A New Queuing Algorithm of Ophthalmic Hospital Beds Arrangement

2012 ◽  
Vol 433-440 ◽  
pp. 1971-1974 ◽  
Author(s):  
Ran Hu ◽  
Jing Shuang Hu ◽  
Ying Wu
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Waiting Time ◽  
Multi Objective ◽  
Hospital Beds ◽  
The Law ◽  
Ophthalmic Hospital

In this paper, we build a new queuing algorithm based on Multi-objective linear programming about the ophthalmic hospital sickbeds arrangement. In the new algorithm we divide the traditional queue into four subqueues depending on the different treatment of diseases and following the law of FCFS. We find a random day for reference and count the data of this day, and then we focus on the arrangement of the next day, which means to choose how many patients from each of the four subqueues to be settled into hospital in the next day. Considering the fair principle, the utilization of sickbeds, and the waiting time of the patients, we found an objective function with several constraint conditions to calculate the arrangement of the next day. In order to simplify the constraint conditions, we transfer the length of the queues into the waiting time of patients and finally get the result through programming by Lingo software.

scholarly journals Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems

2020 ◽  
pp. 1-14
Author(s):  
Sanjay Jain ◽  
Adarsh Mangal
Keyword(s):  
Linear Programming ◽  
Numerical Solution ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Simplex Algorithm ◽  
Multi Objective ◽  
Linear Objective Function ◽  
Gauss Elimination ◽  
Linear Programming Problems

In this research paper, an effort has been made to solve each linear objective function involved in the Multi-objective Linear Programming Problem (MOLPP) under consideration by AHA simplex algorithm and then the MOLPP is converted into a single LPP by using various techniques and then the solution of LPP thus formed is recovered by Gauss elimination technique. MOLPP is concerned with the linear programming problems of maximizing or minimizing, the linear objective function having more than one objective along with subject to a set of constraints having linear inequalities in nature. Modeling of Gauss elimination technique of inequalities is derived for numerical solution of linear programming problem by using concept of bounds. The method is quite useful because the calculations involved are simple as compared to other existing methods and takes least time. The same has been illustrated by a numerical example for each technique discussed here.

scholarly journals On multi-objective linear programming problems with inexact rough interval-fuzzy coefficients

2015 ◽  
Vol 14 (5) ◽  
pp. 5742-5758
Author(s):  
E. E. Ammar ◽  
M. L. Hussein ◽  
A. M. Khalifa
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Fuzzy Number ◽  
Linear Programming Problem ◽  
Solution Procedure ◽  
Modeling Framework ◽  
Multi Objective ◽  
Interval Solution ◽  
Linear Programming Problems ◽  
Rough Interval

This paper deals with a multi-objective linear programming problem with an inexact rough interval fuzzy coefficients IRFMOLP. This problem is considered by incorporating an inexact rough interval fuzzy number in both the objective function and constrains. The concept of "Rough interval" is introduced in the modeling framework to represent dualuncertain parameters. A suggested solution procedure is given to obtain rough interval solution for IRFLP(w) problem. Finally,two numerical example is given to clarify the obtained results in this paper.

scholarly journals Comments on Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems by Sanjay Jain and Adarsh Mangal

2020 ◽  
Vol 06 (09) ◽  
pp. 94-96
Author(s):  
Chandra Sen
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Simplex Method ◽  
Simplex Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Excellent Research ◽  
Gauss Elimination ◽  
Linear Programming Problems ◽  
Averaging Techniques

An excellent research contribution was made by Sanjay and Adarsh in using Gauss Elimination Technique and AHA simplex method for solving multi-objective optimization (MOO) problems. The method was applied for solving MOO problems using Chandra Sen's technique and several other averaging techniques. The formulation of multi-objective function in the averaging techniques was not perfect. The example was also not appropriate.

Grey-fuzzy solution for multi-objective linear programming with interval coefficients

2018 ◽  
Vol 8 (3) ◽  
pp. 312-327 ◽  
Author(s):  
Amin Mahmoudi ◽  
Mohammad Reza Feylizadeh ◽  
Davood Darvishi ◽  
Sifeng Liu
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Fuzzy Programming ◽  
Feasible Region ◽  
Grey Theory ◽  
Acceptable Solution ◽  
Content Type ◽  
Multi Objective ◽  
Interval Coefficients ◽  
Interactive Fuzzy Programming

Purpose The purpose of this paper is to propose a method for solving multi-objective linear programming (MOLP) with interval coefficients using positioned programming and interactive fuzzy programming approaches. Design/methodology/approach In the proposed algorithm, first, lower and upper bounds of each objective function in its feasible region will be determined. Afterwards using fuzzy approach, considering a membership function for each objective function and finally using grey linear programming, the solution for this problem will be obtained. Findings According to the presented example, in this paper, the proposed method is both simple in use and suitable for solving different problems. In the numerical example mentioned in this paper, the proposed method provides an acceptable solution for such problems. Practical implications As in most real-world situations, the coefficients of decision models are not known and exact. In this paper, the authors consider the model of MOLP with interval data, since one of the solutions to cover uncertainty is using interval theory. Originality/value Based on using grey theory and interactive fuzzy programming approaches, an appropriate method has been presented for solving MOLP problems with interval coefficients. The proposed method, against the complex methods, has less effort and offers acceptable solutions.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Solving Fully Fuzzy Multi-Objective Linear Programming Problems

2012 ◽  
Vol 3 (4) ◽  
pp. 1-6 ◽  
Author(s):  
M.Jayalakshmi M.Jayalakshmi ◽  
◽  
P.Pandian P.Pandian
Keyword(s):  
Linear Programming ◽  
Multi Objective ◽  
Linear Programming Problems

Developing Schedule With Linear Programming (Case Study: STTF II Project Komplek Sukamukti Banjaran)

2020 ◽  
Vol 4 (02) ◽  
pp. 34-45
Author(s):  
Naufal Dzikri Afifi ◽  
Ika Arum Puspita ◽  
Mohammad Deni Akbar
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Time Limit ◽  
Minimum Time ◽  
Service Cost ◽  
Trade Off ◽  
Overtime Work ◽  
The Cost

Shift to The Front II Komplek Sukamukti Banjaran Project is one of the projects implemented by one of the companies engaged in telecommunications. In its implementation, each project including Shift to The Front II Komplek Sukamukti Banjaran has a time limit specified in the contract. Project scheduling is an important role in predicting both the cost and time in a project. Every project should be able to complete the project before or just in the time specified in the contract. Delay in a project can be anticipated by accelerating the duration of completion by using the crashing method with the application of linear programming. Linear programming will help iteration in the calculation of crashing because if linear programming not used, iteration will be repeated. The objective function in this scheduling is to minimize the cost. This study aims to find a trade-off between the costs and the minimum time expected to complete this project. The acceleration of the duration of this study was carried out using the addition of 4 hours of overtime work, 3 hours of overtime work, 2 hours of overtime work, and 1 hour of overtime work. The normal time for this project is 35 days with a service fee of Rp. 52,335,690. From the results of the crashing analysis, the alternative chosen is to add 1 hour of overtime to 34 days with a total service cost of Rp. 52,375,492. This acceleration will affect the entire project because there are 33 different locations worked on Shift to The Front II and if all these locations can be accelerated then the duration of completion of the entire project will be effective

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

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