High Speed Information Network Planning using Stochastic Optimization Method

2013 ◽  
Author(s):  
Ki-Sang Song ◽  
Arun K. Somani
Keyword(s):  
Stochastic Optimization ◽  
Network Design ◽  
Multimedia Information ◽  
High Speed ◽  
Minimum Cost ◽  
Optimization Method ◽  
Multimedia Communication ◽  
Network Design Problem ◽  
Information Network ◽  
Traffic Characteristics

From the 1994 CAIS Conference: The Information Industry in Transition McGill University, Montreal, Quebec. May 25 - 27, 1994.Broadband integrated services digital network (B-ISDN) based on the asynchronous transmission mode (ATM) is becoming reality to provide high speed, multi bit rate multimedia communications. Multimedia communication network has to support voice, video and data traffics that have different traffic characteristics, delay sensitive or loss sensitive features have to be accounted for designing high speed multimedia information networks. In this paper, we formulate the network design problem by considering the multimedia communication requirements. A high speed multimedia information network design alogrithm is developed using a stochastic optimization method to find good solutions which meet the Quality of Service (QoS) requirement of each traffic class with minimum cost.

APPLICATION OF THE JUMPING FROGS METHOD FOR THE OPTIMIZATION OF THREE-LEVEL PLANS OF A MULTIPLE FACTOR EXPERIMENT

2019 ◽  
pp. 35-42
Author(s):  
N. Koshevoy ◽  
E. Kostenko ◽  
V. Muratov
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
High Speed ◽  
Minimum Cost ◽  
Optimization Method ◽  
Experimental Designs ◽  
Minimal Cost ◽  
Taboo Search ◽  
Time Costs ◽  
The Cost

he planning of the experiment allows us to solve the problem of obtaining a mathematical model with minimal cost and time costs. The cost of implementing an experiment is significantly affected by the order of alternating levels of change in factors. Thus, it is required to find a procedure for the implementation of experiments that provides the minimum cost (time) for conducting a multivariate experiment. This task becomes especially relevant when studying long and expensive processes. The purpose of this article is the further development of the methodology of optimal planning of the experiment in terms of cost (time), which includes a set of methods for optimizing the plans of the experiment and hardware and software for their implementation. Object of study: optimization processes for the cost of three-level plans for multivariate experiments. Subject of research: optimization method for cost and time costs of experimental designs based on the use of the jumping frog method. Experimental research methods are widely used to optimize production processes. One of the main goals of the experiment is to obtain the maximum amount of information about the influence of the studied factors on the production process. Next, a mathematical model of the object under study is built. Moreover, it is necessary to obtain these models at the minimum cost and time costs. The design of the experiment allows you to get mathematical models with minimal cost and time costs. For this, a method and software were developed for optimizing three-level plans using the jumping frog method. Three-level plans are used in the construction of mathematical models of the studied objects and systems. An analysis is made of the known methods for the synthesis of three-level plans that are optimal in cost and time costs. The operability of the algorithm was tested when studying the roughness of the silicon surface during deep plasma-chemical etching of MEMS elements. Its effectiveness is shown in comparison with the following methods: swarm of particles, taboo search, branches and borders. Using the developed method and software for optimizing three-level plans using the jumping frog method, one can achieve high winnings compared to the initial experimental plan, optimal or close to optimal results compared to particle swarm, taboo search, branches and borders methods, and also high speed of solving the optimization problem in comparison with previously developed optimization methods for three-level experimental designs.

scholarly journals Transportation Network Design considering Morning and Evening Peak-Hour Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hua Wang ◽  
Gui-Yuan Xiao ◽  
Li-Ye Zhang ◽  
Yangbeibei Ji
Keyword(s):  
Network Design ◽  
Programming Model ◽  
Transportation Network ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Network Efficiency ◽  
Demand Distribution ◽  
Traffic Characteristics ◽  
Evening Peak

Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

scholarly journals Optimization of Multimodal Discrete Network Design Problems Based on Super Networks

2021 ◽  
Vol 11 (21) ◽  
pp. 10143
Author(s):  
Yaling Zhou ◽  
Chengxuan Cao ◽  
Ziyan Feng
Keyword(s):  
Network Design ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Minimum Cost ◽  
Network Design Problem ◽  
Equilibrium Constraints ◽  
Modal Interactions ◽  
Proposed Model ◽  
Flow Equilibrium ◽  
Discrete Network Design Problem

In this paper, we investigate the multimodal discrete network design problem that simultaneously optimizes the car, bus, and rail transit network, in which inter-modal transfers are achieved by slow traffic modes including walking and bike-sharing. Specifically, a super network topology is presented to signify the modal interactions. Then, the generalized cost formulas of each type of links in the super network are defined. And based on the above formulas a bi-objective programming model is proposed to minimize the network operation cost and construction cost with traffic flow equilibrium constraints, investment constraints and expansion constraints. Moreover, a hybrid heuristic algorithm that combines the minimum cost flow algorithm and simulated annealing algorithm is presented to solve the proposed model. Finally, the effectiveness of the proposed model and algorithm is evaluated through two numerical tests: a simple test network and an actual multimodal transport network.

scholarly journals Modeling the Service Network Design Problem in Railway Express Shipment Delivery

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 391 ◽  
Author(s):  
Siqi Liu ◽  
Boliang Lin ◽  
Jianping Wu ◽  
Yinan Zhao
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Theory And Practice ◽  
Network Design Problem ◽  
Service Network ◽  
Service Network Design ◽  
Train Services

As air pollution becomes increasingly severe, express trains play a more important role in shifting road freight and reducing carbon emissions. Thus, the design of railway express shipment service networks has become a key issue, which needs to be addressed urgently both in theory and practice. The railway express shipment service network design problem (RESSNDP) not only involves the selection of train services and determination of service frequency, but it is also associated with shipment routing, which can be viewed as a service network design problem (SNDP) with railway characteristics. This paper proposes a non-linear integer programming model (INLP) which aims at finding a service network and shipment routing plan with minimum cost while satisfying the transportation time constraints of shipments, carrying capacity constraints of train services, flow conservation constraint and logical constraints among decision variables. In addition, a linearization technique was adopted to transform our model into a linear one to obtain a global optimal solution. To evaluate the effectiveness and efficiency of our approach, a small trial problem was solved by the state-of-the-art mathematical programming solver Gurobi 7.5.2.

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