The bin packing problem (and its variant, the cutting stock problem) is among the most intensively studied combinatorial optimization problems. We present a library of computer codes, benchmark instances, and pointers to relevant articles for these two problems. The library is available at http://or.dei.unibo.it/library/bpplib. The computer code section includes twelve programs: seven are directly downloadable from the library page, while for the remaining five we provide addresses where they can be obtained or downloaded. Some of the codes for which we provide an original C++ implementation need an integer linear programming solver. For such cases, the library provides two versions: one that uses the commercial solver CPLEX, and one that uses the freeware solver SCIP. The benchmark section provides over six thousands instances (partly coming from the literature and partly randomly generated), together with the corresponding solutions. Instances that are difficult to solve to proven optimality are included. The library also includes a BibTeX file of more than 150 references on this topic and an interactive visual tool to manually solve bin packing and cutting stock instances. We conclude this work by reporting the results of new computational experiments on a number of computer codes and benchmark instances.
BPPLIB: a library for bin packing and cutting stock problems / Delorme, Maxence; Iori, Manuel; Martello, Silvano. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - 12(2018), pp. 235-250.
|Data di pubblicazione:||2018|
|Data di prima pubblicazione:||4-set-2017|
|Titolo:||BPPLIB: a library for bin packing and cutting stock problems|
|Autore/i:||Delorme, Maxence; Iori, Manuel; Martello, Silvano|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/s11590-017-1192-z|
|Codice identificativo ISI:||WOS:000425976100001|
|Codice identificativo Scopus:||2-s2.0-85028801305|
|Citazione:||BPPLIB: a library for bin packing and cutting stock problems / Delorme, Maxence; Iori, Manuel; Martello, Silvano. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - 12(2018), pp. 235-250.|
|Tipologia||Articolo su rivista|
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