Evolutionary Particle Swarm Optimisation for Two Dimensional Bin Packing Problem

Ramakrishnan, Kumaran (2013) Evolutionary Particle Swarm Optimisation for Two Dimensional Bin Packing Problem. PhD thesis, Multimedia University.

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Official URL: http://library.mmu.edu.my/diglib/onlinedb/dig_lib....

Abstract

Swarm intelligence meta-heuristics are widely used in solving continuous optimisation problems. However application of swarm intelligence meta-heuristics to combinatorial optimisation problems is limited, especially to cutting and packing problem which is a core area of research for many decades. EPSO – Evolutionary Particle Swarm Optimisation is the hybrid version of the mainstream swarm intelligence meta-heuristic known as Particle Swarm Optimisation (PSO). The bin packing problem (BPP) is a classical combinatorial optimisation problem which has wide real-life applications: loading of boxes to pallets, trucks and containers, packing of box bases on shelves and other applications in the wood and metal industry. The non-oriented two-dimensional bin packing problem (NO-2DBPP) is a non-trivial variant of BPP where the objective is to allocate without overlapping but allowing the pieces to be rotated by 90 degree to a minimum number of bins. The focus of this thesis is to apply and investigate the efficiency of EPSO methodology for solving the NO2DBPP.

Item Type: Thesis (PhD)
Additional Information: Call No.: Q337.3 .R36 2013
Uncontrolled Keywords: Swarm intelligence
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 12 Sep 2017 16:26
Last Modified: 12 Sep 2017 16:26
URI: http://shdl.mmu.edu.my/id/eprint/6907

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