An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designe...An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designed. In the QCs scheduling phase of the algorithm, a search was performed to determine a good QC unloading operation order. For each QC unloading operation order generated during the QC's scheduling phase, another search was run to obtain a good yard trailer routing for the given QC's unloading order. Using this information, the time required for the operation was estimated, then the time of return to availability of the units was fed back to the QC scheduler. Numerical tests show that the two-phase Tabu Search algorithm searches the solution space efficiently, decreases the empty distance yard trailers must travel, decreases the number of trailers needed, and thereby reduces time and costs and improves the integration and reliability of container terminal operation systems.展开更多
A steam power plant can work as a dual purpose plant for simultaneous production of steam and elec-trical power. In this paper we seek the optimum integration of a steam power plant as a source and a site utility sys-...A steam power plant can work as a dual purpose plant for simultaneous production of steam and elec-trical power. In this paper we seek the optimum integration of a steam power plant as a source and a site utility sys-tem as a sink of steam and power. Estimation for the cogeneration potential prior to the design of a central utility system for site utility systems is vital to the targets for site fuel demand as well as heat and power production. In this regard, a new cogeneration targeting procedure is proposed for integration of a steam power plant and a site utility consisting of a process plant. The new methodology seeks the optimal integration based on a new cogenera-tion targeting scheme. In addition, a modified site utility grand composite curve(SUGCC) diagram is proposed and compared to the original SUGCC. A gas fired steam power plant and a process site utility is considered in a case study. The applicability of the developed procedure is tested against other design methods(STAR? and Thermoflex software) through a case study. The proposed method gives comparable results, and the targeting method is used for optimal integration of steam levels. Identifying optimal conditions of steam levels for integration is important in the design of utility systems, as the selection of steam levels in a steam power plant and site utility for integration greatly influences the potential for cogeneration and energy recovery. The integration of steam levels of the steam power plant and the site utility system in the case study demonstrates the usefulness of the method for reducing the overall energy consumption for the site.展开更多
Abstract Accurate forecast of future container throughput of a port is very important for its con struction, upgrading, and operation management. This study proposes a transfer forecasting model guided by discrete par...Abstract Accurate forecast of future container throughput of a port is very important for its con struction, upgrading, and operation management. This study proposes a transfer forecasting model guided by discrete particle swarm optimization algorithm （TF-DPSO）. It firstly transfers some related time series in source domain to assist in modeling the target time series by transfer learning technique, and then constructs the forecasting model by a pattern matching method called analog complexing. Finally, the discrete particle swarm optimization algorithm is introduced to find the optimal match between the two important parameters in TF-DPSO. The container throughput time series of two im portant ports in China, Shanghai Port and Ningbo Port are used for empirical analysis, and the results show the effectiveness of the proposed model.展开更多
文摘An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designed. In the QCs scheduling phase of the algorithm, a search was performed to determine a good QC unloading operation order. For each QC unloading operation order generated during the QC's scheduling phase, another search was run to obtain a good yard trailer routing for the given QC's unloading order. Using this information, the time required for the operation was estimated, then the time of return to availability of the units was fed back to the QC scheduler. Numerical tests show that the two-phase Tabu Search algorithm searches the solution space efficiently, decreases the empty distance yard trailers must travel, decreases the number of trailers needed, and thereby reduces time and costs and improves the integration and reliability of container terminal operation systems.
文摘A steam power plant can work as a dual purpose plant for simultaneous production of steam and elec-trical power. In this paper we seek the optimum integration of a steam power plant as a source and a site utility sys-tem as a sink of steam and power. Estimation for the cogeneration potential prior to the design of a central utility system for site utility systems is vital to the targets for site fuel demand as well as heat and power production. In this regard, a new cogeneration targeting procedure is proposed for integration of a steam power plant and a site utility consisting of a process plant. The new methodology seeks the optimal integration based on a new cogenera-tion targeting scheme. In addition, a modified site utility grand composite curve(SUGCC) diagram is proposed and compared to the original SUGCC. A gas fired steam power plant and a process site utility is considered in a case study. The applicability of the developed procedure is tested against other design methods(STAR? and Thermoflex software) through a case study. The proposed method gives comparable results, and the targeting method is used for optimal integration of steam levels. Identifying optimal conditions of steam levels for integration is important in the design of utility systems, as the selection of steam levels in a steam power plant and site utility for integration greatly influences the potential for cogeneration and energy recovery. The integration of steam levels of the steam power plant and the site utility system in the case study demonstrates the usefulness of the method for reducing the overall energy consumption for the site.
基金partly supported by the Natural Science Foundation of China under Grant Nos.71101100 and 70731160635New Teachers’Fund for Doctor Stations,Ministry of Education under Grant No.20110181120047+5 种基金Excellent Youth Fund of Sichuan University under Grant No.2013SCU04A08China Postdoctoral Science Foundation under Grant Nos.2011M500418,2012T50148 and 2013M530753Frontier and Cross-innovation Foundation of Sichuan University under Grant No.skqy201352Soft Science Foundation of Sichuan Province under Grant No.2013ZR0016Humanities and Social Sciences Youth Foundation of the Ministry of Education of China under Grant No.11YJC870028Selfdetermined Research Funds of CCNU from the Colleges’ Basic Research and Operation of MOE under Grant No.CCNU13F030
文摘Abstract Accurate forecast of future container throughput of a port is very important for its con struction, upgrading, and operation management. This study proposes a transfer forecasting model guided by discrete particle swarm optimization algorithm （TF-DPSO）. It firstly transfers some related time series in source domain to assist in modeling the target time series by transfer learning technique, and then constructs the forecasting model by a pattern matching method called analog complexing. Finally, the discrete particle swarm optimization algorithm is introduced to find the optimal match between the two important parameters in TF-DPSO. The container throughput time series of two im portant ports in China, Shanghai Port and Ningbo Port are used for empirical analysis, and the results show the effectiveness of the proposed model.
