The Quantum Approximate Optimization Algorithm(QAOA)is an algorithmic framework for finding approximate solutions to combinatorial optimization problems.It consists of interleaved unitary transformations induced by tw...The Quantum Approximate Optimization Algorithm(QAOA)is an algorithmic framework for finding approximate solutions to combinatorial optimization problems.It consists of interleaved unitary transformations induced by two operators labelled the mixing and problem Hamiltonians.To fit this framework,one needs to transform the original problem into a suitable form and embed it into these two Hamiltonians.In this paper,for the well-known NP-hard Traveling Salesman Problem(TSP),we encode its constraints into the mixing Hamiltonian rather than the conventional approach of adding penalty terms to the problem Hamiltonian.Moreover,we map edges(routes)connecting each pair of cities to qubits,which decreases the search space significantly in comparison to other approaches.As a result,our method can achieve a higher probability for the shortest round-trip route with only half the number of qubits consumed compared to IBM Q’s approach.We argue the formalization approach presented in this paper would lead to a generalized framework for finding,in the context of QAOA,high-quality approximate solutions to NP optimization problems.展开更多
In the era of big data,correlation analysis is significant because it can quickly detect the correlation between factors.And then,it has been received much attention.Due to the good properties of generality and equita...In the era of big data,correlation analysis is significant because it can quickly detect the correlation between factors.And then,it has been received much attention.Due to the good properties of generality and equitability of the maximal information coefficient(MIC),MIC is a hotspot in the research of correlation analysis.However,if the original approximate algorithm of MIC is directly applied into mining correlations in big data,the computation time is very long.Then the theoretical time complexity of the original approximate algorithm is analyzed in depth and the time complexity is n2.4 when parameters are default.And the experiments show that the large number of candidate partitions of random relationships results in long computation time.The analysis is a good preparation for the next step work of designing new fast algorithms.展开更多
This paper proposes two kinds of approximate proximal point algorithms （APPA） for monotone variational inequalities, both of which can be viewed as two extended versions of Solodov and Svaiter＇s APPA in the paper ...This paper proposes two kinds of approximate proximal point algorithms （APPA） for monotone variational inequalities, both of which can be viewed as two extended versions of Solodov and Svaiter＇s APPA in the paper ＂Error bounds for proximal point subproblems and associated inexact proximal point algorithms＂ published in 2000. They are both prediction- correction methods which use the same inexactness restriction; the only difference is that they use different search directions in the correction steps. This paper also chooses an optimal step size in the two versions of the APPA to improve the profit at each iteration. Analysis also shows that the two APPAs are globally convergent under appropriate assumptions, and we can expect algorithm 2 to get more progress in every iteration than algorithm 1. Numerical experiments indicate that algorithm 2 is more efficient than algorithm 1 with the same correction step size,展开更多
In order to find roots of maximal monotone operators, this paper introduces and studies the modified approximate proximal point algorithm with an error sequence {e k} such that || ek || \leqslant hk || xk - [(x)\tilde...In order to find roots of maximal monotone operators, this paper introduces and studies the modified approximate proximal point algorithm with an error sequence {e k} such that || ek || \leqslant hk || xk - [(x)\tilde]k ||\left\| { e^k } \right\| \leqslant \eta _k \left\| { x^k - \tilde x^k } \right\| with ?k = 0￥ ( hk - 1 ) < + ￥\sum\limits_{k = 0}^\infty {\left( {\eta _k - 1} \right)} and infk \geqslant 0 hk = m\geqslant 1\mathop {\inf }\limits_{k \geqslant 0} \eta _k = \mu \geqslant 1 . Here, the restrictions on {η k} are very different from the ones on {η k}, given by He et al (Science in China Ser. A, 2002, 32 (11): 1026–1032.) that supk \geqslant 0 hk = v < 1\mathop {\sup }\limits_{k \geqslant 0} \eta _k = v . Moreover, the characteristic conditions of the convergence of the modified approximate proximal point algorithm are presented by virtue of the new technique very different from the ones given by He et al.展开更多
A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, a...A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, and uses an approximate visibility technique to accurately and efficiently determine which objects will be visible in the coming future and prefetch those objects from disk before they are rendered, view-dependent rendering technique provides the ability to change level of detail over the surface seamlessly and smoothly in real-time according to cell solidity value.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
This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constru...This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs subwindows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε ＋ 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n （ n≤N） elements. The second algorithm outputs at most 1/ε ＋ 2 elements. The analytical and experimental results show that our algorithms are accurate and effective.展开更多
The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a ca...The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a capacity Ci.The goal is to find a subset of items of maximum profit such that they have a feasible packing in the knapsacks.MKP(B,S,m,n) is strongly NP- Complete and no polynomial- time approximation algorithm can have an approxima- tion ratio better than0 .5 .In the last ten years,semi- definite programming has been empolyed to solve some combinatorial problems successfully.This paper firstly presents a semi- definite re- laxation algorithm (MKPS) for MKP (B,S,m,n) .It is proved that MKPS have a approxima- tion ratio better than 0 .5 for a subclass of MKP (B,S,m,n) with n≤ 1 0 0 ,m≤ 5 and maxnj=1{ wj} minmi=1{ Ci} ≤ 2 3 .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
This paper describes an extremely fast polynomial time algorithm, the NOVCA （Near Optimal Vertex Cover Algorithm） that produces an optimal or near optimal vertex cover for any known undirected graph G （V, E）. NOVC...This paper describes an extremely fast polynomial time algorithm, the NOVCA （Near Optimal Vertex Cover Algorithm） that produces an optimal or near optimal vertex cover for any known undirected graph G （V, E）. NOVCA is based on the idea of（l） including the vertex having maximum degree in the vertex cover and （2） rendering the degree of a vertex to zero by including all its adjacent vertices. The three versions of algorithm, NOVCA-I, NOVCA-II, and NOVCA-random, have been developed. The results identifying bounds on the size of the minimum vertex cover as well as polynomial complexity of algorithm are given with experimental verification. Future research efforts will be directed at tuning the algorithm and providing proof for better approximation ratio with NOVCA compared to any available vertex cover algorithms.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 w...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
We study scheduling problems with rejection on parallel-machine.Each job consists of a processing time,a rejection cost,and a release date.The goal is to minimize the makespan of the jobs accepted when the total rejec...We study scheduling problems with rejection on parallel-machine.Each job consists of a processing time,a rejection cost,and a release date.The goal is to minimize the makespan of the jobs accepted when the total rejection cost is not larger than a given threshold.Firstly,we verify that these problems are NP-hard.Secondly,for the multiprocessor scheduling problem with rejection,we give a pseudo-polynomial algorithm and two fully polynomial approximation schemes(FPTAS for short)for fixed positive integer m,where m is the number of machines.For the scheduling problem with rejection and the job with non-identical release time on m machines,we also design a pseudo-polynomial algorithm and a fully polynomial approximation scheme when m is a fixed positive integer.We provide an approximation algorithm with the worst case performance 2 for arbitrary positive integer m.Finally,we discuss the online scheduling problem with rejection.We show that even if there are just two distinct arrive times for the jobs,there is not any online algorithm whose competitive ratio is constant for it.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
Capacitated facility location problem(CFLP)is a classical combinatorial optimization problem that has various applications in operations research,theoretical computer science,and management science.In the CFLP,we have...Capacitated facility location problem(CFLP)is a classical combinatorial optimization problem that has various applications in operations research,theoretical computer science,and management science.In the CFLP,we have a potential facilities set and a clients set.Each facility has a certain capacity and an open cost,and each client has a spliitable demand that need to be met.The goal is to open some facilities and assign all clients to these open facilities so that the total cost is as low as possible.The CFLP is NP-hard(non-deterministic polynomial-hard),and a large amount of work has been devoted to designing approximation algorithms for CFLP and its variants.Following this vein,we introduce a new variant of CFLP called capacitated uniform facility location problem with soft penalties(CUFLPSP),in which the demand of each client can be partially rejected by paying penalty costs.As a result,we present a linear programming-rounding(LP-rounding)based 5.5122-approximation algorithm for the CUFLPSP.展开更多
Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact soluti...Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries.展开更多
In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji co...In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji consists of two tasks Ai and Bi ,and task Ai must be completed before task Bi can start. Furthermore ,task Ai can be processed on M1 for ai time units ,or on Mw for ai^J time units ,while task Bi can only be processed on M2 for bi time units. Jobs and machines are available at time zero and no preemption is allowed. The objective is to minimize the maximum job completion time. It is showed that this problem is NP-hard. And a pseudo-polynomial time optimal algorithm is presented. A polynomial time approximation algorithm with worst-case ratio 2 is also presented.展开更多
基金This work is supported by the Natural Science Foundation,China(Grant No.61802002)Natural Science Foundation of Anhui Province,China(Grant No.1708085MF162).
文摘The Quantum Approximate Optimization Algorithm(QAOA)is an algorithmic framework for finding approximate solutions to combinatorial optimization problems.It consists of interleaved unitary transformations induced by two operators labelled the mixing and problem Hamiltonians.To fit this framework,one needs to transform the original problem into a suitable form and embed it into these two Hamiltonians.In this paper,for the well-known NP-hard Traveling Salesman Problem(TSP),we encode its constraints into the mixing Hamiltonian rather than the conventional approach of adding penalty terms to the problem Hamiltonian.Moreover,we map edges(routes)connecting each pair of cities to qubits,which decreases the search space significantly in comparison to other approaches.As a result,our method can achieve a higher probability for the shortest round-trip route with only half the number of qubits consumed compared to IBM Q’s approach.We argue the formalization approach presented in this paper would lead to a generalized framework for finding,in the context of QAOA,high-quality approximate solutions to NP optimization problems.
基金Supported by the China Postdoctoral Science Foundation(2019M650981)Shandong Provincial Natural Science Foundation,China(ZR2018MG003)。
文摘In the era of big data,correlation analysis is significant because it can quickly detect the correlation between factors.And then,it has been received much attention.Due to the good properties of generality and equitability of the maximal information coefficient(MIC),MIC is a hotspot in the research of correlation analysis.However,if the original approximate algorithm of MIC is directly applied into mining correlations in big data,the computation time is very long.Then the theoretical time complexity of the original approximate algorithm is analyzed in depth and the time complexity is n2.4 when parameters are default.And the experiments show that the large number of candidate partitions of random relationships results in long computation time.The analysis is a good preparation for the next step work of designing new fast algorithms.
文摘This paper proposes two kinds of approximate proximal point algorithms （APPA） for monotone variational inequalities, both of which can be viewed as two extended versions of Solodov and Svaiter＇s APPA in the paper ＂Error bounds for proximal point subproblems and associated inexact proximal point algorithms＂ published in 2000. They are both prediction- correction methods which use the same inexactness restriction; the only difference is that they use different search directions in the correction steps. This paper also chooses an optimal step size in the two versions of the APPA to improve the profit at each iteration. Analysis also shows that the two APPAs are globally convergent under appropriate assumptions, and we can expect algorithm 2 to get more progress in every iteration than algorithm 1. Numerical experiments indicate that algorithm 2 is more efficient than algorithm 1 with the same correction step size,
基金Supported both by the Teaching and Research Award Fund for Outstanding Young Teachers inHigher Educational Institutions of MOEChinaand by the Dawn Program Fund in Shanghai
文摘In order to find roots of maximal monotone operators, this paper introduces and studies the modified approximate proximal point algorithm with an error sequence {e k} such that || ek || \leqslant hk || xk - [(x)\tilde]k ||\left\| { e^k } \right\| \leqslant \eta _k \left\| { x^k - \tilde x^k } \right\| with ?k = 0￥ ( hk - 1 ) < + ￥\sum\limits_{k = 0}^\infty {\left( {\eta _k - 1} \right)} and infk \geqslant 0 hk = m\geqslant 1\mathop {\inf }\limits_{k \geqslant 0} \eta _k = \mu \geqslant 1 . Here, the restrictions on {η k} are very different from the ones on {η k}, given by He et al (Science in China Ser. A, 2002, 32 (11): 1026–1032.) that supk \geqslant 0 hk = v < 1\mathop {\sup }\limits_{k \geqslant 0} \eta _k = v . Moreover, the characteristic conditions of the convergence of the modified approximate proximal point algorithm are presented by virtue of the new technique very different from the ones given by He et al.
文摘A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, and uses an approximate visibility technique to accurately and efficiently determine which objects will be visible in the coming future and prefetch those objects from disk before they are rendered, view-dependent rendering technique provides the ability to change level of detail over the surface seamlessly and smoothly in real-time according to cell solidity value.
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.
基金Supported by the National Natural Science Foun-dation of China (60403027)
文摘This paper presents two one-pass algorithms for dynamically computing frequency counts in sliding window over a data stream-computing frequency counts exceeding user-specified threshold ε. The first algorithm constructs subwindows and deletes expired sub-windows periodically in sliding window, and each sub-window maintains a summary data structure. The first algorithm outputs at most 1/ε ＋ 1 elements for frequency queries over the most recent N elements. The second algorithm adapts multiple levels method to deal with data stream. Once the sketch of the most recent N elements has been constructed, the second algorithm can provides the answers to the frequency queries over the most recent n （ n≤N） elements. The second algorithm outputs at most 1/ε ＋ 2 elements. The analytical and experimental results show that our algorithms are accurate and effective.
基金Supported by the National Natural Science Foundation of China(1 9971 0 78)
文摘The multiple knapsack problem denoted by MKP (B,S,m,n) can be defined as fol- lows.A set B of n items and a set Sof m knapsacks are given such thateach item j has a profit pjand weightwj,and each knapsack i has a capacity Ci.The goal is to find a subset of items of maximum profit such that they have a feasible packing in the knapsacks.MKP(B,S,m,n) is strongly NP- Complete and no polynomial- time approximation algorithm can have an approxima- tion ratio better than0 .5 .In the last ten years,semi- definite programming has been empolyed to solve some combinatorial problems successfully.This paper firstly presents a semi- definite re- laxation algorithm (MKPS) for MKP (B,S,m,n) .It is proved that MKPS have a approxima- tion ratio better than 0 .5 for a subclass of MKP (B,S,m,n) with n≤ 1 0 0 ,m≤ 5 and maxnj=1{ wj} minmi=1{ Ci} ≤ 2 3 .
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This paper describes an extremely fast polynomial time algorithm, the NOVCA （Near Optimal Vertex Cover Algorithm） that produces an optimal or near optimal vertex cover for any known undirected graph G （V, E）. NOVCA is based on the idea of（l） including the vertex having maximum degree in the vertex cover and （2） rendering the degree of a vertex to zero by including all its adjacent vertices. The three versions of algorithm, NOVCA-I, NOVCA-II, and NOVCA-random, have been developed. The results identifying bounds on the size of the minimum vertex cover as well as polynomial complexity of algorithm are given with experimental verification. Future research efforts will be directed at tuning the algorithm and providing proof for better approximation ratio with NOVCA compared to any available vertex cover algorithms.
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.12271295 and 12371319)Shandong Province Natural Science Foundation(Nos.ZR2019MA061 and ZR2022MA038).
文摘We study scheduling problems with rejection on parallel-machine.Each job consists of a processing time,a rejection cost,and a release date.The goal is to minimize the makespan of the jobs accepted when the total rejection cost is not larger than a given threshold.Firstly,we verify that these problems are NP-hard.Secondly,for the multiprocessor scheduling problem with rejection,we give a pseudo-polynomial algorithm and two fully polynomial approximation schemes(FPTAS for short)for fixed positive integer m,where m is the number of machines.For the scheduling problem with rejection and the job with non-identical release time on m machines,we also design a pseudo-polynomial algorithm and a fully polynomial approximation scheme when m is a fixed positive integer.We provide an approximation algorithm with the worst case performance 2 for arbitrary positive integer m.Finally,we discuss the online scheduling problem with rejection.We show that even if there are just two distinct arrive times for the jobs,there is not any online algorithm whose competitive ratio is constant for it.
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 by the National Natural Science Foundation of China(Nos.11971349,12071442,12371320,and 12371318).
文摘Capacitated facility location problem(CFLP)is a classical combinatorial optimization problem that has various applications in operations research,theoretical computer science,and management science.In the CFLP,we have a potential facilities set and a clients set.Each facility has a certain capacity and an open cost,and each client has a spliitable demand that need to be met.The goal is to open some facilities and assign all clients to these open facilities so that the total cost is as low as possible.The CFLP is NP-hard(non-deterministic polynomial-hard),and a large amount of work has been devoted to designing approximation algorithms for CFLP and its variants.Following this vein,we introduce a new variant of CFLP called capacitated uniform facility location problem with soft penalties(CUFLPSP),in which the demand of each client can be partially rejected by paying penalty costs.As a result,we present a linear programming-rounding(LP-rounding)based 5.5122-approximation algorithm for the CUFLPSP.
基金the financial support from the National Science Foundation of China(22078190 and 12002196)the National Key Research and Development Program of China(2020YFB1505802)。
文摘Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries.
文摘In this paper,a two-stage semi-hybrid flowshop problem which appears in graphics processing is studied. For this problem, there are two machines M1 and M2, and a set of independent jobs J= {J1 ,J2 ,…,Jn }. Each Ji consists of two tasks Ai and Bi ,and task Ai must be completed before task Bi can start. Furthermore ,task Ai can be processed on M1 for ai time units ,or on Mw for ai^J time units ,while task Bi can only be processed on M2 for bi time units. Jobs and machines are available at time zero and no preemption is allowed. The objective is to minimize the maximum job completion time. It is showed that this problem is NP-hard. And a pseudo-polynomial time optimal algorithm is presented. A polynomial time approximation algorithm with worst-case ratio 2 is also presented.
