scholarly journals Optimizing Capacity Assignment in Multiservice MPLS Networks

2017 ◽  
Vol 29 (1) ◽  
Author(s):  
Abdoul Rassaki ◽  
Andre Nel
Keyword(s):  
Programming Model ◽  
Minimum Cost ◽  
Lagrangean Relaxation ◽  
Telecommunication Networks ◽  
Common Trunk ◽  
Topology Optimisation ◽  
Capacity Assignment ◽  
Optimum Selection ◽  
Flow Assignment ◽  
Experimental Findings

The general Multiprotocol Label Switch (MPLS) topology optimisation problem is complex and concerns the optimum selection of links, the assignment of capacities to these links and the routing requirements on these links. Ideally, all these are jointly optimised, leading to a minimum cost network which continually meets given objectives on network delay and throughput. In practice, these problems are often dealt with separately and a solution iterated. In this paper, we propose an algorithm that computes the shortest routes, assigns optimal flows to these routes and simultaneously determines optimal link capacities. We take into account the dynamic adaptation of optimal link capacities by considering the same Quality of Service (QoS) measure used in the flow assignment problem in combination with a blocking model for describing call admission controls (CAC) in multiservice broadband telecommunication networks. The main goal is to achieve statistical multiplexing advantages with multiple traffic and QoS classes of connections that share a common trunk present. We offer a mathematical programming model of the problem and proficient solutions which are founded on a Lagrangean relaxation of the problem. Experimental findings on 2-class and 6-class models are reported.

scholarly journals A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianxun Cui ◽  
Shi An ◽  
Meng Zhao
Keyword(s):  
Flow Model ◽  
Time Window ◽  
Programming Model ◽  
Real Life ◽  
Minimum Cost ◽  
Emergency Evacuation ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Minimum Cost Flow ◽  
Cost Flow

During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR) function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented.

scholarly journals Minimum Cost Multiobjective Programming Model for Target Efficiency in Sample Selection

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yousaf Shad Muhammad ◽  
Saima Khan ◽  
Ijaz Hussain ◽  
Alaa Mohamd Shoukry ◽  
Sadaf Shamsuddin ◽  
...  
Keyword(s):  
Multiobjective Programming ◽  
Programming Model ◽  
Sample Selection ◽  
Minimum Cost ◽  
Fixed Cost ◽  
Optimal Sample ◽  
Proposed Model ◽  
Compromise Allocation ◽  
Goal Programming Model ◽  
The Cost

In this study, we developed a model which elaborates relationship among efficiency of an estimator and survey cost. This model is based on a multiobjective optimization programming structure. Survey cost and efficiency of related estimator(s) lie in different directions, i.e., if one increases, the other decreases. The model presented in this study computes cost for a desired level of efficiency on various characteristics (goals). The calibrated model minimizes the cost for the compromise optimal sample selection from different strata when characteristic j is subject to achieve at least 1−αj level of efficiency of its estimator. In the first step, the proposed model minimizes the variance for a fixed cost, and it then finds the rise in cost for an αj percent rise in efficiency of any characteristic j. The resultant model is a multiobjective compromise allocation goal programming model.

scholarly journals Optimization of Continuous Berth Scheduling by Taking into Account Double-Line Ship Mooring

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng Luo ◽  
Hongying Fei ◽  
Dana Sailike ◽  
Tingyi Xu ◽  
Fuzhi Huang
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Minimum Cost ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Double Line ◽  
Support Tool ◽  
Berth Scheduling ◽  
Operation Cost

“Double-Line Ship Mooring” (DLSM) mode has been applied as an initiative operation mode for solving berth allocation problems (BAP) in certain giant container terminals in China. In this study, a continuous berth scheduling problem with the DLSM model is illustrated and solved with exact and heuristic methods with an objective to minimize the total operation cost, including both the additional transportation cost for vessels not located at their minimum-cost berthing position and the penalties for vessels not being able to leave as planned. First of all, this problem is formulated as a mixed-integer programming model and solved by the CPLEX solver for small-size instances. Afterwards, a particle swarm optimization (PSO) algorithm is developed to obtain good quality solutions within reasonable execution time for large-scale problems. Experimental results show that DLSM mode can not only greatly reduce the total operation cost but also significantly improve the efficiency of berth scheduling in comparison with the widely used single-line ship mooring (SLSM) mode. The comparison made between the results obtained by the proposed PSO algorithm and that obtained by the CPLEX solver for both small-size and large-scale instances are also quite encouraging. To sum up, this study can not only validate the effectiveness of DLSM mode for heavy-loaded ports but also provide a powerful decision support tool for the port operators to make good quality berth schedules with the DLSM mode.

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.

Research on the Optimization and Adjustment for the Locomotive Overhaul Layout

2013 ◽  
Vol 401-403 ◽  
pp. 2105-2111
Author(s):  
Zhen Lv ◽  
Wei Dong Chen ◽  
Xiang Li Zou
Keyword(s):  
Objective Function ◽  
Optimization Algorithm ◽  
Programming Model ◽  
Minimum Cost ◽  
Layout Optimization ◽  
Railway Transportation ◽  
Coordinated Development ◽  
Financial Investment ◽  
Chinese Nation ◽  
Iterative Optimization Algorithm

In order to keep national economys sustainable, rapid and coordinated development, developing the railway is the strategic choice to realize the great rejuvenation of the Chinese nation. Through the optimization of productivity layout, optimize locomotives, locomotive maintenance equipment resources configuration, can not only improve the efficiency of railway transportation, but also reduce the national financial investment. This thesis studies the locomotive overhaul layout optimization adjustment method, established the locomotive overhaul layout optimization adjustment model and corresponding algorithm of the design model. Based on the analysis of the nature of the problem, makes the minimum cost as the objective function, a bi-level programming model is established, and by using iterative idea, design double iterative optimization algorithm to solve the bi-level programming model.

scholarly journals On Vehicle routing Problem using Mixed Integer Non-Linear Programming

2020 ◽  
pp. 32-34
Keyword(s):  
Linear Programming ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Minimum Cost ◽  
Mixed Integer ◽  
Routing Problem ◽  
Non Linear Programming ◽  
Electric Vehicle Charging ◽  
The Family ◽  
Non Linear

The family of (VRPs) has received remarkable attention in the field of combinatorial optimization after its introduction in the paper of Dantzig and Ramser. VRPs determine a set of vehicle routes in order to accomplish transportation requests at minimum cost. In this paper we develop a mixed-integer non-linear programming model for vrp and apply it in electric vehicle charging.

scholarly journals Cost-Minimized Diets For UiTM Perlis Students Using Goal And Linear Programming

2019 ◽  
Vol 14 (2) ◽  
pp. 230-239
Author(s):  
Nur Fatihah Fauzi ◽  
Rohana Alias ◽  
Nor Hayati Shafii
Keyword(s):  
Linear Programming ◽  
Goal Programming ◽  
Programming Model ◽  
Minimum Cost ◽  
Food Prices ◽  
Female Students ◽  
Male Students ◽  
Nutritional Requirements ◽  
Male And Female ◽  
Food Basket

Humans need to eat good and balanced nutritious diet that provides calories for energy requirements andnutrients for proper growth, repair and maintenance of the body tissue. Today, busy lifestyle habitsdrastically changed the pattern of eating where students are more likely to have irregular meal times andthe cost of food may be expensive for them. Therefore, this study is conducted to find the minimum costthat satisfies the daily nutrient requirements. A linear programming (LP) model and goal programming(GP) model are formulated where the objective function is the total cost of food. Food prices werecollected from selected cafés in UiTM Perlis and the recommended daily nutrient intakes of 19-29 yearsold, male and female were obtained from the Ministry of Health Malaysia. The sample used in thisresearch consists of 10 most frequently consumed food items as decision variables. QM for Windows V5was used to determine minimum cost that satisfies the nutritional requirements. LP results, the minimumcost for male students is RM9.88 and for female students is RM9.10. Based on the GP results, the cost isRM9.00 for both male and female students. It is evident from the results that GP has achieved theminimum cost and the food basket for male students consists of 410g of rice, 140g of chicken, 42.9g ofbroccoli and 252.7g of mushroom. Meanwhile, the food basket for female students consists of 429g ofrice, 113.4g of chicken, 37.44g of broccoli and 321.3g of mushroom. Keywords: Linear Programming Model, Goal Programming Model, Minimum Cost, Nutritional requirements, Optimization

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