This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algo...This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algorithms(simulated annealing(SA),particle swarm optimization(PSO)and genetic algorithm(GA))are provided.For evaluating the performances of algorithms,the distribution of total cost(objective function)and the average computational time are compared.As a result,both GA and PSO have better cost performances with lower average total costs and smaller standard deviations.When the scale of the multilevel lot-sizing problem becomes larger,PSO is of a shorter computational time.展开更多
This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several proper...This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.展开更多
In this paper we develop multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for ill-posed problems. The algorithm and its convergence analysis are pr...In this paper we develop multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for ill-posed problems. The algorithm and its convergence analysis are presented in an abstract framework.展开更多
The maximum satisfiability problem (MAX-SAT) refers to the task of finding a variable assignment that satisfies the maximum number of clauses (or the sum of weight of satisfied clauses) in a Boolean Formula. Most loca...The maximum satisfiability problem (MAX-SAT) refers to the task of finding a variable assignment that satisfies the maximum number of clauses (or the sum of weight of satisfied clauses) in a Boolean Formula. Most local search algorithms including tabu search rely on the 1-flip neighbourhood structure. In this work, we introduce a tabu search algorithm that makes use of the multilevel paradigm for solving MAX-SAT problems. The multilevel paradigm refers to the process of dividing large and difficult problems into smaller ones, which are hopefully much easier to solve, and then work backward towards the solution of the original problem, using a solution from a previous level as a starting solution at the next level. This process aims at looking at the search as a multilevel process operating in a coarse-to-fine strategy evolving from k-flip neighbourhood to 1-flip neighbourhood-based structure. Experimental results comparing the multilevel tabu search against its single level variant are presented.展开更多
1 Introduetion Many industrial and engineering applieations require numerieally solving ill-posed Problems. Regularization methods are employed to find approximate solutions of these problems.The choice of regularization
In this paper we develop two multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for linear ill-posed problems. The two algorithms and their convergen...In this paper we develop two multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for linear ill-posed problems. The two algorithms and their convergence analyses are presented in an abstract framework.展开更多
In this paper, an algorithm based on a shifted inverse power iteration for computing generalized eigenvalues with corresponding eigenvectors of a large scale sparse symmetric positive definite matrix pencil is present...In this paper, an algorithm based on a shifted inverse power iteration for computing generalized eigenvalues with corresponding eigenvectors of a large scale sparse symmetric positive definite matrix pencil is presented. It converges globally with a cubic asymptotic convergence rate, preserves sparsity of the original matrices and is fully parallelizable. The algebraic multilevel itera-tion method (AMLI) is used to improve the efficiency when symmetric positive definite linear equa-tions need to be solved.展开更多
During financial crisis,companies constantly need free cash flows to efficiently react to any uncertainty,thus ensuring solvency.Working capital requirement(WCR)has been recognized as a key factor for releasing tied u...During financial crisis,companies constantly need free cash flows to efficiently react to any uncertainty,thus ensuring solvency.Working capital requirement(WCR)has been recognized as a key factor for releasing tied up cash in companies.However,in literatures related to lot-sizing problem,WCR has only been studied in the single-level supply chain context.In this paper,we initially adopt WCR model for a multi-level case.A two-level(supplier–customer)model is established on the basis of the classic multi-level lot-sizing model integrated with WCR financing cost.To tackle this problem,we propose sequential and centralized approaches to solve the two-level case with a serial chain structure.The ZIO(Zero Inventory Ordering)property is further confirmed valid in both cases.This property allows us to establish a dynamic programming-based algorithm,which solves the problem in O(T).Finally,numerical tests show differences in optimal plans obtained by both approaches and the influence of varying delays in payment on the WCR of both actors.展开更多
为了解决MMC-HVDC(Modular Multilevel Converter Based on HVDC,MMC-HVDC)交流侧系统故障时的过流问题,以及增强MMC换流器的低压穿越能力,通过对换流器功率数学模型及控制方式进行分析,发现了换流器有功和无功功率解耦的PI控制方式。...为了解决MMC-HVDC(Modular Multilevel Converter Based on HVDC,MMC-HVDC)交流侧系统故障时的过流问题,以及增强MMC换流器的低压穿越能力,通过对换流器功率数学模型及控制方式进行分析,发现了换流器有功和无功功率解耦的PI控制方式。提出了当交流侧发生对称和不对称故障时,通过控制PI值限制功率输出,同时由交流电压偏差有效值生成正负序补偿电流的紧急功率支援控制策略。将这种控制策略添加到电磁暂态仿真系统当中,当系统网侧发生对称或不对称故障时,利用数值仿真技术分析了换流器阀侧的电能质量。仿真结果验证了所提出的控制方法对故障时过流抑制的有效性,同时增强了换流器的低压穿越能力。展开更多
基金the National Natural Science Foundation of China(No.70971017)the Humanities and Social Sciences Project of Ministry of Education(No.10YJC630009)+1 种基金the Social Science Fund of Zhejiang Province(No.10CGGL21YBQ)the Natural Science Foundation of Zhejiang Province(No.Y1100854)
文摘This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning(MRP)systems.Three evolutionary algorithms(simulated annealing(SA),particle swarm optimization(PSO)and genetic algorithm(GA))are provided.For evaluating the performances of algorithms,the distribution of total cost(objective function)and the average computational time are compared.As a result,both GA and PSO have better cost performances with lower average total costs and smaller standard deviations.When the scale of the multilevel lot-sizing problem becomes larger,PSO is of a shorter computational time.
基金supported by National Natural Science Foundation of China (No. 10671108 and 70971076)Found for the Doctoral Program of Higher Education of Ministry of Education of China (No. 20070446001)+1 种基金Innovation Planning Project of Shandong Province (No. SDYY06034)Foundation of Qufu Normal University (No. XJZ200849)
文摘This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.
基金Natural Science Foundation of China under grants 10371137 and 10201034 the Foundation of Doctoral Program of National Higher Education of China under grant 20030558008 Guangdong Provincial Natural Science Foundation of China under grant 1011170 the Foundation of Zhongshan University Advanced Research Center.
文摘In this paper we develop multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for ill-posed problems. The algorithm and its convergence analysis are presented in an abstract framework.
文摘The maximum satisfiability problem (MAX-SAT) refers to the task of finding a variable assignment that satisfies the maximum number of clauses (or the sum of weight of satisfied clauses) in a Boolean Formula. Most local search algorithms including tabu search rely on the 1-flip neighbourhood structure. In this work, we introduce a tabu search algorithm that makes use of the multilevel paradigm for solving MAX-SAT problems. The multilevel paradigm refers to the process of dividing large and difficult problems into smaller ones, which are hopefully much easier to solve, and then work backward towards the solution of the original problem, using a solution from a previous level as a starting solution at the next level. This process aims at looking at the search as a multilevel process operating in a coarse-to-fine strategy evolving from k-flip neighbourhood to 1-flip neighbourhood-based structure. Experimental results comparing the multilevel tabu search against its single level variant are presented.
基金The NNSF (10371137 and 10201034) of China, the Foundation of Doctoral Program of National Higher Education (20030558008)Guangdong Provincial Natural Science Foundation (1011170) of China and the Foundation of Zhongshan University Advanced Research Center.
文摘1 Introduetion Many industrial and engineering applieations require numerieally solving ill-posed Problems. Regularization methods are employed to find approximate solutions of these problems.The choice of regularization
基金The NSF(0611005)of Jiangxi Province and the SF(2007293)of Jiangxi Provincial Education Department.
文摘In this paper we develop two multilevel iteration methods for solving linear systems resulting from the Galerkin method and Tikhonov regularization for linear ill-posed problems. The two algorithms and their convergence analyses are presented in an abstract framework.
文摘In this paper, an algorithm based on a shifted inverse power iteration for computing generalized eigenvalues with corresponding eigenvectors of a large scale sparse symmetric positive definite matrix pencil is presented. It converges globally with a cubic asymptotic convergence rate, preserves sparsity of the original matrices and is fully parallelizable. The algebraic multilevel itera-tion method (AMLI) is used to improve the efficiency when symmetric positive definite linear equa-tions need to be solved.
基金This work is supported by the Ministry of Science and Technology of China(Grant No.2016YFC0503606)the National Natural Science Foundation of China for Distinguished Young Scholar(Grant No.71825007)ANR FILEAS FOG project.
文摘During financial crisis,companies constantly need free cash flows to efficiently react to any uncertainty,thus ensuring solvency.Working capital requirement(WCR)has been recognized as a key factor for releasing tied up cash in companies.However,in literatures related to lot-sizing problem,WCR has only been studied in the single-level supply chain context.In this paper,we initially adopt WCR model for a multi-level case.A two-level(supplier–customer)model is established on the basis of the classic multi-level lot-sizing model integrated with WCR financing cost.To tackle this problem,we propose sequential and centralized approaches to solve the two-level case with a serial chain structure.The ZIO(Zero Inventory Ordering)property is further confirmed valid in both cases.This property allows us to establish a dynamic programming-based algorithm,which solves the problem in O(T).Finally,numerical tests show differences in optimal plans obtained by both approaches and the influence of varying delays in payment on the WCR of both actors.
文摘为了解决MMC-HVDC(Modular Multilevel Converter Based on HVDC,MMC-HVDC)交流侧系统故障时的过流问题,以及增强MMC换流器的低压穿越能力,通过对换流器功率数学模型及控制方式进行分析,发现了换流器有功和无功功率解耦的PI控制方式。提出了当交流侧发生对称和不对称故障时,通过控制PI值限制功率输出,同时由交流电压偏差有效值生成正负序补偿电流的紧急功率支援控制策略。将这种控制策略添加到电磁暂态仿真系统当中,当系统网侧发生对称或不对称故障时,利用数值仿真技术分析了换流器阀侧的电能质量。仿真结果验证了所提出的控制方法对故障时过流抑制的有效性,同时增强了换流器的低压穿越能力。
