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The vehicle travel time in time varying network not only depends on the distance between the nodes but also the time of day. In this paper, we developed a method satisfying first-in first-out property to deal with time period(s) crossing. The travel time can be deduced with it directly. The problem was formulated and a novel dynamic programming heuristics was presented to solve it. The algorithm can balance solution quality and computation time with parameter H. From the simulation results on 10 randomly generated cases, the new method can greatly improve the solution of nearest neighborhood algorithm within a very short time. When H=2, the average solution is improved 11%, while the computation time is 1.34s. It also can be improved 17% within less than 2s with H=3. [ABSTRACT FROM AUTHOR]

Urban logistics storage facilities have the nature of network based on commercial trend and demand. In this paper, we first analyze the necessity and feasibility to change the independent decision- making model into interact decision-making model from the perspective of the value stream. Then, we establish a network equilibrium model with the competition of the multi-level members of the supply chain logistics which include the logistics storage facilities and the supplier or demander of the commodity using the variational inequalities theory. Besides, we also get conditions which can make the system reach equilibrium and offer the economic interpretation and the solving algorithm. Finally, we validate th model and present its decision-making applications by solving the specific examples. It shows that storage facilities layer and layer of the commodity's supply and demand always influence and restrict each other, and the improvement of the facilities efficiency, the migration of the sites and other behaviors like these may lead to the regular change of the market pattern, the quantities of commodity, the prices and the social welfare. [ABSTRACT FROM AUTHOR]

While designing the issue of the discount card, stores need to strictly analyze the effect of factors such as the issue price and discount rate on the consumer's behavior. Using the theory of on-line algorithms and competitive analysis, this paper studied the on-line problem how consumers make decisions between two discount cards which are issued at the same time. On the one hand, the optimal deterministic strategy and its competitive ratio were obtained; on the other hand, a randomized strategy was constructed and an upper bound for the optimal randomized competitive ratio was obtained, and moreover, a lower bound for the optimal randomized competitive ratio was proved by Yao's Lemma. Thanks to numerical examples, the effect of the factors on the on-line strategies and their competitive ratios was analyzed. The results may instruct the stores in determining the issue price and discount rate of the discount card. [ABSTRACT FROM AUTHOR]

In this paper, the way of coupling in emergency has been studied in tackling issue on disaster derivative coupling in the GERTS network. Three kinds of notions about coupling have been put forward by having designed the logic structure of co-coupling nodes based on GERTS network, having defined co-coupling algorithm, and having studied the optimal evaluation of co-coupling algorithm parameters in different forms. This research provides the method for co-coupling analysis in the scenario of unconventional incidents and provides new outlook for the decision-making of "scenario-reaction" in unconventional incidents. [ABSTRACT FROM AUTHOR]

Base on the integration of urban transportation, the paper studied the dispatching problem of bus vehicles associating with urban rail transit to transport passengers during the large-scale events. For the operation characteristics of dedicated-line and over-line, optimizing models of independent dispatching and centralized dispatching were developed separately while whose algorithms were provided. An application of the models to the case of Expo 2010 Shanghai shows that the optimizing models are practical and useful for reducing the cost of bus transit operation and improving the efficiency of the intermodal transportation system composed of urban rail transit and bus transit. [ABSTRACT FROM AUTHOR]

The train dispatching problem is one of the key train operation problems. A wide range of studies have been focused on this problem in recent years and yielded great achievements. However, most of the studies are based on deterministic disturbance information and few attention was paid to stochastic information. In this paper, the single-track train dispatching problem under stochastic capacity breakdowns was addressed. At first, the application of two-stage stochastic programming with recourse technique was presented. By extending the two-stage model, a conceptual model of multi-stage recursive train dispatching process was proposed, and also the corresponding complexity was discussed. After that, a semi-continuous multi-stage models was proposed. To address the mathematical models, branch-and-bound solution procedures were presented and comprehensive numerical experiments were conducted to illustrate the performance of the model and algorithms with compassion to priority rule-based algorithm which is commonly used in real-world train dispatching practice. Experimental results show that, compared to the priority rule-based method, the semi-continuous multi-stage model and two-stage model can reduce the expected total train delay by 34% and 4% respectively. [ABSTRACT FROM AUTHOR]

This paper deals with the human resource scheduling problem of multiple IT projects. According to its specific requirements on time and personnel, the duration of the whole development process can be divided into equal-length time slices. Based on the relations among activities and personnel in a certain time slice, the search tree of personnel scheduling solutions can be constructed. By connecting all the search trees sequentially from all the time slices, the solution tree for the whole problem can be generated and all the solutions can be listed. Then, based on the average of advanced completion rate and the variance of advanced completion rate, the optimal solution can be found. By adding heuristic rules to this algorithm, the searching space can contract rapidly, and the searching efficiency can be enhanced greatly. In view of the particularities of this algorithm, it can be applied to many generalized resource scheduling problems that possess similar conditions with the problem described above. After applying this algorithm to a mock example, some regular patterns emerged, showing the potential that further heuristic rules can be extracted. [ABSTRACT FROM AUTHOR]

A credit scoring method for a large problem not only achieves a certain accuracy but also its speed, interpretability, simplicity and other performance are also very important. In this paper, a novel method called an improved SVM learning algorithm based on three-variable working set (ISVMTV) is presented. This algorithm is derived by solving a series of the QP problems with only three points and the corresponding relaxation subproblems are solved analytically so that the proposed method approaches to the optimal solution more quickly. The proposed method is introduced to credit scoring and three datasets from UCI machine learning datasets are selected to demonstrate the method's competitive performance. Moreover, ISVM-TV shows a superior performance in saving the computational cost and improving classification accuracy. [ABSTRACT FROM AUTHOR]

There are some features existing in the procurement auction, for example huge number, multi-species, profit differences and irrational evaluation index systems. To solve these problems, this paper proposed the following model. Firstly, after vendors finishing biddings, we adopted self-organizing map (SOM) and bundle algorithm to simplify the vendors' biddings. This can entrance the goods' similarity within the bundles, balance the competition among suppliers, and reduce the complexity of the Winner Decision Problem (WDP) algorithm. Then, using the CUR model in Data Envelopment Analysis (DEA), we conducted a relative evaluation of simplified biddings and determined the final winner supplier. This can solve the problem of the uncorrelated property assumption and artificial weights in traditional evaluation index system method. Our model provides a new idea for WDP in the procurement auction. It has a good practicability. [ABSTRACT FROM AUTHOR]

Identification of protein complexes in large interaction networks is crucial to understand principles of cellular organization and predict protein functions, which is one of the most important issues in the post-genomic era. Each protein might subordinate multiple protein complexes in the real protein-protein interaction networks. Identifying overlapping protein complexes front protein-protein interaction networks is a considerable research topic. As an effective algorithm on identifying overlapping module structures, clique percolation method (CPM) has a wide range of application in social networks and biological networks. However, CPM algorithm is recognition accuracy rate lowly and unfit to identifying protein complexes with middling scale when it applied in PPI networks. In this paper, an algorithm called CPM-DR for identifying protein complexes based on clique percolation and distance restriction is proposed. In this algorithm, the scale of protein complex is restricted by distance constraint to conquest the drawbacks in CPM. The experiment results show that CPM-DR algorithm can identify many well known protein complexes more effectively, precisely and comprehensively. [ABSTRACT FROM AUTHOR]

Many algorithms of solving vehicle routing problem with time windows have processes of customs insertion detection which hold weak efficiency. In this paper, the time difference concept is presented and then insertion detection method based time difference (TDIDM) is proposed. The computing performance of TDIDM is also compared with the existing insertion detection. Computational results on the benchmark problems show that the TDIDM is faster than the existing insertion detection. [ABSTRACT FROM AUTHOR]

In the actual process of locating facility, the decision-maker always faces the following constraints: they must determine where to locate the initial facility (or facilities) when the number of edges to be served is uncertain, and, the constructed facilities can not be removed when the new facility is built. The existed models and algorithms are always pointed to a static facility location process, but here we need a dynamic facility location model with above constraints. Considered the online vertex covering problem in this paper, we present a structural lower bound which does not need any complexity assumption, and prove that the analysis is tight by giving a competitive algorithm as well as competitive ratio proof for a restricted version of the online vertex covering problem, and we also obtain that this algorithm is optimal if we are permitted to use non-polynomial time. [ABSTRACT FROM AUTHOR]

The paper took different regions and regional industries as initial water right allocation objects in the basin; the compound system for basin initial water right allocation was given; the connotation and objective of the compound system was analyzed; and the bi-level optimization model of the compound system optimization was established to allocate water right of different regions and regional industries, and eliminate the water conflict and contradiction among regions, embody the fairness and efficiency of different regions' water right, prevent different industries from the vicious water right competition, optimize comprehensive benefit of society-economy-ecology in the basin. Meanwhile, according to the interactive decision-making theory, the model algorithm was put forward. The case analysis verified the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Considering that the global optimal solutions often locate on or near the boundary of the feasible region for many constrained optimization problems, a novel genetic algorithm was proposed in this paper. The basic idea of the proposed algorithm was to put feasible solutions and infeasible solutions into two different containers respectively. Subsequently, a new designed crossover operator (named inward-outward crossover operator) was used to a feasible solution and a infeasible solution, then a line search along a potential decent direction was used to improve the offspring so as to find a good solution on or near to the boundary of feasible region. By this search procedure, the possibility for obtaining the globally optimal solution is obviously enhanced, and similarly, the convergent speed is also strengthened. The "particle swarm mutation" inherited the advantages of Particle Swarm Optimization (PSO) algorithm and searched for the potential solution along the direction of the best current particle and the direction of the best individual of the whole swarm in the past. Selection operator retained a constant rate of infeasible solutions. Numerical results indicate that the proposed algorithm can be efficient to get global optimal solutions or near to them in smaller population and less iteration times. [ABSTRACT FROM AUTHOR]

In this paper, an insertion heuristic based on time difference is introduced. Based on this insertion heuristic, a genetic algorithm for pickup and delivery problem with time windows (PDPTW) is proposed. Comparing with other genetic algorithms, our algorithm holds two characters: 1) Cross operation as well as R1- mutation operation and R2- mutation operation are based on time difference insertion heuristic; 2) Non-generation search strategy is applied to the algorithm. Our algorithm is subject to a comparative test on the benchmark problem sets that comprise 56 PDPTW instances. The results show that the solution quality is better than the reported algorithm whose objective function is the same as ours. [ABSTRACT FROM AUTHOR]