共查询到19条相似文献,搜索用时 218 毫秒
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为了便于建立与有上下界网络最大流与最小截问题有关的决策支持系统,本文给出一个求有上下界网络最大流与最小截的数值算法,证明了算法的理论依据,并举例说明了算法在堵塞流理论中的应用。该算法能判定问题是否有可行解,在问题有可行解的情况下能求得问题的最优解。该算法具有易于编程实现、收敛性好等优点。数值实验表明该算法有较高的计算效率,可用于求解最小饱和流问题。 相似文献
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两端固定资源连续分配问题的区间根式解算法证明 总被引:1,自引:0,他引:1
对两端固定资源连续分配问题,动态规划解法过程复杂.针对目标函数及约束条件均为线性函数的此类问题,给出一个根式解的算法证明,将针对点的根式解的算法推广到区间的根式解,使该根式解的算法真正具有实用性. 相似文献
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目前求解置换流水车间调度问题的智能优化算法都是随机型优化方法,存在的一个问题是解的稳定性较差。针对该问题,本文给出一种确定型智能优化算法——中心引力优化算法的求解方法。为处理基本中心引力优化算法对初始解选择要求高的问题,利用低偏差序列生成初始解,提高初始解质量;利用加速度和位置迭代方程更新解的状态;利用两位置交换排序法进行局部搜索,提高算法的优化性能。采用置换流水车间调度问题标准测试算例进行数值实验,并和基本中心引力优化算法、NEH启发式算法、微粒群优化算法和萤火虫算法进行比较。结果表明该算法不仅具有更好的解的稳定性,而且具有更高的计算精度,为置换流水车间调度问题的求解提供了一种可行有效的方法。 相似文献
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该文研究了反对称偏对称矩阵反问题的最小二乘解,得到了该问题解的表达式以及该问题有解的充分必要条件.证明了其最佳逼近解的存在性和唯一性,建立了其最佳逼近解的表达式,并给出了求最佳逼近解的数值算法和算例. 相似文献
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低阶精确罚函数的一种二阶光滑逼近 总被引:1,自引:0,他引:1
给出了求解约束优化问题的低阶精确罚函数的一种二阶光滑逼近方法,证明了光滑后的罚优化问题的最优解是原约束优化问题的ε-近似最优解,基于光滑后的罚优化问题,提出了求解约束优化问题的一种新的算法,并证明了该算法的收敛性,数值例子表明该算法对于求解约束优化问题是有效的. 相似文献
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带投资约束且p不确定的推广p-中位问题 总被引:1,自引:0,他引:1
p-中位问题是设施选址中的一个经典模型,在交通、物流等领域有着广泛应用.在经典p-中位问题的基础上提出一种p不确定的推广p-中位问题,并且加上总投资约束,使得此推广模型更加实用.针对此推广模型,提出三种启发式算法:简单启发式算法、变邻域搜索算法和改进的遗传算法.数值实验结果表明变邻域搜索算法和改进的遗传算法在求解此推广模型时是有效的. 相似文献
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Guoliang Xue 《Numerical Algorithms》1995,9(1):1-12
In this paper we partially resolve an open problem in spherical facility location. The spherical facility location problem is a generalization of the planar Euclidean facility location problem. This problem was first studied by Katz and Cooper and by Drezner and Wesolowsky where a Weszfeld-like algorithm was proposed. This algorithm is very simple and does not require a line search. However, its convergence has been an open problem for more than ten years. In this paper, we prove that the sequence generated by the algorithm converges to the unique optimal solution under the condition that the oscillation of the sequence converges to zero. We conjecture that the algorithm is a descent algorithm and prove that the sequence generated by the algorithm converges to the optimal solution under this conjecture. 相似文献
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This article presents a simplicial branch and bound algorithm for globally solving generalized linear multiplicative programming problem (GLMP). Since this problem does not seem to have been studied previously, the algorithm is apparently the first algorithm to be proposed for solving such problem. In this algorithm, a well known simplicial subdivision is used in the branching procedure and the bound estimation is performed by solving certain linear programs. Convergence of this algorithm is established, and some experiments are reported to show the feasibility of the proposed algorithm. 相似文献
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István Borgulya 《Central European Journal of Operations Research》2008,16(4):331-343
In this paper, we present a multi-objective evolutionary algorithm for the capacitated vehicle routing problem with route
balancing. The algorithm is based on a formerly developed multi-objective algorithm using an explicit collective memory method,
namely the extended virtual loser (EVL). We adapted and improved the algorithm and the EVL method for this problem. We achieved
good results with this simple technique. In case of this problem the quality of the results of the algorithm is similar to
that of other evolutionary algorithms. 相似文献
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H. P. Benson 《Journal of Optimization Theory and Applications》2008,137(1):105-120
This article presents a branch-and-bound algorithm for globally solving the problem (P) of maximizing a generalized concave
multiplicative function over a compact convex set. Since problem (P) does not seem to have been studied previously, the algorithm
is apparently the first algorithm to be proposed for solving this problem. It works by globally solving a problem (P1) equivalent
to problem (P). The branch-and-bound search undertaken by the algorithm uses rectangular partitioning and takes place in a
space which typically has a much smaller dimension than the space to which the decision variables of problem (P) belong. Convergence
of the algorithm is shown; computational considerations and benefits for users of the algorithm are given. A sample problem
is also solved. 相似文献
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Decomposition Branch-and-Bound Based Algorithm for Linear Programs with Additional Multiplicative Constraints 总被引:2,自引:0,他引:2
H. P. Benson 《Journal of Optimization Theory and Applications》2005,126(1):41-61
This article presents an algorithm for globally solving a linear program (P) that contains several additional multiterm multiplicative constraints. To our knowledge, this is the first algorithm proposed to date for globally solving Problem (P). The algorithm decomposes the problem to obtain a master problem of low rank. To solve the master problem, the algorithm uses a branch-and-bound scheme where Lagrange duality theory is used to obtain the lower bounds. As a result, the lower-bounding subproblems in the algorithm are ordinary linear programs. Convergence of the algorithm is shown and a solved sample problem is given. 相似文献
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Sven Axsäter 《European Journal of Operational Research》1980,4(6):395-398
In this paper a relationship between the vehicle scheduling problem and the dynamic lot size problem is considered. For the latter problem we assume that order quantities for different products can be determined separately. Demand is known over our n-period production planning horizon. For a certain product our task is to decide for each period if it should be produced or not. If it is produced, what is its economic lot size? Our aim here is to minimize the combined set-up and inventory holding costs. The optimal solution of this problem is given by the well-known Wagner-Whitin dynamic lot size algorithm. Also many heuristics for solving this problem have been presented. In this article we point out the analogy of the dynamic lot size problem to a certain vehicle scheduling problem. For solving vehicle scheduling problems the heuristic algorithm developed by Clark and Wright in very often used. Applying this algorithm to the equivalent vehicle scheduling problem we obtain by analogy a simple heuristic algorithm for the dynamic lot size problem. Numerical results indicate that computation time is reduced by about 50% compared to the Wagner-Whitin algorithm. The average cost appears to be approximately 0.8% higher than optimum. 相似文献