Abstract
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.
Highlights
Among the many variants and generalizations of the problem, the most intensively studied is probably the Cutting Stock Problem (CSP)
By replacing binary variables xij with a set of integer variables ξij (i = 1, . . . , u; j = 1, . . . , m) giving the number of items of type j packed into bin i, the CSP can be modeled by the ILP
As any instance of either problem can be transformed into an equivalent instance of the other, the same holds for the CSP
Summary
Among the many variants and generalizations of the problem, the most intensively studied is probably the Cutting Stock Problem (CSP). The BPPLIB provides twelve computer codes of different types for the exact solution of the BPP and the CSP. The choice of such codes was motivated by a number of properties: historical relevance, efficiency, reliability, and availability of the corresponding computer codes. SCIP-BP: freeware SCIP C code for a branch-and-price BPP algorithm based on the classical Ryan and Foster [30] branching rule and available at the SCIP web page. This code is only effective for instances with small number of item types and low item multiplicity.
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