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81.
This paper presents a new optimization algorithm called GHS + LEM, which is based on the Global-best Harmony Search algorithm (GHS) and techniques from the learnable evolution models (LEM) to improve convergence and accuracy of the algorithm. The performance of the algorithm is evaluated with fifteen optimization functions commonly used by the optimization community. In addition, the results obtained are compared against the original Harmony Search algorithm, the Improved Harmony Search algorithm and the Global-best Harmony Search algorithm. The assessment shows that the proposed algorithm (GHS + LEM) improves the accuracy of the results obtained in relation to the other options, producing better results in most situations, but more specifically in problems with high dimensionality, where it offers a faster convergence with fewer iterations. 相似文献
82.
Iterated greedy search is a simple and effective metaheuristic for combinatorial problems. Its flexibility enables the incorporation of components from other metaheuristics with the aim of obtaining effective and powerful hybrid approaches. We propose a tabu-enhanced destruction mechanism for iterated greedy search that records the last removed objects and avoids removing them again in subsequent iterations. The aim is to provide a more diversified and successful search process with regards to the standard destruction mechanism, which selects the solution components for removal completely at random. 相似文献
83.
Emilio Carrizosa Alba V. Olivares-Nadal Pepa Ramírez-Cobo 《European Journal of Operational Research》2013
Most time series forecasting methods assume the series has no missing values. When missing values exist, interpolation methods, while filling in the blanks, may substantially modify the statistical pattern of the data, since critical features such as moments and autocorrelations are not necessarily preserved. 相似文献
84.
85.
86.
Tabu search for non-permutation flowshop scheduling problem with minimizing total tardiness 总被引:1,自引:0,他引:1
This paper deals with the non-permutation flowshop problem which means that the job sequences are allowed to be different on machines. The objective function is minimizing the total tardiness. Firstly, three mixed-integer linear programming (MILP) models for non-permutation flowshop problems are described, and then are analyzed and assessed their relative effectiveness. Secondly, two Tabu search based algorithms, denoted by LH1 and LH2, are proposed to solve the complicated non-permutation flowshop problems. The algorithms are constructed on specific neighborhood structures which enable the searching method effective. Finally, the performance is evaluated against Taillard’s famous benchmark. Computational experiments show that the proposed algorithms, LH1 and LH2, are significantly superior to the L_TS algorithm. And the percentages of improved permutation flowshop instances by LH1 and LH2 algorithms are about 87.8% and 98.3% with respect to total tardiness, respectively. The non-permutation schedules also have achieved significant improvement in four different scenarios of due dates. Consequently, average percentage improvement (API) is 14.52% for flowshop problems with low tardiness factors. It is evident that exploring non-permutation schedule is effective and necessary for low tardiness factors. 相似文献
87.
Jhieh-Yu Shyng How-Ming Shieh Gwo-Hshiung Tzeng Shu-Huei Hsieh 《European Journal of Operational Research》2010
This study proposes a novel Forward Search and Backward Trace (FSBT) technique based on Rough Set Theory to improve data analysis and extend the scope of observations made from sample data to solve personal investment portfolio problems. Rough Set Theory mathematically classifies data into class sets. The class set with the most objects may generate one decision rule. The rules generated from RST are rough and fragmented, that are very difficult to interpret the information. An empirical case is used to generate more than 85 rules by the RST method in comparison with FSBT method which only generated 14 rules. This result can show our proposed method is better than traditional RST method based on class sets that contain the most objects. Much of human knowledge is described in natural language. It is a very important thing to convert information from computer databases into normal human language. Sample data taken from features with the same backgrounds are used to compile different portfolios that investment companies and investment advisors can employ to satisfy the investor’ needs. The method not only can provide decision-making rules, but also can offer alternative strategies for better data analysis. We believe that the FSBT technique can be fully applied in research on investment marketing. 相似文献
88.
In the Attractive Traveling Salesman Problem the vertex set is partitioned into facility vertices and customer vertices. A maximum profit tour must be constructed on a subset of the facility vertices. Profit is computed through an attraction function: every visited facility vertex attracts a portion of the profit from the customer vertices based on the distance between the facility and customer vertices, and the attractiveness of the facility vertex. A gravity model is used for computing the profit attraction. The problem is formulated as an integer non-linear program. A linearization is proposed and strengthened through the introduction of valid inequalities, and a branch-and-cut algorithm is developed. A tabu search algorithm is also implemented. Computational results are reported. 相似文献
89.
Ivan Žulj Sergej Kramer Michael Schneider 《European Journal of Operational Research》2018,264(2):653-664
Given a set of customer orders and a routing policy, the goal of the order-batching problem?(OBP) is to group customer orders to picking orders (batches) such that the total length of all tours through a rectangular warehouse is minimized. Because order picking is considered the most labor-intensive process in warehousing, effectively batching customer orders can result in considerable savings. The OBP is NP-hard if the number of orders per batch is greater than two, and the exact solution methods proposed in the literature are not able to consistently solve larger instances. To address larger instances, we develop a metaheuristic hybrid based on adaptive large neighborhood search and tabu search, called ALNS/TS. In numerical studies, we conduct an extensive comparison of ALNS/TS to all previously published OBP methods that have used standard benchmark sets to investigate their performance. ALNS/TS outperforms all comparison methods with respect to both average solution quality and run-time. Compared to the state-of-the-art, ALNS/TS shows the clearest advantages on the larger instances of the existing benchmark sets, which assume a higher number of customer orders and higher capacities of the picking device. Finally, ALNS/TS is able to solve newly generated large-scale instances with up to 600 customer orders and six articles per customer order with reasonable run-times and convincing scaling behavior and robustness. 相似文献
90.
In this paper we consider some generalizations of the vertex coloring problem, where distance constraints are imposed between adjacent vertices (bandwidth coloring problem) and each vertex has to be colored with more than one color (bandwidth multicoloring problem). We propose an evolutionary metaheuristic approach for the first problem, combining an effective tabu search algorithm with population management procedures. The approach can be applied to the second problem as well, after a simple transformation. Computational results on instances from the literature show that the overall algorithm is able to produce high quality solutions in a reasonable amount of time, outperforming the most effective algorithms proposed for the bandwidth coloring problem, and improving the best known solution of many instances of the bandwidth multicoloring problem. 相似文献