scholarly journals Fractional programming approach to a cost minimization problem in electricity market

2019 ◽  
Vol 29 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Tatiana Gruzdeva ◽  
Rentsen Enkhbat ◽  
Natsagdorj Tungalag
Keyword(s):  
Minimization Problem ◽  
Electricity Market ◽  
Optimization Problem ◽  
Cost Minimization ◽  
Real Data ◽  
Identification Problem ◽  
Programming Approach ◽  
Cost Minimization Problem ◽  
Total Average Cost ◽  
Total Average

This paper was motivated by a practical optimization problem that appeared in electricity market of Mongolia. We consider the total average cost minimization problem of power companies of the Ulaanbaatar city. By solving an identification problem, we developed a fractional model that quite adequately represents the real data. The obtained problem turned out to be a fractional minimization problem over a box constraint, and to solve it, we propose a method that employs the global search theory for d.c. minimization.

scholarly journals Energy Cost Minimization in Heterogeneous Cellular Networks with Hybrid Energy Supplies

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Bang Wang ◽  
Qiao Kong ◽  
Qiang Yang
Keyword(s):  
Energy Consumption ◽  
Cellular Networks ◽  
Minimization Problem ◽  
Energy Cost ◽  
Cost Minimization ◽  
Energy Allocation ◽  
Green Energy ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Cost Minimization Problem

The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.

The multiple container loading cost minimization problem

2011 ◽  
Vol 214 (3) ◽  
pp. 501-511 ◽  
Author(s):  
Chan Hou Che ◽  
Weili Huang ◽  
Andrew Lim ◽  
Wenbin Zhu
Keyword(s):  
Minimization Problem ◽  
Cost Minimization ◽  
Container Loading ◽  
Cost Minimization Problem

The train fueling cost minimization problem with fuzzy fuel prices

2012 ◽  
Vol 26 (1-2) ◽  
pp. 249-267 ◽  
Author(s):  
Xiang Li ◽  
Chen-Fu Chien ◽  
Lixing Yang ◽  
Ziyou Gao
Keyword(s):  
Minimization Problem ◽  
Cost Minimization ◽  
Fuel Prices ◽  
Cost Minimization Problem

scholarly journals Method of substantiation of risks insurance of a classification society related to the vendors certification

2018 ◽  
pp. 136-146
Author(s):  
V.O. Lyubchenko ◽  
M.Ya. Postan
Keyword(s):  
Optimization Problem ◽  
Quality Level ◽  
Quality Service ◽  
Safe Operation ◽  
Methodical Approach ◽  
Total Average Cost ◽  
Total Average ◽  
Classification Society

In our paper, the methodical approach is proposed for risks minimization of classification society (CS) related to providing the low quality service by recognized vendors. For example, above vendors provide measurement of residual thicknesses of hull, radio expertise, underwater observations, etc. Safe operation of a ship is immediately determined by qualitative and reliable action of vendors. The method is worked out for optimization of  quality level of services providing  to CS by the vendors which allows us to assess reliability and qua-lity of vendors’ work, and the methodical approach for expediency of risks    insurance determination is proposed, as well. This methodical approach is based on the methods of mathematical reliability theory and evaluation of fai-lures probabilities of some subsystems of ship under operation. It is assumed that quality of vendors work is determined by the volumes of works for each subsystem. The optimization problem is formulated for determination of these volumes which minimize the total average cost for ship observation  by vendors and liquidation of failures sequences. The criterion of insurance expediency  of  failures risk  for the ship under operation (between two neighbor examinations) is formulated. The method is illustrated by numerical results.

scholarly journals Collaborative Computation Offloading and Resource Allocation in Cache-Aided Hierarchical Edge-Cloud Systems

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1430 ◽  
Author(s):  
Yanwen Lan ◽  
Xiaoxiang Wang ◽  
Chong Wang ◽  
Dongyu Wang ◽  
Qi Li
Keyword(s):  
Resource Allocation ◽  
Optimization Problem ◽  
Cost Minimization ◽  
Linear Optimization ◽  
Computation Offloading ◽  
Mixed Integer ◽  
Service Delay ◽  
Mixed Integer Nonlinear Optimization ◽  
Cost Minimization Problem ◽  
Computational Resources

The hierarchical edge-cloud enabled paradigm has recently been proposed to provide abundant resources for 5G wireless networks. However, the computation and communication capabilities are heterogeneous which makes the potential advantages difficult to be fully explored. Besides, previous works on mobile edge computing (MEC) focused on server caching and offloading, ignoring the computational and caching gains brought by the proximity of user equipments (UEs). In this paper, we investigate the computation offloading in a three-tier cache-assisted hierarchical edge-cloud system. In this system, UEs cache tasks and can offload their workloads to edge servers or adjoining UEs by device-to-device (D2D) for collaborative processing. A cost minimization problem is proposed by the tradeoff between service delay and energy consumption. In this problem, the offloading decision, the computational resources and the offloading ratio are jointly optimized in each offloading mode. Then, we formulate this problem as a mixed-integer nonlinear optimization problem (MINLP) which is non-convex. To solve it, we propose a joint computation offloading and resource allocation optimization (JORA) scheme. Primarily, in this scheme, we decompose the original problem into three independent subproblems and analyze their convexity. After that, we transform them into solvable forms (e.g., convex optimization problem or linear optimization problem). Then, an iteration-based algorithm with the Lagrange multiplier method and a distributed joint optimization algorithm with the adoption of game theory are proposed to solve these problems. Finally, the simulation results show the performance of our proposed scheme compared with other existing benchmark schemes.

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