scholarly journals DEVELOPMENT OF METHODS FOR SUPPLY MANAGEMENT IN TRANSPORTATION NETWORKS UNDER CONDITIONS OF UNCERTAINTY OF TRANSPORTATION COST VALUES

2021 ◽  
pp. 108-123
Author(s):  
Lev Raskin ◽  
Oksana Sira ◽  
Yurii Parfeniuk ◽  
Kseniia Bazilevych
Keyword(s):  
Original Problem ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Computational Procedure ◽  
Small Sample ◽  
Logistics System ◽  
The Given ◽  
Random Nature ◽  
Transportation Plan ◽  
Cost Of Transportation

The problem of transport management in a distributed logistics system "suppliers – consumers" is considered. Under the assumption of a random nature of transportation costs, an exact algorithm for solving this problem by a probabilistic criterion has been developed. This algorithm is implemented by an iterative procedure for sequential improvement of the transportation plan. The rate of convergence of a computational procedure to an exact solution depends significantly on the dimension of the problem and is unacceptably low in real problems. In this regard, an alternative method is proposed, based on reducing the original problem to solving a nontrivial problem of fractional-nonlinear programming. A method for solving this problem has been developed and substantiated. The corresponding computational algorithm reduces the fractional-nonlinear model to the quadratic one. The resulting problem is solved by known methods. Further, the original problem is supplemented by considering a situation that is important for practice, when in the conditions of a small sample of initial data there is no possibility of obtaining adequate analytical descriptions for the distribution densities of the random costs of transportation. In this case, the available volume of statistical material is sufficient only to estimate the first two moments of unknown distribution densities. For this marginal case, a minimax method for finding the transportation plan is proposed. The first step is to solve the problem of determining the worst distribution density with the given values of the first two moments. In the second step, the transportation plan is found, which is the best in this most unfavorable situation, when the distribution densities of the random cost of transportation are the worst. To find such densities, let’s use the modern mathematical apparatus of continuous linear programming

scholarly journals A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY

2021 ◽  
pp. 80-88
Author(s):  
Lev Raskin ◽  
Yurii Parfeniuk ◽  
Larysa Sukhomlyn ◽  
Mykhailo Kravtsov ◽  
Leonid Surkov
Keyword(s):  
Nonlinear Programming ◽  
Initial Data ◽  
Computational Procedure ◽  
Complex Problem ◽  
Small Sample ◽  
Goal Development ◽  
The Cost ◽  
Transportation Plan ◽  
Cost Of Transportation ◽  
Transport Logistics

Subject.The canonical task of transport logistics in the distributed system "suppliers - consumers" is considered. Goal. Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. Tasks. 1. Development of an exact method for solving the problem of finding a plan that minimizes the total cost of transportation in conditions when their costs are given by their distribution densities. 2. Development of a method for solving the problem when the distribution density of the cost of transportation is not known. Methods. A computational scheme for solving the problem is proposed, which is implemented by an iterative procedure for sequential improvement of the transportation plan. The convergence of this procedure is proved. In order to accelerate the convergence of the computational procedure to the exact solution, an alternative method is proposed based on the solution of a nontrivial problem of fractional nonlinear programming. The method reduces the original complex problem to solving a sequence of simpler problems. The original problem is supplemented by considering a situation that is important for practice when, in the conditions of a small sample of initial data, there is no possibility of obtaining adequate analytical descriptions for the distribution densities of the random costs of transportation. To solve the problem in this case, a minimax method is proposed for finding the best transportation plan in the most unfavorable situation, when the distribution densities of the random cost of transportation are the worst. To find such densities, the modern mathematical apparatus of continuous linear programming was used. Results. A mathematical model and a method for solving the problem of transport logistics in conditions of uncertainty of the initial data are proposed. The desired plan is achieved using the solution of the fractional nonlinear programming problem. Conclusions: The problem of forming a transportation plan is considered, provided that their costs are random values. Also, a method for solving the problem of optimization of transportation for a situation where the density of distribution of random cost cannot be correctly determined is considered.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals ESTIMATED TRANSPORTATION COST OF LOW-TONNAGE LNG

2020 ◽  
Vol 17 (5) ◽  
pp. 130-163
Author(s):  
O. V. Tarovik ◽  
O. M. Mudrova
Keyword(s):  
Coastal Waters ◽  
Unit Cost ◽  
Transportation Cost ◽  
Model Calculations ◽  
Inland Waterways ◽  
Universal Approach ◽  
Environmental Requirements ◽  
Regression Relations ◽  
The Cost ◽  
Cost Of Transportation

Demand for low-tonnage transportation of LNG requires improved logistics. Assessing the value of all parts of the supply chain is an important component of solving the problem of optimizing transportation costs for both consumers and LNG suppliers. In connection with tightening of environmental requirements regarding bunker fuel, the task of optimizing the supply of LNG for water transport by the cost of transportation becomes particularly relevant.The objective of the study is to develop a universal approach to estimating the cost of transporting low-tonnage LNG for bunkering vessels in the Russian Federation.The research methodology is focused on the analytical method based on a system-structural approach.As part of the departmental project of the Russian Ministry of Industry and Trade «Development of  gaspowered fleet for navigation in coastal waters and inland waterways», the authors developed technical and economic models for calculating the unit cost of LNG transportation by road and water. To calculate the unit cost of LNG transportation by rail, the data of TMkarta information and reference system were used. Based on model calculations and data of TMkarta system, regression relations were obtained that allow one to determine the cost of transportation for various options of transport and technological schemes based on a limited set of parameters. An approach has also been proposed for estimating the cost of LNG transshipment. The regression ratios were tested for selected routes. As a result,conclusions were drawn about the most effective LNG transportation options.

scholarly journals The Graph Reasoning Approach Based on the Dynamic Knowledge Auxiliary for Complex Fact Verification

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1472
Author(s):  
Yongyue Wang ◽  
Chunhe Xia ◽  
Chengxiang Si ◽  
Chongyu Zhang ◽  
Tianbo Wang
Keyword(s):  
Common Sense ◽  
Negative Impact ◽  
Background Knowledge ◽  
Small Sample ◽  
Training Data ◽  
Reasoning Ability ◽  
Auxiliary Graph ◽  
Graph Neural Networks ◽  
The Given ◽  
Conceptual Relationship

Complex fact verification (FV) requires fusing scattered sequences and performing multi-hop reasoning over these composed sequences. Recently, by employing some FV models, knowledge is obtained from context to support the reasoning process based on pretrained models (e.g., BERT, XLNET), and this model outperforms previous out-of-the-art FV models. In practice, however, the limited training data cannot provide enough background knowledge for FV tasks. Once the background knowledge changed, the pretrained models’ parameters cannot be updated. Additionally, noise against common sense cannot be accurately filtered out due to the lack of necessary knowledge, which may have a negative impact on the reasoning progress. Furthermore, existing models often wrongly label the given claims as ‘not enough information’ due to the lack of necessary conceptual relationship between pieces of evidence. In the present study, a Dynamic Knowledge Auxiliary Graph Reasoning (DKAR) approach is proposed for incorporating external background knowledge in the current FV model, which explicitly identifies and fills the knowledge gaps between provided sources and the given claims, to enhance the reasoning ability of graph neural networks. Experiments show that DKAR put forward in this study can be combined with specific and discriminative knowledge to guide the FV system to successfully overcome the knowledge-gap challenges and achieve improvement in FV tasks. Furthermore, DKAR is adopted to complete the FV task on the Fake NewsNet dataset, showing outstanding advantages in a small sample and heterogeneous web text source.

The nature of flux variations in the continua and broad-line regions of selected active galactic nuclei

2020 ◽  
Vol 496 (1) ◽  
pp. 784-800
Author(s):  
A Bewketu Belete ◽  
L J Goicoechea ◽  
B L Canto Martins ◽  
I C Leão ◽  
J R De Medeiros
Keyword(s):  
Active Galactic Nuclei ◽  
Moving Average ◽  
Sampling Rate ◽  
Galactic Nuclei ◽  
Small Sample ◽  
Light Curves ◽  
Ngc 4151 ◽  
The Given ◽  
Ngc 7469 ◽  
The Continuum

ABSTRACT We present a multifractal analysis of the long-term light curves of a small sample of type 1 active galactic nuclei: NGC 4151, Arp 102B, 3C 390.3, E1821+643 and NGC 7469. We aim to investigate how the degrees of multifractality of the continuum and Hβ line vary among the five different objects and to check whether the multifractal behaviours of the continuum and the Hβ line correlate with standard accretion parameters. The backward (θ  = 0) one-dimensional multifractal detrended moving average procedure was applied to light curves covering the full observation period and partial observation periods containing an equal number of epochs for each object. We detected multifractal signatures for the continua of NGC 4151, Arp 102B and 3C 390.3 and for the Hβ lines of NGC 4151 and 3C 390.3. However, we found nearly monofractal signatures for the continua of E1821+643 and NGC 7469, as well as for the Hβ lines of Arp 102B, E1821+643 and NGC 7469. In addition, we did not find any correlations between the degree of multifractality of the Hβ line and accretion parameters, while the degree of multifractality of the continuum seems to correlate with the Eddington ratio (i.e. the smaller the ratio is, the stronger the degree of multifractality). The given method is not robust, and these results should be taken with caution. Future analysis of the sampling rate and other properties of the light curves should help with better constraining and understanding these results.

scholarly journals Multiobjective Scheduling of Remote-Area Employees with Minimum Cost of Transportation

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Hesham K. Alfares
Keyword(s):  
Programming Model ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Transportation Cost ◽  
Solution Procedure ◽  
Primary Objective ◽  
Remote Work ◽  
Optimal Procedures ◽  
Oil Company ◽  
Cost Of Transportation

An integer programming model and optimal solution procedure are presented for assigning employees to the (10, 14) days-off schedule. This schedule is used by a large oil company to schedule employees in remote work locations. The primary objective is to minimize the total number of employees. Since employees are flown to their remote work sites, the company also aims to minimize transportation cost. Therefore, secondary objectives include (1) minimizing the number of active days-off work patterns, (2) consistently using the same set of active days-off patterns, (3) assigning work schedules fairly among employees, and (4) avoiding the use of specialized optimization solvers. A rotation schedule is used in which two scheduling rules are enforced: a minimum proportion of weekend days off needs to be given and a maximum limit on the number of successive workdays cannot be exceeded. Utilizing the problem structure, simple optimal procedures are developed to solve this unique complex scheduling problem.

scholarly journals Performance on verbal fluency tasks depends on the given category/letter: Preliminary data from a multivariable analysis

2022 ◽  
Author(s):  
Petar Gabrić ◽  
Mija Vandek
Keyword(s):  
Verbal Fluency ◽  
Response Times ◽  
Small Sample Size ◽  
Multivariable Analysis ◽  
Small Sample ◽  
Corpus Analysis ◽  
Response Latencies ◽  
Specific Effects ◽  
First Response ◽  
The Given

Verbal fluency tasks are often used in neuropsychological research and may have predictive and diagnostic utility in psychiatry and neurology. However, researchers using verbal fluency have uncritically assumed that there are no category- or phoneme-specific effects on verbal fluency performance. We recruited 16 young adult subjects and administered two semantic (animals, trees) and phonemic (K, M) fluency tasks. Because of the small sample size, results should be regarded as preliminary. On the animal compared to the tree task, subjects produced significantly more legal words, had a significantly lower intrusion rate, significantly shorter first-response latencies and final silence periods, as well as significantly shorter between-cluster response latencies. These differences may be explained by differences in the category sizes, integrity of the categories' borders, and efficiency of the functional connectivity between subcategories. On the K compared to the M task, subjects produced significantly more legal words and had significantly shorter between-cluster response times. Counterintuitively, a corpus analysis revealed there are more words starting with m compared to k in the experimental language. Our results have important implications for research utilizing verbal fluency, including decreased reproducibility, unreliability of diagnostic and predictive tools based on verbal fluency, and decreased knowledge accumulation.

scholarly journals Peculiarities of the logistic approach in the agro-industrial complex

2021 ◽  
Vol 935 (1) ◽  
pp. 012048
Author(s):  
L G Gordeeva ◽  
S P Filippova ◽  
A A Gordeev ◽  
M S Abrosimova ◽  
O V Litvinova ◽  
...  
Keyword(s):  
Financial Stability ◽  
New Technologies ◽  
Industrial Complex ◽  
Logistics System ◽  
Approaches To Studying ◽  
Financial Activity ◽  
Theoretical Approaches ◽  
Food Market ◽  
The Given

Abstract Effective sale of products is one of the main directions of increasing the financial stability of enterprises in the agro-industrial complex. The use of a logistic approach implies a change in the existing situation at the enterprises of the agro-industrial complex, the introduction of new technologies in order to reduce the costs of commodity movement, and the coordination of interaction between participants in the logistics system. It is necessary to take into account the specifics of the food market more fully, consider the logistics system in conditions when a large number of economically independent market entities enter the market. The paper examines theoretical approaches to studying the problem of using the logistic approach in the agro-industrial complex and reveals the basic nodes of the agro-logistics system. Peculiarities of using logistics in the agro-industrial complex are described, basic logistic flows and processes in the given branch are reviewed. Types of distribution of products in the agro-industrial complex are analyzed. Influence of use of logistic methods of management generally and of stocks in particular on production and financial activity of enterprises in the given sphere is estimated.

scholarly journals Improved Regularization Method for Backward Cauchy Problems Associated with Continuous Spectrum Operator

2011 ◽  
Vol 2011 ◽  
pp. 1-11
Author(s):  
Salah Djezzar ◽  
Nihed Teniou
Keyword(s):  
Continuous Spectrum ◽  
Original Problem ◽  
Convergence Rates ◽  
Nonlocal Problem ◽  
Cauchy Problems ◽  
Final Time ◽  
Unbounded Linear Operator ◽  
Convergence Results ◽  
Small Parameters ◽  
The Given

We consider in this paper an abstract parabolic backward Cauchy problem associated with an unbounded linear operator in a Hilbert space , where the coefficient operator in the equation is an unbounded self-adjoint positive operator which has a continuous spectrum and the data is given at the final time and a solution for is sought. It is well known that this problem is illposed in the sense that the solution (if it exists) does not depend continuously on the given data. The method of regularization used here consists of perturbing both the equation and the final condition to obtain an approximate nonlocal problem depending on two small parameters. We give some estimates for the solution of the regularized problem, and we also show that the modified problem is stable and its solution is an approximation of the exact solution of the original problem. Finally, some other convergence results including some explicit convergence rates are also provided.

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