Preference-driven evolutionary metaheuristics for multiobjective combinatorial optimization

Hybrid metaheuristic algorithms for single and multi-objective 2d bin packing problem Beyaz, Muhammed; Coşar, Ahmet; Dökeroğlu, Tansel; Department of Computer Engineering (2015) 2D Bin packing problem (2DBPP) is an NP-hard combinatorial optimization problem. Objects with di erent width and length sizes are packed in order to minimize the number of unit-capacity bins according to an objective function. Single or multiobjective versions of this well-known industrial engineering problem can be faced frequently in real life situations. There have been several heuristics proposed for the solution of 2DBPP until now where it is not possible to find the exact solutions for large problem i...
On the balanced k-chinese postmen problems Limon, Yasemin; Azizoğlu, Meral; Department of Industrial Engineering (2015) In this thesis, we consider a k-Chinese Postmen Problem with the objective of minimizing total squared workloads. Our aim is to balance the workloads of the postmen, while maintaining low total workload. We develop an efficient subtour elimination constraint and incorporate it to our integer program. We develop exact and approximate solution procedures that run in exponential and polynomial time respectively. The results of our computational experiment reveal the satisfactory behaviors of our algorithms in ...
Exact decomposition algorithms for nonlinear location and hub location problems Gündoğdu, Emine; Gürel, Sinan; Department of Industrial Engineering (2018) Developing exact solution algorithms to solve difficult optimization problems is one of the most important subjects in the operations research literature. In this dissertation, we develop Benders decomposition based exact solution algorithms (BDTAs) for handling nonlinearity in three selected nonlinear integer location/hub location problems. The first and second problem include nonlinear capacity constraints, while in the last problem, both objective function and the capacity constraints are nonlinear. In o...
Optimization of non-uniform planar array geometry for direction of arrival estimation Birinci, Toygar; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2006) In this work, a novel method is proposed to optimize the array geometry for DOA estimation. The method is based on minimization of fine error variances with the constraint that the gross error probability is below a certain threshold. For this purpose, a metric function that reflects the gross and fine error characteristics of the array is offered. Theoretical analyses show that the minimization of this metric function leads to small DOA estimation error variance and small gross error probability. Analyses ...
Optimum design of 3-d irregular steel frames using ant colony optimization and harmony search algorithms Aydoğdu, İbrahim; Saka, Mehmet Polat; Tokdemir, Turgut; Department of Engineering Sciences (2010) Steel space frames having irregular shapes when subjected to lateral loads caused by wind or earthquakes undergo twisting as a result of their unsymmetrical topology. As a result, torsional moment comes out which is required to be resisted by the three dimensional frame system. The members of such frame are generally made out of steel I sections which are thin walled open sections. The simple beam theory is not adequate to predict behavior of such thin-walled sections under torsional moments due to the fact...

Citation Formats

F. S. Pamuk, “Preference-driven evolutionary metaheuristics for multiobjective combinatorial optimization,” Ph.D. - Doctoral Program, Middle East Technical University, 2001.