Unconstrained Gibbs Free Energy Minimization for Phase Equilibrium Calculations in Nonreactive Systems, Using an Improved Cuckoo Search Algorithm

2014 ◽  
Vol 53 (26) ◽  
pp. 10826-10834 ◽  
Author(s):  
Seif-Eddeen K. Fateen ◽  
Adrián Bonilla-Petriciolet
Keyword(s):  
Free Energy ◽  
Phase Equilibrium ◽  
Gibbs Free Energy ◽  
Energy Minimization ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Gibbs Free Energy Minimization ◽  
Improved Cuckoo Search Algorithm ◽  
Equilibrium Calculations

scholarly journals APPROACH TO A RELIABLE SOLUTION STRATEGY FOR PERFORMING PHASE EQUILIBRIUM CALCULATIONS USING MINLP OPTIMIZATION

2014 ◽  
Vol 44 (1) ◽  
pp. 63-70
Author(s):  
I. J. JEREZ ◽  
F. MUÑOZ ◽  
J. M. GOMEZ
Keyword(s):  
Free Energy ◽  
Phase Equilibrium ◽  
Gibbs Free Energy ◽  
Energy Minimization ◽  
Continuous Variables ◽  
Solution Strategy ◽  
Free Energy Minimization ◽  
Integer Variables ◽  
Gibbs Free Energy Minimization ◽  
Equilibrium Calculations

The objective of this contribution is to propose a reliable strategy to solver the problem of phase equilibrium calculations for non-ideal systems, using the Gibbs free energy minimization. This type of problem, using the Gibbs free energy minimization, is usually formulated as a Mixed Integer NonLinear Programming (MINLP) Optimization. This optimization problem allows the compositions to be associated with continuous variables, and the presence of phases in the equilibrium to be associated with the integer variables. The solution strategy proposes a bi-level approach. The first level combines a stochastic (Simulated Annealing – SA) and a local deterministic algorithm (Sequential Quadratic Programming – SQP), and solves a Non Linear Programming Problem (NLP). The continuous variables are considered at this level. The second level considers the integer variables. The advantage of this bilevel strategy lies in its easy implementation and in its proven efficiency to locate global optima with acceptable computational load. This article includes the study of the Water-Ethanol-Cyclohexane and Water-Ethanol-Glycerin systems. A comparative analysis was conducted using experimental data reported in published works and theoretical calculations by means of the Gamma-Phi classic method.

Coverage optimization of VLC in smart homes based on improved cuckoo search algorithm

2017 ◽  
Vol 116 ◽  
pp. 63-78 ◽  
Author(s):  
Geng Sun ◽  
Yanheng Liu ◽  
Ming Yang ◽  
Aimin Wang ◽  
Shuang Liang ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Smart Homes ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Coverage Optimization ◽  
Improved Cuckoo Search Algorithm

A solution method for treatment scheduling in rehabilitation hospitals with real-life requirements

2018 ◽  
Vol 30 (4) ◽  
pp. 367-386 ◽  
Author(s):  
Liyang Xiao ◽  
Mahjoub Dridi ◽  
Amir Hajjam El Hassani ◽  
Wanlong Lin ◽  
Hongying Fei
Keyword(s):  
Waiting Time ◽  
Programming Model ◽  
Search Algorithm ◽  
Real Life ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Mixed Integer ◽  
Solution Quality ◽  
Improved Cuckoo Search Algorithm ◽  
Rehabilitation Hospitals

Abstract In this study, we aim to minimize the total waiting time between successive treatments for inpatients in rehabilitation hospitals (departments) during a working day. Firstly, the daily treatment scheduling problem is formulated as a mixed-integer linear programming model, taking into consideration real-life requirements, and is solved by Gurobi, a commercial solver. Then, an improved cuckoo search algorithm is developed to obtain good quality solutions quickly for large-sized problems. Our methods are demonstrated with data collected from a medium-sized rehabilitation hospital in China. The numerical results indicate that the improved cuckoo search algorithm outperforms the real schedules applied in the targeted hospital with regard to the total waiting time of inpatients. Gurobi can construct schedules without waits for all the tested dataset though its efficiency is quite low. Three sets of numerical experiments are executed to compare the improved cuckoo search algorithm with Gurobi in terms of solution quality, effectiveness and capability to solve large instances.

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