International Conference

Discrete Optimization and Operations Research

Novosibirsk · June 24 - 28, 2013





Scientific School for Young Researchers

Program Committee



Plenary speakers 


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 Please, indicate a topic which you consider as the most appropriate one.


Abstract submission                










































Example of abstract


\documentclass [12pt,paper] {article}
\textwidth 160mm \textheight 240mm \oddsidemargin -1mm \topmargin -10mm \pagestyle{empty}



First name Last name


\ \\
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





© Институт математики им. С.Л. Соболева СО РАН
Последняя редакция 07.12.2012