ÉϺ£ÖÎÀíÂÛ̳µÚ389ÆÚ£¨Ôø²¨¸±½ÌÊÚ£¬ÃÀ¹úÆ¥×ȱ¤´óѧ£©

Ìâ    Ä¿£ºÖ÷´Ó²©ÞÄÄ£Ð͵ÄËã·¨¼°½øÕ¹

ÑÝ ½² ÈË£ºÔø²¨£¬ÃÀ¹úÆ¥×ȱ¤´óѧ¸±½ÌÊÚ

Ö÷ ³Ö ÈË£ºÁÖ¹ó»ª£¬Ð±¦GGÖÎÀíѧԺ½ÌÊÚ

ʱ    ¼ä£º2019Äê7ÔÂ2ÈÕ£¨Öܶþ£©£¬ÏÂÎç1:30-2:30

µØ    µã£ºÐ£±¾²¿¶«ÇøÖÎÀíѧԺ420ÊÒ

Ö÷°ìµ¥Ôª£ºÐ±¦GGÖÎÀíѧԺ¡¢Ð±¦GGÖÎÀíѧԺÇàÀÏ´óʦÁªÒê»á

Ñݽ²È˼ò½é£º

Ôø²¨²©Ê¿ÊÇÆ¥×ȱ¤´óѧ˹ÍúÉ­¹¤³ÌѧԺ¹¤Òµ¹¤³ÌϵºÍµçÆøÓëÍÆËã»ú¹¤³ÌϵµÄ¸±½ÌÊÚ¡£ Æä×êÑÐÁìÓòÊÇÓÅ»¯ÀíÂÛÓë²½Öè£¬³ö¸ñÊÇÀëÉ¢ºÍ¶à²ãÓÅ»¯£¬ÒÔ¼°ÆäÔÚ´óÊý¾Ý·ÖÎö£¬µçÁ¦£¬½»Í¨ÔËÊä£¬Ò½ÁƺÍÆäËûÐÅÏ¢ÍøÂçÎïÀíÈÚºÏϵͳÖеÄÀûÓá£×êÑгɾÍÒѱ»¿í·ºÀûÓÃÓÚÏÖʵϵͳ£¬ÒÔ½â¾öÑ¡Ö·¹æ»®£¬·ÀÎÀºÍÔËÓªÓÅ»¯µÈÎÊÌâ¡£³É¾Í°ä·¢ÓÚ¹ú¼Ê³ÛÃûÆÚ¿¯¡¶Mathematical Programming¡·, ¡¶INFORMS Journal of Computing¡·, ¡¶Operations Research Letters¡·, ¡¶IEEE Trans. on Automatic Control¡·,¡¶IEEE Trans. on Power Systems¡·ºÍ¡¶IEEE Trans. on Smart Grids¡·¡£

Ñݽ²ÄÚÈݼò½é£º

Bilevel optimization is widely used as decision support tools in power systems, transportation systems or security applications. Nevertheless, pessimistic bilevel optimization and bilevel mixed integer programs have been known as computationally difficult for a very long time. In this talk, we first review existing research and analyze the fundamental challenges. Then, we present some reformulation and decomposition strategies, along with their theoretical properties, to handle the complicated structure of pessimistic bilevel and bilevel mixed integer programs.  Finally, numerical results on practical and simulated instances are provided to demonstrate the computational advantages over existing methods.

Ó­½Ó¿í´óʦÉú²ÎÓ룡