Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880192
A. Khutoretskii, S. Bredikhin
We present a greedy 0.5-approximation algorithm for allocation indivisible jobs in a multiprocessor system. The algorithm uses an ordering of processors according to the non-decreasing of size, and two orderings of items: in nonincreasing utility order and in nonincreasing order of the utility/ size ratio. These orderings create two lexicographic orderings on the set $ Itimes J$ (here I is the set of jobs and J is the set of processors). Based on these lexicographic orderings, the algorithm creates an admissible allocation by looking through the pairs $(i, j) in Itimes J$ in the corresponding order and allocating the job i to processor j if this job is not allocated yet and can be allocated to processor j. The algorithm chooses the best of the two obtained solutions. This algorithm is 0.5-approximate and has running time $O(mn)$ (without sorting), where m and n are the sizes of the sets I and J correspondingly.
{"title":"A Greedy Algorithm for Jobs Allocation in a Multiprocessor System","authors":"A. Khutoretskii, S. Bredikhin","doi":"10.1109/OPCS.2019.8880192","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880192","url":null,"abstract":"We present a greedy 0.5-approximation algorithm for allocation indivisible jobs in a multiprocessor system. The algorithm uses an ordering of processors according to the non-decreasing of size, and two orderings of items: in nonincreasing utility order and in nonincreasing order of the utility/ size ratio. These orderings create two lexicographic orderings on the set $ Itimes J$ (here I is the set of jobs and J is the set of processors). Based on these lexicographic orderings, the algorithm creates an admissible allocation by looking through the pairs $(i, j) in Itimes J$ in the corresponding order and allocating the job i to processor j if this job is not allocated yet and can be allocated to processor j. The algorithm chooses the best of the two obtained solutions. This algorithm is 0.5-approximate and has running time $O(mn)$ (without sorting), where m and n are the sizes of the sets I and J correspondingly.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132685747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880208
N. Mamatov, A. Samijonov, Z. Yuldashev, N. Niyozmatova
The solution of a set of applied problems is reduced to the solution of problems of fractional-linear discrete optimization. Including economic, medical tasks, tasks of placing objects, etc. The article proposes the fastest method for solving an unconditional discrete-fractional-linear optimization problem, determines the optimality conditions of the selected solution. Based on these conditions of optimality, a new method and algorithm are proposed.
{"title":"Discrete Optimization of Linear Fractional Functionals","authors":"N. Mamatov, A. Samijonov, Z. Yuldashev, N. Niyozmatova","doi":"10.1109/OPCS.2019.8880208","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880208","url":null,"abstract":"The solution of a set of applied problems is reduced to the solution of problems of fractional-linear discrete optimization. Including economic, medical tasks, tasks of placing objects, etc. The article proposes the fastest method for solving an unconditional discrete-fractional-linear optimization problem, determines the optimality conditions of the selected solution. Based on these conditions of optimality, a new method and algorithm are proposed.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130029865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880200
M. Khairetdinov, D. Karavaev, A. Yakimenko, A. Morozov
In the paper approach to reconstruct velocity model of elastic medium in the problem of monitoring cavity zones of underground nuclear explosions is considered. Main problem is to find location and to define characteristic size and shape of cavity object in isotropic elastic media. Cavity is presented by oval shape object formed in the result of an underground nuclear explosion. To recognize cavity on seismic field snapshots and to reconstruct velocity model geometry neural network was used. Neural network was trained with set of 2D results of full seismic field simulation for different models. We performed tests on developed algorithm in area of 3D finite difference simulation with hollow cavity inclusion described by elastic parameters with zero values. The advantages and results of using neural network approach are described.
{"title":"Approaches to Recognize Cavity Inclusions in Elastic Media in Problem of Monitoring Test Sites","authors":"M. Khairetdinov, D. Karavaev, A. Yakimenko, A. Morozov","doi":"10.1109/OPCS.2019.8880200","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880200","url":null,"abstract":"In the paper approach to reconstruct velocity model of elastic medium in the problem of monitoring cavity zones of underground nuclear explosions is considered. Main problem is to find location and to define characteristic size and shape of cavity object in isotropic elastic media. Cavity is presented by oval shape object formed in the result of an underground nuclear explosion. To recognize cavity on seismic field snapshots and to reconstruct velocity model geometry neural network was used. Neural network was trained with set of 2D results of full seismic field simulation for different models. We performed tests on developed algorithm in area of 3D finite difference simulation with hollow cavity inclusion described by elastic parameters with zero values. The advantages and results of using neural network approach are described.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114783838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880247
O. Monakhov, E. Monakhova
The solution of the optimization problem of constructing regular networks (graphs) that are optimal over the average diameter is investigated. Two classes of parametrically described regular networks are investigated - circulant and hypercirculant networks. An approach using bioinspired algorithms for the automatic synthesis of parametric descriptions of optimal circulant and hypercirculant networks has been developed. A comparative analysis of five different bioinspired algorithms (genetic algorithm, differential evolution, particle swarm optimization, algorithm of artificial bee colony and firefly algorithm) was carried out using them to solve this optimization problem. For the found optimal networks structural characteristics such as diameter, average diameter, bandwidth, reliability were obtained, and these networks were compared according to these characteristics.
{"title":"A Comparative Analysis of Bioinspired Algorithms for Solving the Problem of Optimization of Circulant and Hypercirculant Networks","authors":"O. Monakhov, E. Monakhova","doi":"10.1109/OPCS.2019.8880247","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880247","url":null,"abstract":"The solution of the optimization problem of constructing regular networks (graphs) that are optimal over the average diameter is investigated. Two classes of parametrically described regular networks are investigated - circulant and hypercirculant networks. An approach using bioinspired algorithms for the automatic synthesis of parametric descriptions of optimal circulant and hypercirculant networks has been developed. A comparative analysis of five different bioinspired algorithms (genetic algorithm, differential evolution, particle swarm optimization, algorithm of artificial bee colony and firefly algorithm) was carried out using them to solve this optimization problem. For the found optimal networks structural characteristics such as diameter, average diameter, bandwidth, reliability were obtained, and these networks were compared according to these characteristics.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116159281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880148
K. A. Chernykh, V. Servakh
The problem of minimizing the weighted average time to complete jobs on a single machine is considered. The release dates of jobs are fixed. The preemptions are possible. The processing times of all jobs are equal. The computational complexity this problem is unknown. An approach to the analysis of the structure of the optimal solutions is proposed. Polynomial algorithms are described for some important classes.
{"title":"Combinatorial Structure of Optimal Solutions to the Problem of a Single Machine with Preemption","authors":"K. A. Chernykh, V. Servakh","doi":"10.1109/OPCS.2019.8880148","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880148","url":null,"abstract":"The problem of minimizing the weighted average time to complete jobs on a single machine is considered. The release dates of jobs are fixed. The preemptions are possible. The processing times of all jobs are equal. The computational complexity this problem is unknown. An approach to the analysis of the structure of the optimal solutions is proposed. Polynomial algorithms are described for some important classes.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122169808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/opcs.2019.8880201
{"title":"OPCS 2019 Cover Page","authors":"","doi":"10.1109/opcs.2019.8880201","DOIUrl":"https://doi.org/10.1109/opcs.2019.8880201","url":null,"abstract":"","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123839349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880260
M. Pagano
Self-similarity plays an important role, at least over a finite number of scales, in natural phenomena as well as complex technology-related systems. One of the most surprising examples is provided by telecommunication networks, where the shift from circuit-switching to packet-switching has led to a deep change in the stochastic nature of traffic flows. The concepts of self-similarity, long range dependence and heavy tails, widely used in traffic modelling, are closely related among them and strongly influence network performance. Hence, this overview, based on the research and teaching experience of the author, presents in a simple way the main definitions, focusing on their physical interpretation, and highlights the relevance of these properties in network dimensioning.
{"title":"Self-similarity and Long Range Dependence in teletraffic","authors":"M. Pagano","doi":"10.1109/OPCS.2019.8880260","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880260","url":null,"abstract":"Self-similarity plays an important role, at least over a finite number of scales, in natural phenomena as well as complex technology-related systems. One of the most surprising examples is provided by telecommunication networks, where the shift from circuit-switching to packet-switching has led to a deep change in the stochastic nature of traffic flows. The concepts of self-similarity, long range dependence and heavy tails, widely used in traffic modelling, are closely related among them and strongly influence network performance. Hence, this overview, based on the research and teaching experience of the author, presents in a simple way the main definitions, focusing on their physical interpretation, and highlights the relevance of these properties in network dimensioning.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125902635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880191
A. Rodionov
The problem of fast estimating of reliability polynomial’ coefficients is considered in the paper in the case of all-terminal reliability (probability of a graph being connected). Obtaining lower and upper bounds for each coefficient of a reliability polynomial in one of its possible representation is based on counting all trivially known connected and disconnected realizations (states) of a random graph, based on easily derived information about graph’s structure, such as existence of chains and their lengths.
{"title":"Fast Rough Bounds for the Coefficients of the Network Reliability Polynomial","authors":"A. Rodionov","doi":"10.1109/OPCS.2019.8880191","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880191","url":null,"abstract":"The problem of fast estimating of reliability polynomial’ coefficients is considered in the paper in the case of all-terminal reliability (probability of a graph being connected). Obtaining lower and upper bounds for each coefficient of a reliability polynomial in one of its possible representation is based on counting all trivially known connected and disconnected realizations (states) of a random graph, based on easily derived information about graph’s structure, such as existence of chains and their lengths.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126839225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880181
A. Penenko, Z. Mukatova
The problem of data assimilation for the advection diffusion model is considered. Data assimilation is carried out by choosing an uncertainty function that has the sense of the emission sources. Previously, a direct algorithm for data assimilation with a stabilizer in the cost functional governing the norm of the uncertainty function and its spatial derivative was introduced. In the paper, the assimilation parameters are found for a scenario with a known solution (training sample). The optimization is carried out by a genetic algorithm. The values found are used in scenarios with unknown emission sources (control experiment). The results of numerical experiments on solving a test problem are given.
{"title":"Scenario Approach for the Optimization of Regularization Parameters in the Direct Variational Data Assimilation Algorithm","authors":"A. Penenko, Z. Mukatova","doi":"10.1109/OPCS.2019.8880181","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880181","url":null,"abstract":"The problem of data assimilation for the advection diffusion model is considered. Data assimilation is carried out by choosing an uncertainty function that has the sense of the emission sources. Previously, a direct algorithm for data assimilation with a stabilizer in the cost functional governing the norm of the uncertainty function and its spatial derivative was introduced. In the paper, the assimilation parameters are found for a scenario with a known solution (training sample). The optimization is carried out by a genetic algorithm. The values found are used in scenarios with unknown emission sources (control experiment). The results of numerical experiments on solving a test problem are given.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128116106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-01DOI: 10.1109/OPCS.2019.8880249
E. Gimadi, Danila Chesnokov, E. Shin
One clustering problem, which arises in design of search systems, is considered. NP-hardness of the general case of the problem is proved. A complexity status is determined for the cases with certain particular structures of the directed graph, such as: Complete Acyclic graph, Path graph, OutTree and InTree graphs. For the cases of Path and InTree graphs the exact algorithms with quadratic complexity are proposed.
{"title":"One Class of Clusterization Problems in Network Models","authors":"E. Gimadi, Danila Chesnokov, E. Shin","doi":"10.1109/OPCS.2019.8880249","DOIUrl":"https://doi.org/10.1109/OPCS.2019.8880249","url":null,"abstract":"One clustering problem, which arises in design of search systems, is considered. NP-hardness of the general case of the problem is proved. A complexity status is determined for the cases with certain particular structures of the directed graph, such as: Complete Acyclic graph, Path graph, OutTree and InTree graphs. For the cases of Path and InTree graphs the exact algorithms with quadratic complexity are proposed.","PeriodicalId":288547,"journal":{"name":"2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129804495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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