Multi-objective feasibility enhanced particle swarm optimization

Date

2018-12-02

Author

Hasanoglu, Mehmet Sinan
Dölen, Melik

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

259
views

0
downloads

This article introduces a new method entitled multi-objective feasibility enhanced partical swarm optimization (MOFEPSO), to handle highly-constrained multi-objective optimization problems. MOFEPSO, which is based on the particle swarm optimization technique, employs repositories of non-dominated and feasible positions (or solutions) to guide feasible particle flight. Unlike its counterparts, MOFEPSO does not require any feasible solutions in the initialized swarm. Additionally, objective functions are not assessed for infeasible particles. Such particles can only fly along sensitive directions, and particles are not allowed to move to a position where any previously satisfied constraints become violated. These unique features help MOFEPSO gradually increase the overall feasibility of the swarm and to finally attain the optimal solution. In this study, multi-objective versions of a classical gear-train optimization problem are also described. For the given problems, the article comparatively evaluates the performance of MOFEPSO against several popular optimization algorithms found in the literature.

Subject Keywords

Management Science and Operations Research, Industrial and Manufacturing Engineering, Control and Optimization, Applied Mathematics, Computer Science Applications

URI

https://hdl.handle.net/11511/42570

Journal

ENGINEERING OPTIMIZATION

DOI

https://doi.org/10.1080/0305215x.2018.1431232

Collections

Department of Mechanical Engineering, Article

Suggestions

OpenMETU
Core

Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm Hasançebi, Oğuzhan (Informa UK Limited, 2014-01-02) This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang-big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of St...
Optimization of truss bridges within a specified design domain using evolution strategies Hasançebi, Oğuzhan (Informa UK Limited, 2007-09-01) This article reports and investigates the application of evolution strategies (ESs) to optimize the design of truss bridges. This is a challenging optimization problem associated with mixed design variables, since it involves identification of the bridge's shape and topology configurations in addition to the sizing of the structural members for minimum weight. A solution algorithm to this problem is developed by combining different variable-wise versions of adaptive ESs under a common optimization routine. ...
A new multiobjective simulated annealing algorithm Tekinalp, Ozan (Springer Science and Business Media LLC, 2007-09-01) A new multiobjective simulated annealing algorithm for continuous optimization problems is presented. The algorithm has an adaptive cooling schedule and uses a population of fitness functions to accurately generate the Pareto front. Whenever an improvement with a fitness function is encountered, the trial point is accepted, and the temperature parameters associated with the improving fitness functions are cooled. Beside well known linear fitness functions, special elliptic and ellipsoidal fitness functions,...
Dissimilarity maximization method for real-time routing of parts in random flexible manufacturing systems Saygin, C; Kilic, SE (Springer Science and Business Media LLC, 2004-04-01) This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is...
Effective optimization with weighted automata on decomposable trees Ravve, E. V.; Volkovich, Z.; Weber, Gerhard Wilhelm (Informa UK Limited, 2014-01-02) In this paper, we consider quantitative optimization problems on decomposable discrete systems. We restrict ourselves to labeled trees as the description of the systems and we use weighted automata on them as our computational model. We introduce a new kind of labeled decomposable trees, sum-like weighted labeled trees, and propose a method, which allows us to reduce the solution of an optimization problem, defined in a fragment of Weighted Monadic Second Order Logic, on such a tree to the solution of effec...

Citation Formats

M. S. Hasanoglu and M. Dölen, “Multi-objective feasibility enhanced particle swarm optimization,” ENGINEERING OPTIMIZATION, pp. 2013–2037, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42570.