Solving for nonlinear integer programming problem using genetic algorithm and its application

2002 ◽  
Author(s):  
T. Yokota ◽  
M. Gen
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Programming Problem ◽  
Nonlinear Integer Programming ◽  
Integer Programming Problem

scholarly journals Planning of Aircraft Fleet Maintenance Teams

Aerospace ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 140
Author(s):  
Duarte P. Pereira ◽  
Isaias L. R. Gomes ◽  
Rui Melicio ◽  
Victor M. F. Mendes
Keyword(s):  
Information System ◽  
Integer Programming ◽  
Positive Integer ◽  
Programming Problem ◽  
Nonlinear Integer Programming ◽  
Mathematical Programming Problem ◽  
Aircraft Maintenance ◽  
Integer Programming Problem ◽  
Integer Variables ◽  
Support Information

This paper addresses a support information system for the planning of aircraft maintenance teams, assisting maintenance managers in delivering an aircraft on time. The developed planning of aircraft maintenance teams is a computer application based on a mathematical programming problem written as a minimization one. The initial decision variables are positive integer variables specifying the allocation of available technicians by skills to maintenance teams. The objective function is a nonlinear function balancing the time spent and costs incurred with aircraft fleet maintenance. The data involve technicians’ skills, hours of work to perform maintenance tasks, costs related to facilities, and the aircraft downtime cost. The realism of this planning entails random possibilities associated with maintenance workload data, and the inference by a procedure of Monte Carlo simulation provides a proper set of workloads, instead of going through all the possibilities. The based formalization is a nonlinear integer programming problem, converted into an equivalent pure linear integer programming problem, using a transformation from initial positive integer variables to Boolean ones. A case study addresses the use of this support information system to plan a team for aircraft maintenance of three lines under the uncertainty of workloads, and a discussion of results shows the serviceableness of the proposed support information system.

Chaotic Genetic Algorithm for Mixed Integer Programming Problem

2014 ◽  
Vol 651-653 ◽  
pp. 2273-2277
Author(s):  
Ya Ming Wang ◽  
Z. Zhang ◽  
Jun Bao Zheng ◽  
L.L. Tong
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Programming Problem ◽  
Mixed Integer Programming ◽  
Stability And Convergence ◽  
Mixed Integer ◽  
Search Process ◽  
Integer Programming Problem ◽  
Genetic Search ◽  
Mixed Integer Programming Problem

This paper proposed a chaotic genetic algorithm (CGA) to solve the mixed integer programming problem (MIPP). The basic idea of this algorithm is to overcome the deficiency of genetic algorithm (GA) by introducing chaotic disturbances into the genetic search process. Two typical MIPP problems are used to evaluate the performances of the proposed CGA. Experimental results show that performances of the algorithm have been improved by the chaotic disturbances, such as, search ability, precision, stability and convergence speed or calculation efficiency. The proposed CGA algorithm is suitable for solving complicated practical MIPP problem.

scholarly journals Reduction of dimensionality in dynamic programming-based solution methods for nonlinear integer programming

1988 ◽  
Vol 11 (4) ◽  
pp. 811-814
Author(s):  
Balasubramanian Ram ◽  
A. J. G. Babu
Keyword(s):  
Dynamic Programming ◽  
Integer Programming ◽  
Programming Problem ◽  
Nonlinear Integer Programming ◽  
Integer Programming Problem ◽  
Reduction Of Dimensionality ◽  
Single Constraint ◽  
Solution Methods ◽  
Dynamic Programming Problem ◽  
Constraint Problem

This paper suggests a method of formulating any nonlinear integer programming problem, with any number of constraints, as an equivalent single constraint problem, thus reducing the dimensionality of the associated dynamic programming problem.

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