scholarly journals A Framework for the Joint Placement of Edge Service Infrastructure and User Plane Functions for 5G

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3975 ◽  
Author(s):  
Irian Leyva-Pupo ◽  
Alejandro Santoyo-González ◽  
Cristina Cervelló-Pastor
Keyword(s):  
Linear Programming ◽  
Optimal Solution ◽  
Cost Savings ◽  
Computation Time ◽  
Optimal Number ◽  
Use Cases ◽  
Next Generation Networks ◽  
Placement Problem ◽  
Communication Latency ◽  
Operational Costs

Achieving less than 1 ms end-to-end communication latency, required for certain 5G services and use cases, is imposing severe technical challenges for the deployment of next-generation networks. To achieve such an ambitious goal, the service infrastructure and User Plane Function (UPF) placement at the network edge, is mandatory. However, this solution implies a substantial increase in deployment and operational costs. To cost-effectively solve this joint placement problem, this paper introduces a framework to jointly address the placement of edge nodes (ENs) and UPFs. Our framework proposal relies on Integer Linear Programming (ILP) and heuristic solutions. The main objective is to determine the ENs and UPFs’ optimal number and locations to minimize overall costs while satisfying the service requirements. To this aim, several parameters and factors are considered, such as capacity, latency, costs and site restrictions. The proposed solutions are evaluated based on different metrics and the obtained results showcase over 20 % cost savings for the service infrastructure deployment. Moreover, the gap between the UPF placement heuristic and the optimal solution is equal to only one UPF in the worst cases, and a computation time reduction of over 35 % is achieved in all the use cases studied.

scholarly journals Data-based polyhedron model for optimization of engineering structures involving uncertainties

2021 ◽  
Vol 2 ◽  
Author(s):  
Zhiping Qiu ◽  
Han Wu ◽  
Isaac Elishakoff ◽  
Dongliang Liu
Keyword(s):  
Linear Programming ◽  
Convex Polyhedron ◽  
Linear Optimization ◽  
Optimal Solution ◽  
Composite Plates ◽  
Convex Polyhedra ◽  
Chebyshev Inequality ◽  
Engineering Structures ◽  
Load Bearing ◽  
Polyhedron Model

Abstract This paper studies the data-based polyhedron model and its application in uncertain linear optimization of engineering structures, especially in the absence of information either on probabilistic properties or about membership functions in the fussy sets-based approach, in which situation it is more appropriate to quantify the uncertainties by convex polyhedra. Firstly, we introduce the uncertainty quantification method of the convex polyhedron approach and the model modification method by Chebyshev inequality. Secondly, the characteristics of the optimal solution of convex polyhedron linear programming are investigated. Then the vertex solution of convex polyhedron linear programming is presented and proven. Next, the application of convex polyhedron linear programming in the static load-bearing capacity problem is introduced. Finally, the effectiveness of the vertex solution is verified by an example of the plane truss bearing problem, and the efficiency is verified by a load-bearing problem of stiffened composite plates.

scholarly journals Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului
Keyword(s):  
Decision Making ◽  
Ad Hoc ◽  
Market Competition ◽  
Optimal Solution ◽  
Cost Savings ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimal Decision ◽  
Environmental Damage ◽  
Fuel Cost

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.

scholarly journals Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

2014 ◽  
Vol 39 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Enrique Gerstl ◽  
Gur Mosheiov ◽  
Assaf Sarig
Keyword(s):  
Flow Shop ◽  
Optimal Solution ◽  
Setup Time ◽  
Optimal Number ◽  
Two Stage ◽  
Second Stage ◽  
Flow Shop Problem ◽  
Batch Sizes ◽  
Batch Schedule ◽  
Identical Jobs

Abstract We study a special two-stage flexible flowshop, which consists of several parallel identical machines in the first stage and a single machine in the second stage. We assume identical jobs, and the option of batching, with a required setup time prior to the processing of a new batch. We also consider the option to use only a subset of the available machines. The objective is minimum makespan. A unique optimal solution is introduced, containing the optimal number of machines to be used, the sequence of batch sizes, and the batch schedule. The running time of our proposed solution algorithm is independent of the number of jobs, and linear in the number of machines

Towards Intelligent Road Traffic Management over Weighted Large Graphs Hybrid Meta-heuristic-Based Approach

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Traffic Management ◽  
Large Scale ◽  
Road Traffic ◽  
Optimization Technique ◽  
Shortest Paths ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Computation Time ◽  
Exact Algorithm ◽  
On The Road

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Joint optimization of components redundancy, spares inventory and repairmen allocation for a standby series system

2018 ◽  
Vol 233 (4) ◽  
pp. 623-638
Author(s):  
Xian Zhao ◽  
Jing Zhang ◽  
Xiaoyue Wang
Keyword(s):  
Optimal Solution ◽  
Optimal Number ◽  
Joint Optimization ◽  
Series System ◽  
Inventory Policy ◽  
System Availability ◽  
Cold Standby ◽  
Batch Ordering ◽  
The Mathematical Model ◽  
Warm Standby

In the past, redundancy, inventory and maintenance are often considered separately to improve the system availability. Recently, a few joint optimization papers have emerged, but they only considered hot-standby redundancy, one-for-one-ordering inventory policy and the case of single repairman. In order to deepen the previous research, this article formulates a joint optimization model of components redundancy, spares inventory and repairmen allocation for a standby series system with an objective of maximizing system availability. As to the components redundancy, hot-standby, warm-standby and cold-standby are considered, respectively. A more general batching ordering inventory policy is adopted and the number of repairmen is added as a new element. By continuous time Markov process, related reliability probability indices are derived. Then the mathematical model is constructed and branch-and-bound method is employed to solve the optimal solution. Finally, we conduct analysis and comparison for different numerical examples and obtain the following results: cold-standby and warm-standby redundancy yield higher availabilities compared to hot-standby under the same conditions. The optimal batch ordering inventory policy is better than optimal one-for-one-ordering inventory policy if the spares replenishment rate is not high enough. Moreover, an optimal number of repairmen, which is always more than one, can be achieved to enhance the efficiency of maintenance.

scholarly journals Linear programming measures for solving the problem of a linear division of convex multiplayers.

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Sarmad H. Ali ◽  
Osamah A. Ali ◽  
Samir C. Ajmi
Keyword(s):  
Machine Learning ◽  
Linear Programming ◽  
Optimal Solution ◽  
Optimal Method ◽  
Linear Separation ◽  
Different Types ◽  
Simplex Methods

In this research, we are trying to solve Simplex methods which are used for successively improving solution and finding the optimal solution, by using different types of methods Linear, the concept of linear separation is widely used in the study of machine learning, through this study we will find the optimal method to solve by comparing the time consumed by both Quadric and Fisher methods.

scholarly journals Modelo de otimização de recursos financeiros para o gerenciamento de riscos empresariais

2017 ◽  
Vol 1 (1) ◽  
pp. 98 ◽  
Author(s):  
Wanderlei Lima Paulo ◽  
Francisco Carlos Fernandes ◽  
Marcia Zanievicz Silva
Keyword(s):  
Linear Programming ◽  
Decision Process ◽  
Control Policy ◽  
Financial Resources ◽  
Business Risk ◽  
Risk Manager ◽  
Operational Costs ◽  
Proposed Model ◽  
Control Target ◽  
Reduced Costs

<p>This article aims to propose a model to determine the best allocation of financial resources for business risk management, permitting the risk manager to define a control policy with reduced costs that reaches a desired control target. The problem of study is presented as an issue of optimization of costs, formulated as a model of whole linear programming, which basic restrictions are associated to the demanded levels of control. The proposed model is applied to a problem of resource allocation for the control of operational costs. The results show that the model is an adequate instrument to better allocate financial resources, which its use proportionates better conditions for the decision process of business risks.</p>

scholarly journals Applying Simulation Modelling in Quantifying Optimization Results

2021 ◽  
Vol 15 (4) ◽  
pp. 518-523
Author(s):  
Ratko Stanković ◽  
Diana Božić
Keyword(s):  
Linear Programming ◽  
Simulation Model ◽  
Input Data ◽  
Optimization Problems ◽  
Programming Model ◽  
Optimal Solution ◽  
Simulation Modelling ◽  
Simulation Software ◽  
Programming Models ◽  
Freight Forwarding

Improvements achieved by applying linear programming models in solving optimization problems in logistics cannot always be expressed by physically measurable values (dimensions), but in non-dimensional values. Therefore, it may be difficult to present the actual benefits of the improvements to the stake holders of the system being optimized. In this article, a possibility of applying simulation modelling in quantifying results of optimizing cross dock terminal gates allocation is outlined. Optimal solution is obtained on the linear programming model by using MS Excel spreadsheet optimizer, while the results are quantified on the simulation model, by using Rockwell Automation simulation software. Input data are collected from a freight forwarding company in Zagreb, specialized in groupage transport (Less Than Truckload - LTL).

scholarly journals ANALISIS PENGGUNAAN SISTEM BARCODE UNTUK MENDUKUNG PAPERLESS DALAM MENINGKATKAN KEUNTUNGAN FINANSIAL DAN OPERASIONAL

2019 ◽  
Vol 5 (1) ◽  
pp. 1-6
Author(s):  
Danny Ong
Keyword(s):  
Employee Performance ◽  
Cost Savings ◽  
Operating Costs ◽  
Business World ◽  
Operational Process ◽  
Financial Cycle ◽  
World Today ◽  
Operational Costs ◽  
Effectiveness And Efficiency ◽  
Physical Paper

The use of physical paper in the business world today has become a consideration as a waste that can affect the company's financial cycle. The saving of using documents without using physical paper is one way to reduce the company's operating costs, especially for companies that have offices and also some factories in running their businesses. The operational process of non-physical documents is supported by the use of barcodes so that the use of paper is very minimal and management can reduce the company's operational costs to the maximum. This study aims to make observations and analysis of barcode usage related to the effectiveness and efficiency in terms of employee performance and especially financial savings. The results of the study show that in terms of operational expenses of the company that there are benefits of cost savings on physical paper purchases and also employee performance is quite significantly increased in carrying out daily operations because entering data can be done semi-automatically.

scholarly journals Ranking Function Application for Optimal Solution of Fractional programming problem

2020 ◽  
Vol 25 (1) ◽  
Author(s):  
Rasha Jalal
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Fractional Programming ◽  
Linear Programming Problem ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Ranking Function ◽  
Linear Fractional Programming ◽  
Fractional Programming Problem ◽  
Linear Programming Problems

The aim of this paper is to suggest a solution procedure to fractional programming problem based on new ranking function (RF) with triangular fuzzy number (TFN) based on alpha cuts sets of fuzzy numbers. In the present procedure the linear fractional programming (LFP) problems is converted into linear programming problems. We concentrate on linear programming problem problems in which the coefficients of objective function are fuzzy numbers, the right- hand side are fuzzy numbers too, then solving these linear programming problems by using a new ranking function. The obtained linear programming problem can be solved using win QSB program (simplex method) which yields an optimal solution of the linear fractional programming problem. Illustrated examples and comparisons with previous approaches are included to evince the feasibility of the proposed approach.

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