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The water level simulation for crane habitat optimization in Xianghai Nature Reserve
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作者 ZHANG Yanhong 1 ,DENG Wei 1 ,LIU Zhaoli 1 ,ZHANG Shuwen 1 ,ZHAI Jinliang 2 (1. Northeast Inst. of Geography and Agricultural Ecology, CAS, Changchun 130012, China 2. Bureau of Sciences and Technology for Resources and Environment, CAS, Beijing 100864, China) 《Journal of Geographical Sciences》 SCIE CSCD 2003年第2期187-194,共8页
The probability of crane living in reedy wetlands can reach 100%, at the same time, the area of reed, the water level and adjacent water area are main factors which control the crane'... The probability of crane living in reedy wetlands can reach 100%, at the same time, the area of reed, the water level and adjacent water area are main factors which control the crane's habitat selection. We all know that all these factors are spatially heterogeneous. For the Xianghai wetland safety and to protect the Xianghai wetland habitat of crane, this paper has mainly identified a solution to these problems. The wetland information is extracted from the TM images, which reflect the whole wetland landscape and are very important for both quantitative analysis of remote sensing observation of the earth system and positioning analysis in GIS database that is automatically extracted from DEM. The DEM for Xianghai characteristics of topography is created. On the basis of the GRID SUBMODULE, applying the GIS spatial overlay analysis, the relationship between the water level and the reed area below the water level and the rating distribution maps of reed area above water level is established. When the water level reaches the altitude of 165 m, the reed area, 981.2 ha is maximum, i.e., the water level of 165 m is the optimal. 展开更多
关键词 crane habitat optimization simulation of water level Xianghai National Nature Reserve CLC number:Q958.1
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AN ANT COLONY ALGORITHM FOR YARD TRUCK SCHEDULING AND YARD LOCATION ASSIGNMENT PROBLEMS WITH PRECEDENCE CONSTRAINTS 被引量:8
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作者 Zhaojie XUE Canrong ZHANG +1 位作者 Lixin MIAO Wei-Hua LIN 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2013年第1期21-37,共17页
This paper examines the yard truck scheduling,the yard location assignment for discharging containers,and the quay crane scheduling in container terminals.Taking into account the practical situation,we paid special at... This paper examines the yard truck scheduling,the yard location assignment for discharging containers,and the quay crane scheduling in container terminals.Taking into account the practical situation,we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations.A Mixed Integer Program(MIP) model is constructed,and a two-stage heuristic algorithm is proposed.In the first stage an Ant Colony Optimization(ACO) algorithm is employed to generate the yard location assignment for discharging containers.In the second stage,the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem,and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms. 展开更多
关键词 Container terminal yard truck scheduling yard location assignment quay crane scheduling precedence constraints ant colony optimization
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