International Conference Discrete Optimization and Operations Research Novosibirsk · June 24 - 28, 2013

 Abstract submission The size of abstract is limited to one page a rectangle 160 x 240 mm. Text must be prepared in LATEX,  font size - 12 pt  (documentstyle [12pt])   Each abstract must include the following:   1.      a title in CAPITAL letters; 2.      initials and author's name in small letter for each authors on a new line; 3.      an empty line before a main text; 4.      the main text;      5.      references; 6.      the author's information: first name, last name, affiliation, city, county, e-mail at the bottom of the page.     All the abstracts should be sent to the organizing committee by e-mail door@math.nsc.ru. Please, indicate a topic which you consider as the most appropriate one.

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 \documentclass [12pt,paper] {article} \usepackage[cp1251]{inputenc} \usepackage[english,russian]{babel} \textwidth 160mm \textheight 240mm \oddsidemargin -1mm \topmargin -10mm \pagestyle{empty} \begin{document} \begin{center} TITLE OF PAPER IN CAPITAL LETTERS\\[2mm] First name Last name \end{center} \ \\ In the paper we consider the Simple Plant Location Problem in the following formulation. Given sets $I=\{1,2, \dots, {\bf I} \}, \ J=\{1,2, \dots, {\bf J} \},$ vector $c_i \geq 0, i \in I$ and matrix $d_{ij} \geq 0, \ i \in I, \ j \in J.$ The objective is to find the subset $S \subseteq I,$ which minimizes a function $$F(S) =\sum\limits_{i \in S} c_i + \sum\limits_{j \in J} \min_{i \in S} d_{ij}$$ over all subsets of the set $I$. It is a well-known $NP$-hard discrete optimization problem [1]. We study behavior of Tabu Search algorithm [2] with different kinds of neighborhoods: complete neighborhood for the 2 Hamming distance and two randomized subneighborhoods with constant and adaptive sizes. We present a new search strategy which keeps an information about searching process and uses it for creating of a subneighborhoods (probabilistic antitabu rule). To find new starting point a history-sensitive randomized greedy algorithm is proposed. The algorithm is a modified Greedy Randomized Adaptive Search Procedure [3] which applies previous search information of Tabu Search algorithm. Comprehensive computational results for the Simple Plant Location Problem are discussed.\\[2mm] This research was supported by RFBR grant 11-01-00111. \begin{center} REFERENCES \end{center}\\ \ \\ 1. Martello S., Toth P. Knapsack Problems. Algorithms and Computer Implementations. Chichester: John Wiley \& Sons, 1990. 296 p. \\[2mm]   2. Drezner Z., Klamroth K., Schobel A., Wesolowsky G. The Weber Problem. In: Z.~Drezner, H.~Hamacher (Eds.) Facility Location. Applications and Theory. Springer, 2004. P. 1--36.\\[2mm]   3. Johnson~D.S., Papadimitriou C.H., Yannakakis M. How easy is local search? // J. of Computer and System Sciences. 1988. V. 37. P. 79--100.\\   \vfill\vfill \hrule \vspace{1mm} \noindent first name, last name, affiliation, mail, address, e-mail \end{document}

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