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.     

A heuristic solution technique to attain the minimal total cost bounds of transporting a homogeneous product with varying demands and supplies

Transportation of a product from multi-source to multi-destination with minimal total transportation cost plays an important role in logistics and supply chain management. Researchers have given considerable attention in minimizing this cost with fixed supply and demand quantities. However, these quantities may vary within a certain range in a period due to the variation of the global economy. So, the concerned parties might be more interested in finding the lower and the upper bounds of the minimal total costs with varying supplies and demands within their respective ranges for proper decision making. This type of transportation problem has received attention of only one researcher, who formulated the problem and solved it by LINGO. We demonstrate that this method fails to obtain the correct upper bound solution always. Then we extend this model to include the inventory costs during transportation and at destinations, as they are interrelated factors. The number of choices of supplies and demands within their respective ranges increases enormously as the number of suppliers and buyers increases. In such a situation, although the lower bound solution can be obtained methodologically, determination of the upper bound solution becomes an NP hard problem. Here we carry out theoretical analyses on developing the lower and the upper bound heuristic solution techniques to the extended model. A comparative study on solutions of small size numerical problems shows promising performance of the current upper bound technique. Another comparative study on results of numerical problems demonstrates the effect of inclusion of the inventory costs.     

Two dimensional load balancing

We consider a bi-criteria parallel machine scheduling problem in which the first objective is the minimization of the makespan of the schedule and the second objective is the minimization of the maximum machine cost. Since the problem is strongly NP-hard, we propose a fast heuristic and derive its worst-case performance bound.     

Low-cost one-step fabrication of superhydrophobic surface on Al alloy

A stable superhydrophobicity on aluminum alloy has been rendered by a low-cost one-step method, simply immersing the substrates in a solution containing hydrochloric acid and fatty acid molecules. The formation mechanism of such a surface was proposed by SEM morphology and EDS results. The resulting surface shows superhydrophobicity and low adhesion. This low cost and facile process provides a real feasible avenue for large-scale production of superhydrophobic surfaces.     

Design of progressively censored group sampling plans for Weibull distributions: An optimization problem

Optimization algorithms provides efficient solutions to many statistical problems. Essentially, the design of sampling plans for lot acceptance purposes is an optimization problem with several constraints, usually related to the quality levels required by the producer and the consumer. An optimal acceptance sampling plan is developed in this paper for the Weibull distribution with unknown scale parameter. The proposed plan combines grouping of items, sudden death testing in each group and progressive group removals, and its decision criterion is based on the uniformly most powerful life test. A mixed integer programming problem is first solved for determining the minimum number of failures required and the corresponding acceptance constant. The optimal number of groups is then obtained by minimizing a balanced estimation of the expected test cost. Excellent approximately optimal solutions are also provided in closed-forms. The sampling plan is considerably flexible and allows to save experimental time and cost. In general, our methodology achieves solutions that are quite robust to small variations in the Weibull shape parameter. A numerical example about a manufacturing process of gyroscopes is included for illustration.     

分配网络的一个最小费用流算法

分配网络流广泛应用于解决水源、电力的调度及工厂的产品运输、分配、合成等问题.本文提出一个分配网络流的最小费用流算法.     

基于博弈论的促销商广告微分方程决策分析

将供应链看作为一个整体,他们需要经手一种新型时髦的商品或季节性商品,促销商作为供应链中一个独立的部门,专门负责季节性商品的促销工作,在供应链管理体系中处于一个核心地位,制造商与零售商则专门按照促销商提供的信息,专职从事制造与销售工作.以此假设为前提,分别建立了三类广告促销的微分方程对策模型,研究广告对季节性商品销售量的影响,以及在促进供应链整体绩效中的作用,进而确定合理的广告强度和时间.最后,在假设广告收益函数与成本函数服从均匀分布的情况下,由建立的广告决策模型得出了恰当的广告使用费用和时间.并由此得到了一些对决策有重要参考价值的结论.     

基于SFA的中国保险业X-效率研究

本文运用随机前沿法(SFA)对2001-2006年中国29家保险公司的成本/利润效率状况和演进趋势进行了研究。实证结果表明,中国保险公司的成本效率要高于利润效率,并出现了成本效率减速提高与利润效率稳定上升并存的发展态势;无论在成本或利润效率方面,国有保险公司都低于其他所有制保险公司,但在演进过程中与其他所有制公司的差距正在逐步缩小。同时,财产保险公司的平均成本效率要高于人寿保险公司,而人寿保险公司的平均利润效率要高于财产保险公司.     

Study on the model of an insurer’s solvency ratio in Markov-modulated Brownian markets

In this paper the insurer’s solvency ratio model with or without jump diffusion process in the presence of financial distress cost is constructed, where an insurer’s solvency ratio is characterized by a Markov-modulated dynamics. By Girsanov’s theorem and the option pricing formula, the expected present value of shareholders’ terminal payoff is provided.     

Study on the optimization of the water Cherenkov detector array of the LHAASO project for surveying VHE gamma ray sources

It is prpopsed that a water Cherenkov detector array, LHAASO-WCDA, is to be built at Shangri-la, Yunnan Province, China. As one of the major components of the LHAASO project, the main purpose of it is to survey the northern sky for gamma ray sources in the energy range of 100 GeV-30 TeV. In order to design the water Cherenkov array efficiently to economize the budget, a Monte Carlo simulation is carried out. With the help of the simulation, the cost performance of different configurations of the array are obtained and compared with each other, serving as a guide for the more detailed design of the experiment in the next step.