scholarly journals Genetic algorithm for network cost minimization using threshold based discounting

2003 ◽  
Vol 7 (4) ◽  
pp. 207-228 ◽  
Author(s):  
Hrvoje Podnar ◽  
Jadranka Skorin-Kapov
Keyword(s):  
Genetic Algorithm ◽  
Communication Networks ◽  
Branch And Bound ◽  
Cost Minimization ◽  
Total Flow ◽  
Cpu Time ◽  
Network Cost ◽  
Cost Minimization Problem ◽  
The Cost ◽  
Different Sources

We present a genetic algorithm for heuristically solving a cost minimization problem applied to communication networks with threshold based discounting. The network model assumes that every two nodes can communicate and offers incentives to combine flow from different sources. Namely, there is a prescribed threshold on every link, and if the total flow on a link is greater than the threshold, the cost of this flow is discounted by a factor α. A heuristic algorithm based on genetic strategy is developed and applied to a benchmark set of problems. The results are compared with former branch and bound results using the CPLEX® solver. For larger data instances we were able to obtain improved solutions using less CPU time, confirming the effectiveness of our heuristic approach.

Demystifying Multi-Tier Cost Model for Scheduling in Fog Communication Networks

2022 ◽  
pp. 145-152
Author(s):  
Jagadesh T. ◽  
Jaishankar B.
Keyword(s):  
Nash Equilibrium ◽  
Communication Networks ◽  
Cost Minimization ◽  
Cost Model ◽  
User Equipment ◽  
Multi Level ◽  
The Cost

In this chapter, the authors explore a cost model and the come about cost-minimization client booking issue in multi-level mist figuring organizations. For an average multi-level haze figuring network comprising of one haze control hub (FCN), different fog access nodes (FANs), and user equipment (UE), how to model the cost paid to FANs for propelling assets sharing and how to adequately plan UEs to limit the cost for FCN are still issues to be settled. To unravel these issues, multi-level cost model, including the administration delay and a straight backwards request dynamic installment conspire, is proposed, and a cost-minimization client planning issue is defined. Further, the client planning issue is reformulated as an expected game and demonstrated to have a Nash equilibrium (NE) arrangement.

Cost-Optimal Coordination of Interacting HVAC Loads in Buildings

2017 ◽  
Vol 140 (4) ◽  
Author(s):  
Saeid Bashash
Keyword(s):  
Control Function ◽  
Cost Minimization ◽  
Control Input ◽  
Electricity Pricing ◽  
Temperature Deviation ◽  
Air Conditioners ◽  
Optimal Coordination ◽  
Optimal Energy Management ◽  
Cost Minimization Problem ◽  
The Cost

This paper investigates the optimal coordination of multiple interacting heating, ventilation, and air conditioning (HVAC) appliances in buildings such as air conditioners and refrigerators, in time-varying electricity pricing environments. Each load is modeled as a first-order differential equation with a binary (ON–OFF) switching control function. An energy cost minimization problem is then formulated with weighted penalties on the temperature deviation from the desired setpoint and the control input fluctuation. Using the dynamic programming (DP) method, the cost-optimal trajectories are computed, which indicate precooling of the loads in anticipation of higher electricity prices. Moreover, the loads are desynchronized in the presence of local renewable generation to maximize the on-site consumption of the local energy. The presented results provide useful insights for the development of predictive control policies for optimal energy management in buildings.

scholarly journals Reducing the Cost of Electricity by Optimizing Real-Time Consumer Planning Using a New Genetic Algorithm-Based Strategy

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1144 ◽  
Author(s):  
Laurentiu-Mihai Ionescu ◽  
Nicu Bizon ◽  
Alin-Gheorghita Mazare ◽  
Nadia Belu
Keyword(s):  
Genetic Algorithm ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Time Interval ◽  
Renewable Sources ◽  
Total Cost ◽  
Cost Of Electricity ◽  
Cost Of Energy ◽  
Input Parameters ◽  
The Cost

To ensure the use of energy produced from renewable energy sources, this paper presents a method for consumer planning in the consumer–producer–distributor structure. The proposed planning method is based on the genetic algorithm approach, which solves a cost minimization problem by considering several input parameters. These input parameters are: the consumption for each unit, the time interval in which the unit operates, the maximum value of the electricity produced from renewable sources, and the distribution of energy production per unit of time. A consumer can use the equipment without any planning, in which case he will consume energy supplied by a distributor or energy produced from renewable sources, if it is available at the time he operates the equipment. A consumer who plans his operating interval can use more energy from renewable sources, because the planning is done in the time interval in which the energy produced from renewable sources is available. The effect is that the total cost of energy to the consumer without any planning will be higher than the cost of energy to the consumer with planning, because the energy produced from renewable sources is cheaper than that provided from conventional sources. To be validated, the proposed approach was run on a simulator, and then tested in two real-world case studies targeting domestic and industrial consumers. In both situations, the solution proposed led to a reduction in the total cost of electricity of up to 25%.

scholarly journals Advanced Computation Capacity Modeling for Delay-Constrained Placement of IoT Services

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3830
Author(s):  
Balázs Németh ◽  
Balázs Sonkoly
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Cost Minimization ◽  
Efficient Solutions ◽  
Dynamic Features ◽  
Delay Constraint ◽  
Service Placement ◽  
Placement Algorithms ◽  
Capacity Modeling ◽  
The Cost

A vast range of sensors gather data about our environment, industries and homes. The great profit hidden in this data can only be exploited if it is integrated with relevant services for analysis and usage. A core concept of the Internet of Things targets this business opportunity through various applications. The virtualized and software-controlled 5G networks are expected to achieve the scale and dynamicity of communication networks required by Internet of Things (IoT). As the computation and communication infrastructure rapidly evolves, the corresponding substrate models of service placement algorithms lag behind, failing to appropriately describe resource abstraction and dynamic features. Our paper provides an extension to existing IoT service placement algorithms to enable them to keep up with the latest infrastructure evolution, while maintaining their existing attributes, such as end-to-end delay constraints and the cost minimization objective. We complement our recent work on 5G service placement algorithms by theoretical foundation for resource abstraction, elasticity and delay constraint. We propose efficient solutions for the problems of aggregating computation resource capacities and behavior prediction of dynamic Kubernetes infrastructure in a delay-constrained service embedding framework. Our results are supported by mathematical theorems whose proofs are presented in detail.

Joining Pre-existing International Production Networks: Implications for India's Economic Integration with East Asia

2014 ◽  
Vol 13 (2) ◽  
pp. 117-142
Author(s):  
Jeongmeen Suh ◽  
Jong Duk Kim
Keyword(s):  
Economic Integration ◽  
Multinational Firms ◽  
Cost Minimization ◽  
Policy Implications ◽  
Production Networks ◽  
Economic Data ◽  
International Production ◽  
Production Processes ◽  
Cost Minimization Problem ◽  
The Cost

This study provides a conceptual framework to explain the difficulties a late-follower country will need to surmount if it seeks to join pre-existing international production networks (IPNs). To address this problem, we consider the cost minimization problem that confronts multinational firms as they choose how to locate fragmented production processes across borders. By clarifying IPN-related costs, we describe the structural disadvantages that confront late-follower countries and provide several policy implications that may help these countries overcome their disadvantages through targeted efforts. We use our framework to guide our examination of economic data, to analyze the hurdles that limit India's participation in the East Asian IPNs.

Service Provisioning for Multi-source IoT Applications in Mobile Edge Computing

2022 ◽  
Vol 18 (2) ◽  
pp. 1-25
Author(s):  
Jing Li ◽  
Weifa Liang ◽  
Zichuan Xu ◽  
Xiaohua Jia ◽  
Wanlei Zhou
Keyword(s):  
Minimization Problem ◽  
Optimization Problems ◽  
Cost Minimization ◽  
Edge Computing ◽  
Service Provisioning ◽  
Mobile Edge Computing ◽  
Iot Applications ◽  
Iot Devices ◽  
Cost Minimization Problem ◽  
The Cost

We are embracing an era of Internet of Things (IoT). The latency brought by unstable wireless networks caused by limited resources of IoT devices seriously impacts the quality of services of users, particularly the service delay they experienced. Mobile Edge Computing (MEC) technology provides promising solutions to delay-sensitive IoT applications, where cloudlets (edge servers) are co-located with wireless access points in the proximity of IoT devices. The service response latency for IoT applications can be significantly shortened due to that their data processing can be performed in a local MEC network. Meanwhile, most IoT applications usually impose Service Function Chain (SFC) enforcement on their data transmission, where each data packet from its source gateway of an IoT device to the destination (a cloudlet) of the IoT application must pass through each Virtual Network Function (VNF) in the SFC in an MEC network. However, little attention has been paid on such a service provisioning of multi-source IoT applications in an MEC network with SFC enforcement. In this article, we study service provisioning in an MEC network for multi-source IoT applications with SFC requirements and aiming at minimizing the cost of such service provisioning, where each IoT application has multiple data streams from different sources to be uploaded to a location (cloudlet) in the MEC network for aggregation, processing, and storage purposes. To this end, we first formulate two novel optimization problems: the cost minimization problem of service provisioning for a single multi-source IoT application, and the service provisioning problem for a set of multi-source IoT applications, respectively, and show that both problems are NP-hard. Second, we propose a service provisioning framework in the MEC network for multi-source IoT applications that consists of uploading stream data from multiple sources of the IoT application to the MEC network, data stream aggregation and routing through the VNF instance placement and sharing, and workload balancing among cloudlets. Third, we devise an efficient algorithm for the cost minimization problem built upon the proposed service provisioning framework, and further extend the solution for the service provisioning problem of a set of multi-source IoT applications. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.

scholarly journals On the uniqueness of the solution of the cost minimization problem with generalized Sato production function

2021 ◽  
Vol 12 (1) ◽  
pp. 37-48
Author(s):  
Vedran Kojic ◽  
Zrinka Lukac ◽  
Krunoslav Puljic
Keyword(s):  
Production Function ◽  
Minimization Problem ◽  
Cost Minimization ◽  
Theory Of The Firm ◽  
Production Functions ◽  
Elasticity Of Substitution ◽  
Uniqueness Of The Solution ◽  
Cost Minimization Problem ◽  
The Cost ◽  
Standard Production

Whenever a firm is maximizing its profit, it necessarily has to minimize its cost. Thus, the cost minimization problem is one of the central problems in the theory of the firm. When presenting this problem, the majority of microeconomic textbooks use very well-known production functions, such as Leontief, Cobb-Douglas, or other CES production functions. The goal of this paper is to analyze the cost minimization problem with the generalized Sato production function. The generalized Sato production function is one of the non-standard production functions with variable elasticity of substitution. First, we show that the generalized Sato production function is continuous, strictly monotone, strictly quasiconcave and that a positive amount of output requires positive amounts of some of the inputs. Next, by using mathematical programming we show that the cost minimization problem with generalized Sato production function has a unique solution. This result is very important since it implies the existence of the corresponding cost function and conditional input demands.

Machining Cost Optimization Involving Shift and Overtime Work

2000 ◽  
Vol 122 (4) ◽  
pp. 790-794
Author(s):  
Esko Niemi
Keyword(s):  
Cost Minimization ◽  
Cost Optimization ◽  
Cutting Speed ◽  
Overtime Work ◽  
Long Run ◽  
Short Run ◽  
Cost Minimization Problem ◽  
Cost Parameters ◽  
The Cost ◽  
Tool Types

Minimization of machining cost as a function of cutting speed is examined taking into account the effect of shift and overtime work. The cost minimization problem is formulated as the minimization of the total cost of machining a given number of workpieces within a given time. Different types of costs of machining and determination of cost parameters in the long run and short run are discussed. The use of both one-tool type and several-tool types is considered. Characteristics of the solutions of the problem are examined in light of examples. [S1087-1357(00)02304-2]

GSS 2011 Linked with TIFF: Exploring the Cost of Child Care in Canada and the Use of the Child Care Tax Benefit

2019 ◽  
Vol 12 (1) ◽  
pp. 81-103
Author(s):  
Leanne Findlay ◽  
Dafna Kohen
Keyword(s):  
Child Care ◽  
General Social Survey ◽  
Cost Of Care ◽  
Indigenous Identity ◽  
Social Survey ◽  
The Cost ◽  
Care Costs ◽  
Compare And Contrast ◽  
Employment Characteristics ◽  
Different Sources

Affordability of child care is fundamental to parents’, in particular, women’s decision to work. However, information on the cost of care in Canada is limited. The purpose of the current study was to examine the feasibility of using linked survey and administrative data to compare and contrast parent-reported child care costs based on two different sources of data. The linked file brings together data from the 2011 General Social Survey (GSS) and the annual tax files (TIFF) for the corresponding year (2010). Descriptive analyses were conducted to examine the socio-demographic and employment characteristics of respondents who reported using child care, and child care costs were compared. In 2011, parents who reported currently paying for child care (GSS) spent almost $6700 per year ($7,500 for children age 5 and under). According to the tax files, individuals claimed just over $3900 per year ($4,700). Approximately one in four individuals who reported child care costs on the GSS did not report any amount on their tax file; about four in ten who claimed child care on the tax file did not report any cost on the survey. Multivariate analyses suggested that individuals with a lower education, lower income, with Indigenous identity, and who were self-employed were less likely to make a tax claim despite reporting child care expenses on the GSS. Further examination of child care costs by province and by type of care are necessary, as is research to determine the most accurate way to measure and report child care costs.

Cost-minimization analysis of drugs used in the treatment of Asthma and COPD diseases in India

2020 ◽  
Vol 15 ◽  
Author(s):  
Billu Payal ◽  
Anoop Kumar ◽  
Harsh Saxena
Keyword(s):  
Generic Drugs ◽  
Cost Minimization ◽  
Cost Savings ◽  
Chronic Obstructive ◽  
Pulmonary Medicine ◽  
Potential Cost ◽  
Maximum Cost ◽  
Cost Minimization Analysis ◽  
Cost Variation ◽  
The Cost

Background: Asthma and Chronic Obstructive Pulmonary Diseases (COPD) are well known respiratory diseases affecting millions of peoples in India. In the market, various branded generics, as well as generic drugs, are available for their treatment and how much cost will be saved by utilizing generic medicine is still unclear among physicians. Thus, the main aim of the current investigation was to perform cost-minimization analysis of generic versus branded generic (high and low expensive) drugs and branded generic (high expensive) versus branded generic (least expensive) used in the Department of Pulmonary Medicine of Era Medical University, Lucknow for the treatment of asthma and COPD. Methodology: The current index of medical stores (CIMS) was referred for the cost of branded drugs whereas the cost of generic drugs was taken from Jan Aushadi scheme of India 2016. The percentage of cost variation particularly to Asthma and COPD regimens on substituting available generic drugs was calculated using standard formula and costs were presented in Indian Rupees (as of 2019). Results: The maximum cost variation was found between the respules budesonide high expensive branded generic versus least expensive branded generic drugs and generic versus high expensive branded generic. In combination, the maximum cost variation was observed in the montelukast and levocetirizine combination. Conclusion: In conclusion, this study inferred that substituting generic antiasthmatics and COPD drugs can bring potential cost savings in patients.

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