C_(i))|C_(i)∈C_(E)\S_(K)}among such all aforementioned subsets S_(k),where C_(E)S_(k)is a set of k-tours(of G\S_(k))starting and ending at the depot v_(1),jointly traversing each edge in G\S_(k)at least once,and w(C_(i))=∑e∈C_(i)w(e)for each tour C_(i)∈C_(E)\S_(k).We obtain the following main results:(1)Given an-approximation algorithm to solve the minimization knapsack problem,we design an(α+β)-approximation algorithm to solve the k-CPIBC problem,whereβ=7/2-1/k-[1/k].(2)We present aβ-approximation algorithm to solve the special version of the k-CPIBC problem,where c(e)1 for each edge e in G and is defined in(1).
基金supported by the National Natural Science Foundation of China(Nos.12271259 and 12301414)the China Scholarship Council(No.202306200014)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Nos.KYCX24_1785).
文摘We consider the Max Directed 3-Section problem,which is closely connected to other well-known graph partition problems,such as Max Cut and Max Bisection.Given an arc-weighted directed graph,the goal of the Max Directed 3-Section problem is to partition the vertex set into three disjoint subsets with equal size,while maximizing the total weight of arcs crossing different vertex subsets.By combining the Lasserre hierarchy with the random hyperplane rounding strategy,we propose a polynomial-time algorithm with approximation ratio of 0.489.
基金supported in part by Henan Science and Technology Research(Grant Number 222102310547)Natural Science Foundation of Henan(Grant Number 242300421474)Collaborative Innovation Major Project of Zhengzhou(Grant Number 20XTZX06013).
文摘This paper investigates a two-stage flow shop scheduling model incorporating transportation after the job is complete.The system configuration comprises dual processing machines and a single automated transporter with unit capacity.Each job in the production sequence is defined by distinct physical size,and the transporter can load multiple jobs in a batch at the same time.All jobs follow identical processing order across both machines before they are transported to the destination.The goal of this problem is to determine a schedule and the batch scheme for transport,such that the makespan is minimum,where the makespan represents the minimum completion time required for full job processing and delivery operations.We present a novel approximation algorithm achieving a performance ratio of(1+ε+2B∗−1/2),where is an arbitrary positive number in(0,1]and B∗is the number of batches in an optimal solution.The ratio is asymptotically optimal when B∗tends toward infinity and the parameter approaches 0.Empirical validation through numerical simulations confirms that our methodology efficiently produces solutions approaching optimality within practical computation times.
文摘The problem of efficiently monitoring the network flow is regarded as the problem to find out the minimum weighted weak vertex cover set for a given graphG=(V,E). In this paper, we give an approximation algorithm to solve it, which has the approximation ratio lnd+1, whered is the maximum degree of the vertex in graphG, and improve the previous work. Keywords weak vertex cover - NP-hard - approximation algorithm NoteThis work is supported by the Ministry of Science and Technology of China (Grant No.2001CCA03000), the National Natural Science Foundation of China (Grant No.60273045), and the Shanghai Science and Technology Development Foundation (Grant No.025115032).
基金supported by the National Natural Science Foundation of China(Nos.11671135,11871213,11901255)the Natural Science Foundation of Shanghai(No.19ZR1411800)。
文摘In this work,we investigate a generalization of the classical capacitated arc routing problem,called the Multi-depot Capacitated Arc Routing Problem(MCARP).We give exact and approximation algorithms for different variants of the MCARP.First,we obtain the first constant-ratio approximation algorithms for the MCARP and its nonfixed destination version.Second,for the multi-depot rural postman problem,i.e.,a special case of the MCARP where the vehicles have infinite capacity,we develop a(2-1/2k+1)-approximation algorithm(k denotes the number of depots).Third,we show the polynomial solvability of the equal-demand MCARP on a line and devise a 2-approximation algorithm for the multi-depot capacitated vehicle routing problem on a line.Lastly,we conduct extensive numerical experiments on the algorithms for the multi-depot rural postman problem to show their effectiveness.
文摘A special case of the bottleneck Steiner tree problem in the Euclidean plane was considered in this paper. The problem has applications in the design of wireless communication networks, multifacility location, VLSI routing and network routing. For the special case which requires that there should be no edge connecting any two Steiner points in the optimal solution, a 3-restricted Steiner tree can be found indicating the existence of the performance ratio root2. In this paper, the special case of the problem is proved to be NP-hard and cannot be approximated within ratio root2. First a simple polynomial time approximation algorithm with performance ratio root3 is presented. Then based on this algorithm and the existence of the 3-restricted Steiner tree, a polynomial time approximation algorithm with performance ratio-root2 + epsilon is proposed, for any epsilon > 0.
基金Research partly supported by Chinese NSF grant 19731001 and National 973 Information Technology and High-Performance Software Program of China with grant No.G1998030401.The first author gratefully acknowledges the support of K.C.Wong Education Foundat
文摘Using outward rotations, we obtain an approximation algorithm for Max-Bisection problem, i.e., partitioning the vertices of an undirected graph into two blocks of equal cardinality so as to maximize the weights of crossing edges. In many interesting cases, the algorithm performs better than the algorithms of Ye and of Halperin and Zwick. The main tool used to obtain this result is semidefinite programming.
基金The work was supported in part by the National Natural Science Foundation of China(Grant No.12071417)。
文摘In this paper,we consider the-prize-collecting minimum vertex cover problem with submodular penalties,which generalizes the well-known minimum vertex cover problem,minimum partial vertex cover problem and minimum vertex cover problem with submodular penalties.We are given a cost graph and an integer.This problem determines a vertex set such that covers at least edges.The objective is to minimize the total cost of the vertices in plus the penalty of the uncovered edge set,where the penalty is determined by a submodular function.We design a two-phase combinatorial algorithm based on the guessing technique and the primal-dual framework to address the problem.When the submodular penalty cost function is normalized and nondecreasing,the proposed algorithm has an approximation factor of.When the submodular penalty cost function is linear,the approximation factor of the proposed algorithm is reduced to,which is the best factor if the unique game conjecture holds.
基金supported by National Natural Science Foundation of China(Grant Nos.11171160,11331003 and 11471003)the Priority Academic Program Development of Jiangsu Higher Education Institutions+2 种基金the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.13KJB1100188)Natural Science Foundation of Guangdong Province(Grant No.S2012040007521)Sienceand Technology Planning Project in Guangzhou(Grant No.2013J4100077)
文摘We consider the design of semidefinite programming （SDP） based approximation algorithm for the problem Max Hypergraph Cut with Limited Unbalance （MHC-LU）： Find a partition of the vertices of a weighted hypergraph H = （V, E） into two subsets V1, V2 with ｜｜V2｜ - ｜1/1 ｜｜ ≤ u for some given u and maximizing the total weight of the edges meeting both V1 and V2. The problem MHC-LU generalizes several other combinatorial optimization problems including Max Cut, Max Cut with Limited Unbalance （MC-LU）, Max Set Splitting, Max Ek-Set Splitting and Max Hypergraph Bisection. By generalizing several earlier ideas, we present an SDP randomized approximation algorithm for MHC-LU with guaranteed worst-case performance ratios for various unbalance parameters τ = u/｜V｜. We also give the worst-case performance ratio of the SDP-algorithm for approximating MHC-LU regardless of the value of τ. Our strengthened SDP relaxation and rounding method improve a result of Ageev and Sviridenko （2000） on Max Hypergraph Bisection （MHC-LU with u = 0）, and results of Andersson and Engebretsen （1999）, Gaur and Krishnamurti （2001） and Zhang et al. （2004） on Max Set Splitting （MHC-LU with u = ｜V｜）. Furthermore, our new formula for the performance ratio by a tighter analysis compared with that in Galbiati and Maffioli （2007） is responsible for the improvement of a result of Galbiati and Maffioli （2007） on MC-LU for some range of τ.
基金supported in part by Hong Kong General Research Fund(No.CityU143711)Zhening Li was supported in part by Natural Science Foundation of Shanghai(No.12ZR1410100)+1 种基金Ph.D.Programs Foundation of Chinese Ministry of Education(No.20123108120002)Shuzhong Zhang was supported in part by U.S.National Science Foundation(No.CMMI-1161242).
文摘In this paper,we consider approximation algorithms for optimizing a generic multivariate polynomial function in discrete(typically binary)variables.Such models have natural applications in graph theory,neural networks,error-correcting codes,among many others.In particular,we focus on three types of optimization models:(1)maximizing a homogeneous polynomial function in binary variables;(2)maximizing a homogeneous polynomial function in binary variables,mixed with variables under spherical constraints;(3)maximizing an inhomogeneous polynomial function in binary variables.We propose polynomial-time randomized approximation algorithms for such polynomial optimizationmodels,and establish the approximation ratios(or relative approximation ratios whenever appropriate)for the proposed algorithms.Some examples of applications for these models and algorithms are discussed as well.
基金the National Basic Research Program of China(Nos.2015CB358700,2011CBA00300 and 2011CBA00301)the National Natural Science Foundation of China(Nos.61202009,61033001 and 61361136003).
文摘Stochastic optimization has established itself as a major method to handle uncertainty in various optimization problems by modeling the uncertainty by a probability distribution over possible realizations.Traditionally,the main focus in stochastic optimization has been various stochastic mathematical programming(such as linear programming,convex programming).In recent years,there has been a surge of interest in stochastic combinatorial optimization problems from the theoretical computer science community.In this article,we survey some of the recent results on various stochastic versions of classical combinatorial optimization problems.Since most problems in this domain are NP-hard(or#P-hard,or even PSPACE-hard),we focus on the results which provide polynomial time approximation algorithms with provable approximation guarantees.Our discussions are centered around a few representative problems,such as stochastic knapsack,stochastic matching,multi-armed bandit etc.We use these examples to introduce several popular stochastic models,such as the fixed-set model,2-stage stochastic optimization model,stochastic adaptive probing model etc,as well as some useful techniques for designing approximation algorithms for stochastic combinatorial optimization problems,including the linear programming relaxation approach,boosted sampling,content resolution schemes,Poisson approximation etc.We also provide some open research questions along the way.Our purpose is to provide readers a quick glimpse to the models,problems,and techniques in this area,and hopefully inspire new contributions.
基金This research was supported by the National Natural Science Foundation of China(Nos.11271338,11771406,11571321,U1504103).
文摘This paper considers the integrated production and delivery scheduling on a serial batch machine,in which split is allowed in the delivery of the jobs.The objective is to minimize the makespan,i.e.,the maximum delivery completion time of the jobs.Lu et al.(Theor Comput Sci 572:50–57,2015)showed that this problem is strongly NP-hard,and presented a 32-approximation algorithm.In this paper,we present an improved 43-approximation algorithm for this problem.We also present a polynomial-time algorithm for the special case when all jobs have the identical weight.
基金the National Natural Science Foundation of China(No.11971146)the Natural Science Foundation of Hebei Province of China(Nos.A2019205089 and A2019205092)+1 种基金Hebei Province Foundation for Returnees(No.CL201714)the Graduate Innovation Grant Program of Hebei Normal University(No.CXZZSS2022053).
文摘In this paper,we consider the parallel-machine customer order scheduling with delivery time and submodular rejection penalties.In this problem,we are given m dedicated machines in parallel and n customer orders.Each order has a delivery time and consists of m product types and each product type should be manufactured on a dedicated machine.An order is either rejected,in which case a rejection penalty has to be paid,or accepted and manufactured on the m dedicated machines.The objective is to find a solution to minimize the sum of the maximum delivery completion time of the accepted orders and the penalty of the rejected orders which is determined by a submodular function.We design an LP rounding algorithm with approximation ratio of n+1 for this problem.
基金supported by the project of Central University Basic Research Fund(HEUCF150903)the project of the major research task,institute of Policy and Management,Chinese Academy of Sciences(Y201181z01)the National Natural Science Foundation of China(71273072)
文摘Abstract We study the fleet size and mix vehicle routing problem with constraints on the capacity of each vehicle. The objective is to minimize the total cost including fixed utilization cost of vehicles and traveling cost by vehicles. We give differential approximation algorithms for the fleet size and mix vehicle routing problem （FSMVRP） with two kinds of vehicles, the capacities of which are respectively nlk and n2k, n2 〉 nl ≥ 1, k ≥ 1. Using existing theories for vehicle routing problems and feature of the algorithms represented in the paper, we also prove that the algorithms give（1-6n＋3/（n＋1）2k＋n＋1）differential approximation ratio for （k, nk） VRP, n 〉 1and （1-6n2＋3n/n1k＋n2k）2k）differential approximation ratio for （nlk, n2k）VRP, n2 〉 nl 〉 1.
