Minimum convex piecewise linear cost tension problem on quasi-<Emphasis Type="Italic">k</Emphasis> series-parallel graphs

Some hypermedia synchronization issues request the resolution of the minimum convex piecewise linear cost tension problem (CPLCT problem) on directed graphs that are close to two-terminal series-parallel graphs (TTSP-graphs), the so-called quasi-k series-parallel graphs (k-QSP graphs). An aggregation algorithm has already been introduced for the CPLCT problem on TTSP-graphs. We propose here a reconstruction method, based on the aggregation and the well-known out-of-kilter techniques, to solve the problem on k-QSP graphs. One of the main steps being to decompose a graph into TTSP-subgraphs, methods based on the recognition of TTSP-graphs are thoroughly discussed.Received: October 2003, Revised: July 2004, MSC classification: 90C35, 05C85     

Note on “Inverse minimum cost flow problems under the weighted Hamming distance”

Jiang et al. proposed an algorithm to solve the inverse minimum cost flow problems under the bottleneck-type weighted Hamming distance [Y. Jiang, L. Liu, B. Wuc, E. Yao, Inverse minimum cost flow problems under the weighted Hamming distance, European Journal of Operational Research 207 (2010) 50–54]. In this note, it is shown that their proposed algorithm does not solve correctly the inverse problem in the general case due to some incorrect results in that article. Then, a new algorithm is proposed to solve the inverse problem in strongly polynomial time. The algorithm uses the linear search technique and solves a shortest path problem in each iteration.     

The biobjective undirected two-commodity minimum cost flow problem

We address the two-commodity minimum cost flow problem considering two objectives. We show that the biobjective undirected two-commodity minimum cost flow problem can be split into two standard biobjective minimum cost flow problems using the change of variables approach. This technique allows us to develop a method that finds all the efficient extreme points in the objective space for the two-commodity problem solving two biobjective minimum cost flow problems. In other words, we generalize the Hu's theorem for the biobjective undirected two-commodity minimum cost flow problem. In addition, we develop a parametric network simplex method to solve the biobjective problem.     

动态最小费用路在L1模下的逆问题讨论

考察动态最小费用路在L_1模下的逆问题,其中在弧费用的定义中,将弧(i,j)上的运行时间d_(ij)(t)分成最小可能运行时间d_(ij)~*和超出的运行时间(excess time)e_(ij)(t)两部分,弧(i,j)上费用即为两者赋权之和.在逆问题的讨论中考虑先将动态网络中的问题通过时间扩张网络G~T转化为静态问题,然后再利用解线性规划的逆问题的方法来解该动态最短路问题的逆问题.     

无容量限制的最小费用流问题

本文研究了无容量限制的带固定费用和可变费用的单物资和二物资的最小费用流问题,并分别给出了多项式算法.最后应用该算法,计算了一个二物资的最小费用流问题的实例.     

Branch and bound based solution algorithms for the budget constrained discrete time/cost trade-off problem

The time/cost trade-off models in project management aim to reduce the project completion time by putting extra resources on activity durations. The budget problem in discrete time/cost trade-off scheduling selects a time/cost mode for each activity so as to minimize the project completion time without exceeding the available budget. There may be alternative modes that solve the budget problem optimally and each solution may have a different total cost value. In this study we consider the budget problem and aim to find the minimum cost solution among the minimum project completion time solutions. We analyse the structure of the problem together with its linear programming relaxation and derive some mechanisms for reducing the problem size. We solve the reduced problem by branch and bound based optimization and heuristic algorithms. We find that our branch and bound algorithm finds optimal solutions for medium-sized problem instances in reasonable times and the heuristic algorithms produce high quality solutions very quickly.     

The sample average approximation method for empty container repositioning with uncertainties

One of the challenges faced by liner operators today is to effectively operate empty containers in order to meet demand and to reduce inefficiency in an uncertain environment. To incorporate uncertainties in the operations model, we formulate a two-stage stochastic programming model with random demand, supply, ship weight capacity, and ship space capacity. The objective of this model is to minimize the expected operational cost for Empty Container Repositioning (ECR). To solve the stochastic programs with a prohibitively large number of scenarios, the Sample Average Approximation (SAA) method is applied to approximate the expected cost function. To solve the SAA problem, we consider applying the scenario aggregation by combining the approximate solution of the individual scenario problem. Two heuristic algorithms based on the progressive hedging strategy are applied to solve the SAA problem. Numerical experiments are provided to show the good performance of the scenario-based method for the ECR problem with uncertainties.     

The minimum cost flow problem: A unifying approach to dual algorithms and a new tree-search algorithm

This paper is concerned with the minimum cost flow problem. It is shown that the class of dual algorithms which solve this problem consists of different variants of a common general algorithm. We develop a new variant which is, in fact, a new form of the ‘primal-dual algorithm’ and which has several interesting properties. It uses, explicitly only dual variables. The slope of the change in the (dual) objective is monotone. The bound on the maximum number of iterations to solve a problem with integral bounds on the flow is better than bounds for other algorithms. This paper is part of the author's doctoral dissertation submitted at Yale University.     

基于区间意见的非对称最小成本共识决策问题研究

针对已有共识模型大多是基于精确意见且未考虑决策者意见调整方向约束的不足,引入区间型意见,从最优化角度研究了非对称调整成本下的群决策共识模型。首先,基于区间意见构建了非对称最小成本共识模型。其次,考虑到决策者对不同共识水平的实际需求,通过引入软共识测度,提出了基于区间长度的决策者权重分配方法,据此构建了基于区间意见的非对称最小成本软共识模型。最后,通过政府与污染企业之间关于污染减排决策的实例验证了模型的有效性,并进行了灵敏度分析与比较研究。结果表明:(1)同精确值信息相比,区间意见能够缩减共识成本;(2)与对称成本共识模型相比,非对称调整成本的总共识成本不会随着单位调整成本的增加而无限增大。     

An introduction to dynamic generative networks: Minimum cost flow

What we are dealing with is a class of networks called dynamic generative network flows in which the flow commodity is dynamically generated at source nodes and dynamically consumed at sink nodes. As a basic assumption, the source nodes produce the flow according to time generative functions and the sink nodes absorb the flow according to time consumption functions. This paper tries to introduce these networks and formulate minimum cost dynamic flow problem for a pre-specified time horizon T. Finally, some simple, efficient approaches are developed to solve the dynamic problem, in the general form when the capacities and costs are time varying and some other special cases, as a minimum cost static flow problem.     

Finding a minimum cost path between a pair of nodes in a time-varying road network with a congestion charge

The minimum cost path problem in a time-varying road network is a complicated problem. The paper proposes two heuristic methods to solve the minimum cost path problem between a pair of nodes with a time-varying road network and a congestion charge. The heuristic methods are compared with an alternative exact method using real traffic information. Also, the heuristic methods are tested in a benchmark dataset and a London road network dataset. The heuristic methods can achieve good solutions in a reasonable running time.     

A dynamic programming approach for solving single-source uncapacitated concave minimum cost network flow problems

In this paper, we describe a dynamic programming approach to solve optimally the single-source uncapacitated minimum cost network flow problem with general concave costs. This class of problems is known to be NP-Hard and there is a scarcity of methods to solve them in their full generality. The algorithms previously developed critically depend on the type of cost functions considered and on the number of nonlinear arc costs. Here, a new dynamic programming approach that does not depend on any of these factors is proposed. Computational experiments were performed using randomly generated problems. The computational results reported for small and medium size problems indicate the effectiveness of the proposed approach.     

Branch-and-price algorithm for a multicast routing problem

This paper considers a multicast routing problem to find the minimum cost tree where the whole communication link delay on each path(route) of the tree is subject to a given delay allowance. The problem is formulated as an integer programming problem by using path variables. An associated problem reduction property is then characterised to reduce the solution space. Moreover, a polynomial time column generation procedure is exploited to solve the associated linear programming relaxation with such solution space reduced. Therefore a branch-and-price algorithm is derived to obtain the optimal integer solution(tree) for the problem. Computational results show that the algorithm can solve practical size problems in a reasonable length of time.     

基于网络流理论的非线性规划评价模型

针对既有的评价模型缺乏对评价结果保序性的讨论,以及难以有效处理缺失数据的问题,本文建立了一个新的评价模型用以解决以上问题。该模型建立在三个标准的基础上,这三个标准分别为“结果一致性”、“最小偏离性”和“最小差异性”,其为模型的建立提供了依据和理论基础;在已建立的非线性规划模型基础上,进行了模型的性质讨论,并将其归结为一类最小凸费用循环流的统一表述,这是解决模型的算法问题和揭示其蕴含的更为深刻的管理学意义的核心;最后,模型被用于一个示例分析和含有缺失数据的大规模数据集的实证分析,这些分析论证了该新模型的有效性。本文的模型提供了新的评价工具,扩展了运筹学和决策科学之间相互运用的案例,具有较好的保序性和处理缺失数据的能力,含有理论和实践的双重意义。     

Usability aware secret protection with minimum cost

In this paper we study a cybersecurity problem of protecting system’s secrets with multiple protections and a required security level, while minimizing the associated cost due to implementation/maintenance of these protections as well as the affected system usability. The target system is modeled as a discrete-event system (DES) in which there are a subset of marker states denoting the services/functions provided to regular users, a subset of secret states, and multiple subsets of protectable events with different security levels. We first introduce usability-aware cost levels for the protectable events, and then formulate the security problem as to ensure that every system trajectory that reaches a secret state contains a specified number of protectable events with at least a certain security level, and the highest usability-aware cost level of these events is minimum. We first provide a necessary and sufficient condition under which this security problem is solvable, and when this condition holds we propose an algorithm to solve the problem based on the supervisory control theory of DES. Moreover, we extend the problem to the case of heterogeneous secrets with different levels of importance, and develop an algorithm to solve this extended problem. Finally, we demonstrate the effectiveness of our solutions with a network security example.     

Interactive decision making for uncertain minimum spanning tree problems with total importance based on a risk-management approach

This paper deals with a minimum spanning tree problem where each edge cost includes uncertainty and importance measure. In risk management to avoid adverse impacts derived from uncertainty, a d-confidence interval for the total cost derived from robustness is introduced. Then, by maximizing the considerable region as well as minimizing the cost-importance ratio, a biobjective minimum spanning tree problem is proposed. Furthermore, in order to satisfy the objects of the decision maker and to solve the proposed model in mathematical programming, fuzzy goals for the objects are introduced as satisfaction functions, and an exact solution algorithm is developed using interactive decision making and deterministic equivalent transformations. Numerical examples are provided to compare our proposed model with some previous models.     

Optimal synchronization of two different in‐commensurate fractional‐order chaotic systems with fractional cost function

This article investigates the optimal synchronization of two different fractional‐order chaotic systems with two kinds of cost function. We use calculus of variations for minimizing cost function subject to synchronization error dynamics. We introduce optimal control problem to solve fractional Euler–Lagrange equations. Optimal control signal and minimum time of synchronization are obtained by proposed method. Examples show the optimal synchronization of two different systems with two different cost functions. First, we use an ordinary integer cost function then we use a fractional‐order cost function and comparing the results. Finally, we suggest a cost function which has the optimal solution of this problem, and we can extend this solution to solve other synchronization problems. © 2016 Wiley Periodicals, Inc. Complexity 21: 401–416, 2016     

An exact solution framework for the minimum cost dominating tree problem

The minimum cost dominating tree problem is a recently introduced NP-hard problem, which consists of finding a tree of minimal cost in a given graph, such that for every node of the graph, the node or one of its neighbours is in the tree. We present an exact solution framework combining a primal–dual heuristic with a branch-and-cut approach based on a transformation of the problem into a Steiner arborescence problem with an additional constraint. The effectiveness of our approach is evaluated on testbeds proposed in literature containing instances with up to 500 nodes. Our framework manages to solve all but four instances from literature to proven optimality within 3 h (most of them in a few seconds). We provide optimal solution values for 69 instances from literature for which the optimal solution was previously unknown.     

A multi-population hybrid biased random key genetic algorithm for hop-constrained trees in nonlinear cost flow networks

Genetic algorithms and other evolutionary algorithms have been successfully applied to solve constrained minimum spanning tree problems in a variety of communication network design problems. In this paper, we enlarge the application of these types of algorithms by presenting a multi-population hybrid genetic algorithm to another communication design problem. This new problem is modeled through a hop-constrained minimum spanning tree also exhibiting the characteristic of flows. All nodes, except for the root node, have a nonnegative flow requirement. In addition to the fixed charge costs, nonlinear flow dependent costs are also considered. This problem is an extension of the well know NP-hard hop-constrained Minimum Spanning Tree problem and we have termed it hop-constrained minimum cost flow spanning tree problem. The efficiency and effectiveness of the proposed method can be seen from the computational results reported.     

一类受时间约束的广义运输问题的求解

研究一类受时间约束的广义运输问题,将时间约束转化为容量约束,并将该问题转化为标准的最小费用流问题进而求解.该方法能够较快地找到最优运输方案.