scholarly journals OPTIMIZATION OF TOPOLOGICAL STRUCTURES OF CENTRALIZED LOGISTICS NETWORKS IN THE PROCESS OF REENGINEERING

2021 ◽  
pp. 23-31
Author(s):  
Vladimir Beskorovainyi ◽  
Antonii Sudik
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Time Complexity ◽  
Large Scale ◽  
System Optimization ◽  
Distributed Objects ◽  
Computational Point ◽  
Topological Structures ◽  
Logistics Networks ◽  
Current State

The subject of research in the article is the topological structures of closed logistics networks. The purpose of the work is to create a mathematical model and methods for solving problems of optimization of topological structures of centralized logistics networks in the process of reengineering, taking into account many topological and functional constraints. The article solves the following tasks: analysis of the current state of the problem of system optimization of logistics networks and methods of its solution; formalization of the problem of system optimization of logistics networks as territorially distributed objects; development of a mathematical model of the problem of optimization of centralized three-level topological structures of logistics networks at the stage of reengineering; development of a method for solving the problem of optimization of centralized three-level topological structures of logistics networks at the reengineering stage; estimation of time complexity of the method of optimization of centralized three-level topological structures of logistics networks. The following methods are used: methods of systems theory, methods of utility theory, optimization and operations research. The following results were obtained: analysis of the current state of the problem of system optimization of logistics networks and methods of its solution; the problem of system optimization of logistics networks as territorially distributed objects has been formalized; developed a mathematical model of the problem of reengineering three-level topological structures of logistics networks in terms of cost and efficiency for the case of combined production and processing points; methods of directed search of variants of construction of a logistic network which use procedures of coordinate optimization and modeling of evolution on the basis of genetic algorithm are developed; estimates of the accuracy and time complexity of optimization methods of centralized three-level topological structures of logistics networks are obtained. Conclusions: Based on the results of the study of methods for solving the problem, an approximation of their accuracy and time complexity was performed. In practice, this will allow you to choose a more efficient method for solving large-scale practical problems, based on the required accuracy, available computing and time resources. The method based on the coordinate optimization procedure has a significantly higher accuracy, but it is more complex from a computational point of view. The accuracy of the evolutionary method based on a genetic algorithm can be increased by increasing the number of iterations. The practical use of the proposed mathematical model and methods of reengineering the topological structures of centralized closed logistics systems by jointly solving problems for direct and reverse flows will reduce the cost of transport activities of companies. Keywords: closed logistics; logistics network; optimization; reengineering; structure; topology.

Mathematical model of structural and topological optimization of logistics networks

2021 ◽  
pp. 178
Author(s):  
Volodymyr Bezkorovainyi ◽  
Leonid Nefedov ◽  
Vladimir Russkin
Keyword(s):  
Mathematical Model ◽  
Optimization Problem ◽  
System Optimization ◽  
Topological Optimization ◽  
Distributed Objects ◽  
Topological Structures ◽  
Logistics Networks ◽  
Current State ◽  
Geographically Distributed ◽  
The Mathematical Model

The subject of research in the article is the topological structures of closed-loop logistics networks. The goal of the article is to increase the efficiency of centralized logistics networks by developing a mathematical model for a two-criteria problem of optimizing topological structures in the process of their reengineering. The article solves the following tasks: analysis of the current state of the problem of structural and topological optimization of logistics networks; formalization of the problem of optimization of logistics networks as geographically distributed objects; synthesis of objective functions of the mathematical model of a two-criterion optimization problem for centralized three-level topological structures of closed logistics networks at the reengineering stage; development of a system of constraints of the mathematical model of the problem of optimizing centralized three-level topological structures of closed logistics networks; a function for evaluating the overall utility of options based on the Kolmogorov-Gabor polynomial is offered. The following methods are used: methods of systems theory, methods of utility theory, optimization and operations research. The following results were obtained: the analysis of the current state of the problem of system optimization of logistics networks, mathematical models and methods for its solution was carried out; formalization of the problem of structural and topological optimization of logistics networks as geographically distributed objects; a mathematical model of a two-criterion task of reengineering of three-level topological structures of logistics networks in terms of costs and efficiency with integrated points of production and processing has been developed (originality). Conclusions: Based on the results of the analysis of the problem of optimizing the topological structures of logistics systems, it has been established that the problems of direct and reverse logistics are still considered as conditionally independent, which does not allow obtaining effective global solutions. In the context of expanding the network of consumers, changes in delivery volumes, the introduction of environmental restrictions, it is proposed to reengineer the networks, which provides for their radical redesign. The formulated statement and the developed mathematical model of a two-criterion (in terms of cost and efficiency) optimization problem for three-level topological structures for combined production and processing points will increase the efficiency of logistics networks with reverse flows by reducing the cost of reengineering (practical value).

scholarly journals Efficient Non-parametric Bayesian Hawkes Processes

2019 ◽  
Author(s):  
Rui Zhang ◽  
Christian Walder ◽  
Marian-Andrei Rizoiu ◽  
Lexing Xie
Keyword(s):  
Time Complexity ◽  
Large Scale ◽  
Goodness Of Fit ◽  
Linear Time ◽  
Synthetic Data ◽  
Hawkes Process ◽  
Hawkes Processes ◽  
Branching Structures ◽  
Current State ◽  
Non Parametric

In this paper, we develop an efficient non-parametric Bayesian estimation of the kernel function of Hawkes processes. The non-parametric Bayesian approach is important because it provides flexible Hawkes kernels and quantifies their uncertainty. Our method is based on the cluster representation of Hawkes processes. Utilizing the stationarity of the Hawkes process, we efficiently sample random branching structures and thus, we split the Hawkes process into clusters of Poisson processes. We derive two algorithms --- a block Gibbs sampler and a maximum a posteriori estimator based on expectation maximization --- and we show that our methods have a linear time complexity, both theoretically and empirically. On synthetic data, we show our methods to be able to infer flexible Hawkes triggering kernels. On two large-scale Twitter diffusion datasets, we show that our methods outperform the current state-of-the-art in goodness-of-fit and that the time complexity is linear in the size of the dataset. We also observe that on diffusions related to online videos, the learned kernels reflect the perceived longevity for different content types such as music or pets videos.

scholarly journals Development of the mathematical model of the problem of reengineering topological structures of large-scale monitoring systems

2015 ◽  
Vol 4 (4(76)) ◽  
pp. 49
Author(s):  
Владимир Валентинович Бескоровайный ◽  
Ксения Евгеньевна Подоляка
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Monitoring Systems ◽  
Topological Structures ◽  
The Mathematical Model

scholarly journals MATHEMATICAL MODELS OF DECISION SUPPORT IN THE PROBLEMS OF LOGISTICS NETWORKS OPTIMIZATION

2021 ◽  
pp. 5-14
Author(s):  
Vladimir Beskorovainyi ◽  
Oksana Draz
Keyword(s):  
Mathematical Model ◽  
Decision Support ◽  
Mathematical Models ◽  
General Problem ◽  
Network Optimization ◽  
Optimization Problems ◽  
Final Choice ◽  
Logistics Networks ◽  
Current State

The subject of research in the article is the process of decision support in the problems of logistics networks optimization. The goal of the work is to develop a set of mathematical models of logistics network optimization problems to increase the efficiency of decision support systems by coordinating the interaction between automatic and interactive procedures of computer-aided design systems. The following tasks are solved in the article: review and analysis of the current state of the problem of decision support in the problems of logistics networks optimization; decomposition of the problem of decision support for the optimization of logistics networks; development of a mathematical model of the general problem of network optimization in terms of economy, efficiency, reliability and survivability; development of a set of technological mathematical models for the correct reduction of many effective options for building logistics networks for the final choice, taking into account difficult to formalize factors, knowledge and experience of the decision maker (DM). The following methods are used: systems theory, utility theory, optimization and operations research. Results. Analysis of the current state of the problem of logistics networks optimization has established the existence of the problem of correct reduction of a subset of effective options for their construction for ranking, taking into account difficult to formalize factors, as well as knowledge and experience of DM. The decomposition of the problem into tasks is performed: definition of the principles of network construction; network structure selection; determination of the topology of network elements; choice of network operation technology; determination of parameters of elements and communications (means of cargo delivery); multi criteria evaluation and selection of the best option for building a network. A mathematical model of the general problem of network optimization in terms of economy, efficiency, reliability and survivability is proposed. To coordinate the interaction between automatic and interactive network optimization procedures, it is proposed to use a combined method of ranking options, which allows you to identify and correctly reduce the subset of effective options for ranking DM. To implement the method, mathematical models of problems of the procedure of ranking options in the technologies of project decision support have been developed, which allow to combine the advantages of the technologies of the ordinalistic and cardinalistic approaches. Conclusions. The developed set of mathematical models expands the methodological bases of automation of processes of support of multi criteria decisions on optimization of logistic networks, allows to carry out correct reduction of set of effective options of their construction for the final choice taking into account factors, knowledge and experience of DM. The practical use of the proposed models and procedures will reduce the time and capacity complexity of decision support technologies, and through the use of the proposed selection procedures - to improve their quality across a variety of functional and cost indicators.

Optimal Design of Multistage Flash Desalination Process Based on the Modified Genetic Algorithm (MGA)

2011 ◽  
Vol 233-235 ◽  
pp. 1044-1049
Author(s):  
Lian Ying Wu ◽  
Yang Dong Hu ◽  
Cong Jie Gao
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Flow Rate ◽  
Water Flow Rate ◽  
System Optimization ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Continuous Variables ◽  
Integer Variables ◽  
Modified Genetic Algorithm

In this paper, a rigorous mathematical model of multistage flash system (MSF) is presented based on a detailed physicochemical representation of the process, including all the fundamental elementary phenomena. In particular, Comparison to the mathematical model of reference, two integer variables, which are the number of recovery stage (NR) and the number of rejection stage (NJ), are introduced to the model. Additionally, two special variables, which are the ratio of recirculation brine water flow rate and distillation flow rate and the ratio of make-up flow rate and the distillation flow rate, are introduced to the model as the continuous variables too. Then, the MSF system is described as a mixed-integer nonlinear programming (MINLP). The objective is to minimize the total annual cost (TAC), which is mainly composed of the operating costs and investment cost. Here the modified genetic algorithm (MGA), which is characterized as mixing coding way, is adopted for the system optimization. A case study and a discussion of the results are presented.

Research on cargo-loading optimization based on genetic and fuzzy integration

2021 ◽  
Vol 40 (4) ◽  
pp. 8493-8500
Author(s):  
Yanwei Du ◽  
Feng Chen ◽  
Xiaoyi Fan ◽  
Lei Zhang ◽  
Henggang Liang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Three Dimensional ◽  
Distribution Center ◽  
Long Time ◽  
Low Efficiency ◽  
Decision Making Model ◽  
The Mathematical Model ◽  
Loading Scheme

With the increase of the number of loaded goods, the number of optional loading schemes will increase exponentially. It is a long time and low efficiency to determine the loading scheme with experience. Genetic algorithm is a search heuristic algorithm used to solve optimization in the field of computer science artificial intelligence. Genetic algorithm can effectively select the optimal loading scheme but unable to utilize weight and volume capacity of cargo and truck. In this paper, we propose hybrid Genetic and fuzzy logic based cargo-loading decision making model that focus on achieving maximum profit with maximum utilization of weight and volume capacity of cargo and truck. In this paper, first of all, the components of the problem of goods stowage in the distribution center are analyzed systematically, which lays the foundation for the reasonable classification of the problem of goods stowage and the establishment of the mathematical model of the problem of goods stowage. Secondly, the paper abstracts and defines the problem of goods loading in distribution center, establishes the mathematical model for the optimization of single car three-dimensional goods loading, and designs the genetic algorithm for solving the model. Finally, Matlab is used to solve the optimization model of cargo loading, and the good performance of the algorithm is verified by an example. From the performance evaluation analysis, proposed the hybrid system achieve better outcomes than the standard SA model, GA method, and TS strategy.

scholarly journals Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1030
Author(s):  
Julie Lake ◽  
Catherine S. Storm ◽  
Mary B. Makarious ◽  
Sara Bandres-Ciga
Keyword(s):  
Neurodegenerative Diseases ◽  
Large Scale ◽  
Disease Diagnosis ◽  
Open Science ◽  
Future Directions ◽  
The Road ◽  
Current State ◽  
Molecular Complexity ◽  
Science Framework ◽  
Lateral Sclerosis

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson’s disease, Alzheimer’s disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

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