The Tokugawa clan was a powerful daimyō family of Japan. They nominally descended from Emperor Seiwa and were a branch of the Minamoto clan by the Nitta clan; the early history of this clan remains a mystery. Members of the clan ruled Japan as shōguns from 1603 to 1867. Minamoto no Yoshishige, grandson of Minamoto no Yoshiie, was the first to take the name of Nitta, he sided with his cousin Minamoto no Yoritomo against the Taira clan and accompanied him to Kamakura. Nitta Yoshisue, 4th son of Yoshishige, took the name of that place, their provincial history book did not mention Nitta clan. The nominal originator of the Matsudaira clan was Matsudaira Chikauji, a poor Buddhist monk, he descended from Nitta Yoshisue in the 8th generation and witnessed the ruin of the Nitta in their war against the Ashikaga. He was adopted by his wife's family, their provincial history book claimed. Because this place is said to have been reclaimed by Nobumori Ariwara, one theory holds that Matsudaira clan was related to Ariwara no Narihira.
Matsudaira Nobumitsu, son of Chikauji, was in charge of Okazaki Castle, strengthened the authority of his family in the Mikawa province. Nobumitsu's great-great-grandson Matsudaira Kiyoyasu was assassinated. In 1567, Tokugawa Ieyasu - known as Matsudaira Motonobu - grandson of Kiyoyasu, was recognized by Emperor Ōgimachi as a descendant of Seiwa Genji; the clan rose to power at the end of the Sengoku period, to the end of the Edo period they ruled Japan as shōguns. There were fifteen Tokugawa shōguns, their dominance was so strong that some history books use the term "Tokugawa era" instead of "Edo period". Their principal family shrine is the Tōshō-gū in Nikkō, principal temple is at Kan'ei-ji in Tokyo. Heirlooms of the clan are administered by the Tokugawa Memorial Foundation. After the death of Ieyasu, in 1636, the heads of the gosanke bore the Tokugawa surname, so did the three additional branches, known as the gosankyō: the Tayasu and Shimizu family, after the ascension of Tokugawa Yoshimune.
Once a shōgun died without a living heir, both the heads of gosanke and gosankyō had priority to succeed his position. Many daimyōs descended from cadet branches of the clan, remained the surname Matsudaira. Members of the Tokugawa clan intermarried with the Imperial family. On November 9, 1867, Tokugawa Yoshinobu, the 15th and the last shōgun of Tokugawa, tendered his resignation to Emperor Meiji and formally stepped down ten days returning governing power to the Emperor, marking the end of the ruling power of the Tokugawa shogunate. By the next year, Tokugawa Iesato was chosen as the heir to Yoshinobu as the head of Tokugawa clan; the 1946 Constitution of Japan abolished the kazoku and the noble titles, making Iesato's son, Iemasa Tokugawa, no longer a prince. Iemasa had a son Iehide, who died young, so he was succeeded by one of his grandsons, Tsunenari. Tsunenari is the second son of Toyoko and Ichirō Matsudaira, he is a patrilineal descendant of Tokugawa Yorifusa, the youngest son of Tokugawa Ieyasu.
The Tokugawa's clan crest, known in Japanese as a "mon", the "triple hollyhock", has been a recognized icon in Japan, symbolizing in equal parts the Tokugawa clan and the last shogunate. The crest derives from the Kamo clan, which legendarily descended from Yatagarasu. Matsudaira village was located in Aichi Prefecture. Although Emperor Go-Yōzei offered a new crest, Ieyasu continued to use the crest, not related to Minamoto clan. In jidaigeki, the crest is shown to locate the story in the Edo period, and in works set in during the Meiji Restoration movement, the crest is used to show the bearer's allegiance to the shogunate—as opposed to the royalists, whose cause is symbolized by the Imperial throne's chrysanthemum crest. Compare with the red and white rose iconography of English Wars of the Roses, as imagined by Walter Scott earlier in the 19th century, in Anne of Geierstein. Tokugawa Ieyasu Tokugawa Hidetada Matsudaira Nobuyasu Kamehime Yūki Hideyasu Matsudaira Ietada Matsudaira Tadaaki Matsudaira Tadanao Tokuhime Tokugawa Komatsu Tokugawa Iemitsu Senhime Tokugawa Mitsukuni Tokugawa Iesada Tsunenari Tokugawa Muneyoshi Tokugawa Abe clan of Mikawa Province Gosankyō Baba clan Honda clan Ii clan Ishikawa clan Ōkubo clan Sakai clan Toda clan Tokugawa memorial foundation
The berth allocation problem is a NP-complete problem in operations research, regarding the allocation of berth space for vessels in container terminals. Vessels arrive over time and the terminal operator needs to assign them to berths to be served as soon as possible. Different factors affect the time assignment of each vessel. Among models found in the literature, there are four most observed cases: discrete vs. continuous berthing space, static vs. dynamic vessel arrivals, static vs. dynamic vessel handling times, variable vessel arrivals. In the discrete problem, the quay is viewed as a finite set of berths. In the continuous problem, vessels can berth anywhere along the quay and the majority of research deals with the former case. In the static arrival problem all vessels are at the port whereas in the dynamic only a portion of the vessels to be scheduled are present; the majority of the published research in berth scheduling considers the latter case. In the static handling time problem, vessel handling times are considered as input, whereas in the dynamic they are decision variables.
In the last case, the vessel arrival times are considered as variables and are optimized. Technical restrictions such as berthing draft and inter-vessel and end-berth clearance distance are further assumptions that have been adopted in some of the studies dealing with the berth allocation problem, bringing the problem formulation closer to real world conditions. Introducing technical restrictions to existing berth allocation models is rather straightforward and it may increase the complexity of the problem but simplify the use of metaheuristics; some of the most notable objectives addressed in the literature are: Minimization of vessel total service times, Minimization of early and delayed departures, Optimization of vessel arrival times, Optimization of emissions and fuel consumption. Problems have been formulated as multi-objective as well as single and bi-level. List of NP-complete problems Quay crane scheduling Container terminals Golias, Mihalis M.. "The berth allocation problem: Optimizing vessel arrival time".
Maritime Economics & Logistics. 11: 358–377. Doi:10.1057/mel.2009.12. Guan, Yongpei. "The berth allocation problem: models and solution methods". OR Spectrum. 26: 75–92. Doi:10.1007/s00291-003-0140-8. Pinedo, Michael L.. Scheduling: Theory and Systems. New York: Springer. ISBN 978-0-387-78934-7. Briano C, Briano E. Bruzzone A. G. Revetria R. Models for Support Maritime Logistics: A Case Study for Improving Terminal Planning. 19th European Conference on Modeling and Simulation. June 1–4, 2005 Riga, Latvia Brown G. G. Cormican K. J. Lawphongpanich S. and Widdis, D. B. Optimizing submarine berthing with a persistence incentive. Naval Research Logistics. Vol. 44, 1997, pp. 301–318. Brown G. G. Lawphongpanich S. and Thurman K. P. Optimizing vessel berthing. Naval Research Logistics, Vol. 41, 1994, pp. 1–15. Canonaco, P. Legato, P. Mazza, R. Musmanno, R. A queuing network model for the management of berth crane operations. Computers and Operations Research, Vol. 35, 2008, pp. 2432–2446. Cordeau, J.-F. Laporte, G. Legato, P. Moccia, L.
Models and tabu search heuristics for the berth-allocation problem. Transportation Science. Vol. 39, 2005, pp. 526–538. Dai, J. Liu, W. Moorthy, R. and Teo, C.-P. Berth Allocation Planning Optimization in Container Terminals. Http://www.bschool.nus.edu.sg/staff/bizteocp/berthplanningjuly2004.pdf%5B%5D Dragović, B. Park N-K, Radmilović Z. Ship-berth link performance evaluation: simulation and analytical approaches. Maritime Policy & Management, Vol. 33, 2006, pp. 281–299. Edmond E. D. and Maggs R. P. 1978. How useful are queue models in port investment decisions for container berths? Journal of the Operational Research Society, Vol. 29, 1978, pp. 741–750. Golias M. M. A bi-objective berth allocation formulation to account for vessel handling time uncertainty. Journal of Maritime Economics and Logistics. 13:419-441 Golias M. M. Haralambides H. E. Berth scheduling with variable cost functions. Journal of Maritime Economics and Logistics. 13:174-189 Golias M. M. Boilé M. Theofanis S. Efstathiou C; the berth scheduling problem: Maximizing berth productivity and minimizing fuel consumption and emissions production.
Transportation Research Record: Journal of the Transportation Research Board, Marine Transportation and Port Operations, 2166, 20-27. Golias M. M. Boilé M. Theofanis S; the discrete berth scheduling problem: Towards a unified mathematical formulation. Transportation Research Record: Journal of the Transportation Research Board, Freight Transportation Modeling and Logistics, 2168, 1-8. Golias M. M. Boilé M. Theofanis S. Taboada A. H. A multi-objective decision and analysis approach for the berth scheduling problem. International Journal of Information Technology Project Management, 1, 54-73. Saharidis G. K. D. Golias M. M. Boilé M. Theofanis S. Ierapetritou M; the berth scheduling problem with customer differentiation: A new methodological approach based on hierarchical optimization. International Journal of Advanced Manufacturing Technology, 46, 377-393. Golias M. M. Boilé M. Theofanis S. Service time based customer differentiation berth scheduling. Transportation Research Part E: Logistics and Transportation Review, 45, 878-892.
Golias M. M. Boilé M. Theofanis S. A lambda-optimization based heuristic for the discrete berth scheduling problem. Transportation Research Pt. C, 18, 794-806. Golias M. M. Boilé M. Theofanis S. An adaptive time window partitioning based algorithm fo
CCDI Group is a large global architecture and engineering consulting firm that provides integrated professional services for urban construction and development headquartered in Shanghai, People's Republic of China. Its business units cover broad industry sectors with diverse specialized expertise. CCDI operates cross-regionally with offices in Shanghai, Shenzhen, Sydney, New York City and Suzhou with branches and representative offices in Chongqing and twenty other cities in China. Over the years, CCDI has established strong client relationships with most major developers and city governments. Founded in 1994, CCDI is a subsidiary of the owned construction and engineering firm, China State Construction Engineering Corporation. From 1994 to 2002, CCDI's work focused on the south China market, working on residential projects and public facilities such as exhibition halls and sports arenas. But, in 2003, CCDI and a consortium of other firms, won an architectural competition with the innovative design of the Beijing National Aquatics Center, constructed for the 2008 Summer Olympics.
Since CCDI has experienced substantial growth. In 2013, CCDI acquired PTW Architects, a owned Australian-based architectural firm with expanding business interests in China and Southeast Asia. CCDI employs more than thousand architects, planners, project managers as well as design and management consultants to offer various critical services of strategic planning, development and operations related to buildings and industries. Beijing National Aquatics Center Beijing Olympic Green Tennis Center National Tennis Center Ping'an Financial Center Shanghai Rockbund Reconstruction Project Jinan Olympic Center Hangzhou Olympic Center Dameisha Vanke Center Tencent Headquarters Alibaba Headquarters Baidu Headquarters Harbin West Railway Station Beijing Kunlun Apartment Shenzhen City Crossing Complex Tianjin Cruise Terminal Shanghai International Tourism Resorts CCDI Architects: Designing China's Future by Victoria Mulgrave