Azala

Solution of Bin Packing Instances in Falkenauer T Class: Not So Hard

Gorde:
Argitaratua izan da:Algorithms vol. 18, no. 2 (2025), p. 115
Egile nagusia: Dósa, György
Beste egile batzuk: Éles, András, Goswami, Angshuman Robin, Szalkai, István, Tuza, Zsolt
Argitaratua:
MDPI AG
Gaiak:
Machine learning
Approximation
Algorithms
Packing problem
Combinatorial analysis
Logistics
Heuristic
Genetic algorithms
Optimization
Benchmarks
Heuristic methods
Sarrera elektronikoa:Citation/Abstract
Full Text + Graphics
Full Text - PDF
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100 1 |a Dósa, György  |u Mathematical Department, Faculty of Information Technology, University of Pannonia, 8200 Veszprém, Hungary; <email>goswami.angshuman.robin@mik.uni-pannon.hu</email> (A.R.G.); <email>szalkai.istvan@mik.uni-pannon.hu</email> (I.S.) 
245 1 |a Solution of Bin Packing Instances in Falkenauer T Class: Not So Hard 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a In this work, the Bin Packing combinatorial optimization problem is studied from the practical side. The focus is on the Falkenauer T benchmark class, which is a collection of 80 problem instances that are considered hard to handle algorithmically. Contrary to this widely accepted view, we show that the instances of this benchmark class can be solved relatively easily, without applying any sophisticated methods like metaheuristics. A new algorithm is proposed, which can operate in two modes: either using backtrack or local search to find optimal packing. In theory, both operating modes are guaranteed to find a solution. Computational results show that all instances of the Falkenauer T benchmark class can be solved in a total of 1.18 s and 2.39 s with the two operating modes alone, or 0.2 s when running in parallel. 
653 |a Machine learning 
653 |a Approximation 
653 |a Algorithms 
653 |a Packing problem 
653 |a Combinatorial analysis 
653 |a Logistics 
653 |a Heuristic 
653 |a Genetic algorithms 
653 |a Optimization 
653 |a Benchmarks 
653 |a Heuristic methods 
700 1 |a Éles, András  |u Department of Computer Science and Systems Technology, Faculty of Information Technology, University of Pannonia, 8200 Veszprém, Hungary; <email>eles.andras@mik.uni-pannon.hu</email> (A.É.); <email>tuza.zsolt@mik.uni-pannon.hu</email> (Z.T.) 
700 1 |a Goswami, Angshuman Robin  |u Mathematical Department, Faculty of Information Technology, University of Pannonia, 8200 Veszprém, Hungary; <email>goswami.angshuman.robin@mik.uni-pannon.hu</email> (A.R.G.); <email>szalkai.istvan@mik.uni-pannon.hu</email> (I.S.) 
700 1 |a Szalkai, István  |u Mathematical Department, Faculty of Information Technology, University of Pannonia, 8200 Veszprém, Hungary; <email>goswami.angshuman.robin@mik.uni-pannon.hu</email> (A.R.G.); <email>szalkai.istvan@mik.uni-pannon.hu</email> (I.S.) 
700 1 |a Tuza, Zsolt  |u Department of Computer Science and Systems Technology, Faculty of Information Technology, University of Pannonia, 8200 Veszprém, Hungary; <email>eles.andras@mik.uni-pannon.hu</email> (A.É.); <email>tuza.zsolt@mik.uni-pannon.hu</email> (Z.T.); HUN-REN Alfréd Rényi Institute of Mathematics, 1053 Budapest, Hungary 
773 0 |t Algorithms  |g vol. 18, no. 2 (2025), p. 115 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3170855236/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3170855236/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3170855236/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch