Variable Neighborhood Search for the File Transfer Scheduling Problem

ACM Computing Classification System (1998): I.2.8, G.1.6.In this paper a file transfer scheduling problem is considered. This problem is known to be NP-hard, and thus provides a challenging area for metaheuristics. A variable neighborhood search algorithm is designed for the transfer scheduling of files between various nodes of a network, by which the overall transfer times are to be minimized. Optimality of VNS solutions on smaller size instances has been verified by total enumeration. For several larger instances optimality follows from reaching the elementary lower bound of a problem

Modifications of the variable neighborhood search method and their applications to solving the file transfer scheduling problem

Metoda promenljivih okolina se u praksi pokazala vrlo uspesnom za resavanje pro- blema diskretne i kontinualne optimizacije. Glavna ideja ove metode je sistematska promena okolina unutar prostora resenja u potrazi za boljim resenjem. Za opti- mizaciju funkcija vise promenljivih koriste se metode koje nalaze lokalni minimum polazeci od zadate pocetne tacke. U slucaju kada kontinualna funkcija ima mnostvo lokalnih minimuma, nalazenje globalnog minimuma obicno nije lak zadatak jer najcesce dostignuti lokalni minimumi nisu optimalni. Kod uobicajenih implementa- cija sa ogranicenim okolinama razlicitih dijametara iz proizvoljne tacke nije moguce dostici sve tacke prostora resenja. Zbog toga je strategija koriscenja konacnog broja ogranicenih okolina primenjiva na probleme kod kojih optimalno resenje pripada nekom unapred poznatom ogranicenom podskupu skupa IRn. U cilju prevazilazenja pomenutog ogranicenja predlozena je nova varijanta meto- de, Gausovska metoda promenljivih okolina. Umesto denisanja niza razlicitih okolina iz kojih ce se birati slucajna tacka, u ovoj metodi se sve okoline pokla- paju sa celim prostorom resenja, a slucajne tacke se generisu koriscenjem razlicitih slucajnih raspodela Gausovog tipa. Na ovaj nacin se i tacke na vecem rastojanju od tekuce tacke mogu teorijski dostici mada sa manjom verovatnocom. U osnovnoj verziji metode promenljivih okolina neophodno je unapred denisati sistem okolina, njihov ukupan broj i velicinu, kao i tip raspodele koja ce se koristiti za odabir slucajne tacke unutar tih okolina. Gausovska metoda promenljivih okolina za razliku od osnovne verzije ima manje parametara jer su sve okoline teorijski iste velicine (jednake celom prostoru pretrage) i imaju jedinstvenu jednoparametarsku familiju raspodela Gausovu raspodelu slucajnih brojeva sa promenljivom dispe- rzijom. Problem raspored-ivanja prenosa datoteka (File transfer scheduling problem - FTSP) je optimizacioni problem koji svoju primenu pronalazi u mnogim oblastima poput telekomunikacijama, LAN i WAN mrezama, raspored-ivanju u okviru MIMD (multiple instruction multiple data) racunarskih sistema i dr. Spada u klasu NP teskih problema za cije resavanje se uobicajeno koriste heuristicke metode. Za- datak optimizacije FTSP sastoji se u trazenju odgovarajuceg rasporeda pojedinacnih prenosa datoteka, tj. vremenskih trenutaka kada ce svaka datoteka zapoceti svoj prenos tako da duzina vremenskog intervala od trenutka kada prva datoteka zapocne prenos do trenutka u kom poslednja zavrsi bude sto manja...The Variable neighborhood search method proved to be very successful for solving discrete and continuous optimization problems. The basic idea is a systematic change of neighborhood structures in search for the better solution. For optimiza- tion of multiple variable functions, methods for obtaining the local minimum starting from certain initial point are used. In case when the continuous function has many local minima, nding the global minimum is usually not an easy task since the obta- ined local minima in most cases are not optimal. In typical implementations with bounded neighborhoods of various diameters it is not possible, from arbitrary point, to reach all points in solution space. Consequently, the strategy of using the nite number of neighborhoods is suitable for problems with solutions belonging to some known bounded subset of IRn. In order to overcome the previously mentioned limitation the new variant of the method is proposed, Gaussian Variable neighborhood search method. Instead of dening the sequence of dierent neighborhoods from which the random point will be chosen, all neighborhoods coincide with the whole solution space, but with die- rent probability distributions of Gaussian type. With this approach, from arbitrary point another more distant point is theoretically reachable, although with smaller probability. In basic version of Variable neighborhood search method one must dene in advance the neighborhood structure system, their number and size, as well as the type of random distribution to be used for obtaining the random point from it. Gaussian Variable neighborhood search method has less parameters since all the neighborhoods are theoretically the same (equal to the solution space), and uses only one distribution family - Gaussian multivariate distribution with variable dispersion. File transfer scheduling problem (FTSP) is an optimization problem widely appli- cable to many areas such as Wide Area computer Networks (WAN), Local Area Ne- tworks (LAN), telecommunications, multiprocessor scheduling in a MIMD machines, task assignments in companies, etc. As it belongs to the NP-hard class of problems, heuristic methods are usually used for solving this kind of problems. The problem is to minimize the overall time needed to transfer all les to their destinations for a given collection of various sized les in a computer network, i.e. to nd the le transfer schedule with minimal length..

The traveling salesman problem: The spectral radius and the length of an optimal tour

We consider the symmetric traveling salesman problem (TSP) with instances represented by complete graphs with distances between cities as edge weights. Computational experiments with randomly generated instances on 50 and 100 vertices with the uniform distribution of integer edge weights in interval [1, 100] show that there exists a correlation between the sequences of the spectral radii of the distance matrices and the lengths of optimal tours obtained by the well known TSP solver Concorde. In this paper we give a partial theoretical explanation of this correlation.Bulletin de l'Académie serbe des sciences. Classe des sciences mathématiques et naturelles. Sciences mathématiques. . - 43 , 151 (2018

Diversity of Fraxinus ornus from Serbia and Montenegro as revealed by RAPDs

PCR-RAPD markers revealed individual variation in F. ornus. A total of 122 fragments were amplified using 7 primers and of these 97 fragments were polymorphic. The percentage of polymorphic loci was between 53.3% and 74.6% with an average of 63.1%. The mean gene diversity for all populations was 0.30 and the mean Shannon's index was 0.44. Of the total genetic variation 87% was intra-population whilst 13% was inter-population. The Mantel test revealed significant correlation between genetic and geographical distance matrice. Results herein represent the first use of molecular genetic (DNA) markers to characterize genetic variation in F. ornus populations. The partition of total genetic variance indicates a relatively restricted population differentiation as expected in outcrossing species. Present and future information on genetic structure and variability in F. ornus needs to be incorporated into strategies for the preservation of genetic resources of tree species.U radu su korišćeni PCR-RAPD markeri radi procene individualnih varijacija kod vrste F. ornus. Ukupno 122 fragmenta je amplificirano korišćenjem 7 prajmera, i među njima je bilo 97 polimorfnih fragmenata. Procenat polimorfnih lokusa se kretao između 53.3% i 74.6% sa prosečnom vrednošću od 63.1%. Srednji diverzitet gena za sve ispitivane populacije je iznosio 0.30, dok je srednji Shannon's index imao vrednost 0.44. Od totalne genetičke varijabilnosti 87% pripada intra-populacionoj varijabilnost, a 13% inter-populacionoj. Mantel test je pokazao značajne korelacije između matrica genetičke i geografske distance. Rezultati ovog rada predstavljaju prvu upotrebu molekularno genetičkih (DNA) markera u cilju određivanja genetičke varijabilnosti populacija F. ornus. Odnosi unutar ukupne genetičke varijabilnosti ukazuju na relativno ograničenu populacionu diferencijacije u odnosu na vrednosti koje su očekivane kod stranooplodne vrste. Na osnovu ovih kao i budućih informacija koje se odnose na genetičku strukturu i varijabilnost vrste F. ornus potrebno je kreirati strategije za očuvanje genetičkih resursa drvenastih vrsta.Projekat ministarstva br. 17301

Sortiment i uzgojnih oblika kao uticajni faktori energetskog potencijala rezidbenih ostataka iz voćarsko-vinogradarske proizvodnje

Biomass resulting from agricultural production represents potential which can be used in multiple ways. The expansion of fruit-growing and viticulture in Serbia in recent years contributes to an even larger quantities of pruning residues. Long-standing practice of destroying and burning of the pruning residues hardly changed, but the energy and environmental indicators point to the importance of proper exploitation of this biomass. The aim of this study is to show the quantity and energy value of tree branches from fruitgrowing and viticulture as fuel, as well as the influence of different fruit types and vine varieties and training systems on energy potential. The apple sort Idared has the highest values of thermal power per mass unit (19.853 kJ kg-1) and the peach sort Redheven has the highest value of thermal power per area unit (974,78 GJ ha-1). The grapevine lags behind other sorts of fruit have significantly less thermal power per unit, but the calorific value per unit mass ranges within the limits of 17,300 ± 100 kJ kg-1.Biomasa iz poljoprivredne proizvodnje, predstavlja nedovoljno iskorišćen potencijal. Ekspanzija voćarske i vinogradarske proizvodnje u Srbiji, poslednjih godina, doprinosi stvaranju ogromnih količina rezidbenih ostataka. Dugogodišnja praksa uništavanja i spaljivanja rezidbenih ostataka se polako menja, ali energetski i ekološki pokazatelji ukazuju na značaj pravilnog korišćenja ove biomase. Cilj ovog rada je da prikaže količine i energetsku vrednost rezidbenih ostataka iz voćarske i vinogradarske proizvodnje, kao i uticaj različitih voćnih vrsta, sorti vinove loze i uzgojnih oblika na energetski potencijal. Najveću toplotnu moć po jedinici mase ustanovljeno je kod jabuke sorte Ajdared (19.853 kJ kg-1), a najveću toplotnu moć po jedinici površine ostvarena je kod breskve, sorte Redheven (974,78 GJ ha-1). Vinova loza u odnosu na voćne vrste ima značajno manju toplotnu moć po jedinici površine, dok se toplotna moć po jedinici mase kreće oko 17.300 ± 100 kJ kg-1

Mehanizovani postupci pripreme i obrade komposta od rezidbenih ostataka voćarsko-vinogradarske proizvodnje

This paper is part of research about the effects of mechanized process of fragmentation of pruning residues on the composting process. Compost, as a form of organic fertilizer, requires specific production treatment depending on the form of biomass. Pruning residues from fruit-vine production can be translated into quality organic fertilizer, but it is necessary to coordinate mechanized treatment of biomass and technology of composting process with microbiological processes for organic matter decomposition.Rad predstavlja deo istraživanja uticaja mehanizovanih procesa usitnjavanja rezidbenih ostataka na proces kompostiranja. Kompost kao vid organskog đubriva zahteva specifičan tretman proizvodnje u zavisnosti od vida biomase. Rezidbeni ostaci iz voćarsko-vinogradarske proizvodnje se mogu prevesti u kvalitetno organsko đubrivo, ali je potrebno uskladiti mehanizovane procese obrade biomase i tehnologiju kompostiranja sa mikrobiološkim procesima razlaganja organske materije

Diversity of Fraxinus ornus from Serbia and Montenegro as revealed by RAPDs

PCR-RAPD markers revealed individual variation in F. ornus. A total of 122 fragments were amplified using 7 primers and of these 97 fragments were polymorphic. The percentage of polymorphic loci was between 53.3% and 74.6% with an average of 63.1%. The mean gene diversity for all populations was 0.30 and the mean Shannon's index was 0.44. Of the total genetic variation 87% was intra-population whilst 13% was inter-population. The Mantel test revealed significant correlation between genetic and geographical distance matrice. Results herein represent the first use of molecular genetic (DNA) markers to characterize genetic variation in F. ornus populations. The partition of total genetic variance indicates a relatively restricted population differentiation as expected in outcrossing species. Present and future information on genetic structure and variability in F. ornus needs to be incorporated into strategies for the preservation of genetic resources of tree species.U radu su korišćeni PCR-RAPD markeri radi procene individualnih varijacija kod vrste F. ornus. Ukupno 122 fragmenta je amplificirano korišćenjem 7 prajmera, i među njima je bilo 97 polimorfnih fragmenata. Procenat polimorfnih lokusa se kretao između 53.3% i 74.6% sa prosečnom vrednošću od 63.1%. Srednji diverzitet gena za sve ispitivane populacije je iznosio 0.30, dok je srednji Shannon's index imao vrednost 0.44. Od totalne genetičke varijabilnosti 87% pripada intra-populacionoj varijabilnost, a 13% inter-populacionoj. Mantel test je pokazao značajne korelacije između matrica genetičke i geografske distance. Rezultati ovog rada predstavljaju prvu upotrebu molekularno genetičkih (DNA) markera u cilju određivanja genetičke varijabilnosti populacija F. ornus. Odnosi unutar ukupne genetičke varijabilnosti ukazuju na relativno ograničenu populacionu diferencijacije u odnosu na vrednosti koje su očekivane kod stranooplodne vrste. Na osnovu ovih kao i budućih informacija koje se odnose na genetičku strukturu i varijabilnost vrste F. ornus potrebno je kreirati strategije za očuvanje genetičkih resursa drvenastih vrsta.Projekat ministarstva br. 17301

Gaussian variable neighborhood search for the file transfer scheduling problem

This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results. [Projekat Ministarstava nauke Republike Srbije, br. 174010

Modifications of the variable neighborhood search method and their applications to solving the file transfer scheduling problem

Metoda promenljivih okolina se u praksi pokazala vrlo uspesnom za resavanje pro- blema diskretne i kontinualne optimizacije. Glavna ideja ove metode je sistematska promena okolina unutar prostora resenja u potrazi za boljim resenjem. Za opti- mizaciju funkcija vise promenljivih koriste se metode koje nalaze lokalni minimum polazeci od zadate pocetne tacke. U slucaju kada kontinualna funkcija ima mnostvo lokalnih minimuma, nalazenje globalnog minimuma obicno nije lak zadatak jer najcesce dostignuti lokalni minimumi nisu optimalni. Kod uobicajenih implementa- cija sa ogranicenim okolinama razlicitih dijametara iz proizvoljne tacke nije moguce dostici sve tacke prostora resenja. Zbog toga je strategija koriscenja konacnog broja ogranicenih okolina primenjiva na probleme kod kojih optimalno resenje pripada nekom unapred poznatom ogranicenom podskupu skupa IRn. U cilju prevazilazenja pomenutog ogranicenja predlozena je nova varijanta meto- de, Gausovska metoda promenljivih okolina. Umesto denisanja niza razlicitih okolina iz kojih ce se birati slucajna tacka, u ovoj metodi se sve okoline pokla- paju sa celim prostorom resenja, a slucajne tacke se generisu koriscenjem razlicitih slucajnih raspodela Gausovog tipa. Na ovaj nacin se i tacke na vecem rastojanju od tekuce tacke mogu teorijski dostici mada sa manjom verovatnocom. U osnovnoj verziji metode promenljivih okolina neophodno je unapred denisati sistem okolina, njihov ukupan broj i velicinu, kao i tip raspodele koja ce se koristiti za odabir slucajne tacke unutar tih okolina. Gausovska metoda promenljivih okolina za razliku od osnovne verzije ima manje parametara jer su sve okoline teorijski iste velicine (jednake celom prostoru pretrage) i imaju jedinstvenu jednoparametarsku familiju raspodela Gausovu raspodelu slucajnih brojeva sa promenljivom dispe- rzijom. Problem raspored-ivanja prenosa datoteka (File transfer scheduling problem - FTSP) je optimizacioni problem koji svoju primenu pronalazi u mnogim oblastima poput telekomunikacijama, LAN i WAN mrezama, raspored-ivanju u okviru MIMD (multiple instruction multiple data) racunarskih sistema i dr. Spada u klasu NP teskih problema za cije resavanje se uobicajeno koriste heuristicke metode. Za- datak optimizacije FTSP sastoji se u trazenju odgovarajuceg rasporeda pojedinacnih prenosa datoteka, tj. vremenskih trenutaka kada ce svaka datoteka zapoceti svoj prenos tako da duzina vremenskog intervala od trenutka kada prva datoteka zapocne prenos do trenutka u kom poslednja zavrsi bude sto manja...The Variable neighborhood search method proved to be very successful for solving discrete and continuous optimization problems. The basic idea is a systematic change of neighborhood structures in search for the better solution. For optimiza- tion of multiple variable functions, methods for obtaining the local minimum starting from certain initial point are used. In case when the continuous function has many local minima, nding the global minimum is usually not an easy task since the obta- ined local minima in most cases are not optimal. In typical implementations with bounded neighborhoods of various diameters it is not possible, from arbitrary point, to reach all points in solution space. Consequently, the strategy of using the nite number of neighborhoods is suitable for problems with solutions belonging to some known bounded subset of IRn. In order to overcome the previously mentioned limitation the new variant of the method is proposed, Gaussian Variable neighborhood search method. Instead of dening the sequence of dierent neighborhoods from which the random point will be chosen, all neighborhoods coincide with the whole solution space, but with die- rent probability distributions of Gaussian type. With this approach, from arbitrary point another more distant point is theoretically reachable, although with smaller probability. In basic version of Variable neighborhood search method one must dene in advance the neighborhood structure system, their number and size, as well as the type of random distribution to be used for obtaining the random point from it. Gaussian Variable neighborhood search method has less parameters since all the neighborhoods are theoretically the same (equal to the solution space), and uses only one distribution family - Gaussian multivariate distribution with variable dispersion. File transfer scheduling problem (FTSP) is an optimization problem widely appli- cable to many areas such as Wide Area computer Networks (WAN), Local Area Ne- tworks (LAN), telecommunications, multiprocessor scheduling in a MIMD machines, task assignments in companies, etc. As it belongs to the NP-hard class of problems, heuristic methods are usually used for solving this kind of problems. The problem is to minimize the overall time needed to transfer all les to their destinations for a given collection of various sized les in a computer network, i.e. to nd the le transfer schedule with minimal length..

Modifications of the variable neighborhood search method and their applications to solving the file transfer scheduling problem

Metoda promenljivih okolina se u praksi pokazala vrlo uspesnom za resavanje pro- blema diskretne i kontinualne optimizacije. Glavna ideja ove metode je sistematska promena okolina unutar prostora resenja u potrazi za boljim resenjem. Za opti- mizaciju funkcija vise promenljivih koriste se metode koje nalaze lokalni minimum polazeci od zadate pocetne tacke. U slucaju kada kontinualna funkcija ima mnostvo lokalnih minimuma, nalazenje globalnog minimuma obicno nije lak zadatak jer najcesce dostignuti lokalni minimumi nisu optimalni. Kod uobicajenih implementa- cija sa ogranicenim okolinama razlicitih dijametara iz proizvoljne tacke nije moguce dostici sve tacke prostora resenja. Zbog toga je strategija koriscenja konacnog broja ogranicenih okolina primenjiva na probleme kod kojih optimalno resenje pripada nekom unapred poznatom ogranicenom podskupu skupa IRn. U cilju prevazilazenja pomenutog ogranicenja predlozena je nova varijanta meto- de, Gausovska metoda promenljivih okolina. Umesto denisanja niza razlicitih okolina iz kojih ce se birati slucajna tacka, u ovoj metodi se sve okoline pokla- paju sa celim prostorom resenja, a slucajne tacke se generisu koriscenjem razlicitih slucajnih raspodela Gausovog tipa. Na ovaj nacin se i tacke na vecem rastojanju od tekuce tacke mogu teorijski dostici mada sa manjom verovatnocom. U osnovnoj verziji metode promenljivih okolina neophodno je unapred denisati sistem okolina, njihov ukupan broj i velicinu, kao i tip raspodele koja ce se koristiti za odabir slucajne tacke unutar tih okolina. Gausovska metoda promenljivih okolina za razliku od osnovne verzije ima manje parametara jer su sve okoline teorijski iste velicine (jednake celom prostoru pretrage) i imaju jedinstvenu jednoparametarsku familiju raspodela Gausovu raspodelu slucajnih brojeva sa promenljivom dispe- rzijom. Problem raspored-ivanja prenosa datoteka (File transfer scheduling problem - FTSP) je optimizacioni problem koji svoju primenu pronalazi u mnogim oblastima poput telekomunikacijama, LAN i WAN mrezama, raspored-ivanju u okviru MIMD (multiple instruction multiple data) racunarskih sistema i dr. Spada u klasu NP teskih problema za cije resavanje se uobicajeno koriste heuristicke metode. Za- datak optimizacije FTSP sastoji se u trazenju odgovarajuceg rasporeda pojedinacnih prenosa datoteka, tj. vremenskih trenutaka kada ce svaka datoteka zapoceti svoj prenos tako da duzina vremenskog intervala od trenutka kada prva datoteka zapocne prenos do trenutka u kom poslednja zavrsi bude sto manja...The Variable neighborhood search method proved to be very successful for solving discrete and continuous optimization problems. The basic idea is a systematic change of neighborhood structures in search for the better solution. For optimiza- tion of multiple variable functions, methods for obtaining the local minimum starting from certain initial point are used. In case when the continuous function has many local minima, nding the global minimum is usually not an easy task since the obta- ined local minima in most cases are not optimal. In typical implementations with bounded neighborhoods of various diameters it is not possible, from arbitrary point, to reach all points in solution space. Consequently, the strategy of using the nite number of neighborhoods is suitable for problems with solutions belonging to some known bounded subset of IRn. In order to overcome the previously mentioned limitation the new variant of the method is proposed, Gaussian Variable neighborhood search method. Instead of dening the sequence of dierent neighborhoods from which the random point will be chosen, all neighborhoods coincide with the whole solution space, but with die- rent probability distributions of Gaussian type. With this approach, from arbitrary point another more distant point is theoretically reachable, although with smaller probability. In basic version of Variable neighborhood search method one must dene in advance the neighborhood structure system, their number and size, as well as the type of random distribution to be used for obtaining the random point from it. Gaussian Variable neighborhood search method has less parameters since all the neighborhoods are theoretically the same (equal to the solution space), and uses only one distribution family - Gaussian multivariate distribution with variable dispersion. File transfer scheduling problem (FTSP) is an optimization problem widely appli- cable to many areas such as Wide Area computer Networks (WAN), Local Area Ne- tworks (LAN), telecommunications, multiprocessor scheduling in a MIMD machines, task assignments in companies, etc. As it belongs to the NP-hard class of problems, heuristic methods are usually used for solving this kind of problems. The problem is to minimize the overall time needed to transfer all les to their destinations for a given collection of various sized les in a computer network, i.e. to nd the le transfer schedule with minimal length..