Statistical mechanics analysis of generalized multi-dimensional knapsack problems

نویسندگان

چکیده

Abstract Knapsack problem (KP) is a representative combinatorial optimization that aims to maximize the total profit by selecting subset of items under given constraints on weights. In this study, we analyze generalized version KP, which termed multidimensional knapsack (GMDKP). As opposed basic GMDKP allows multiple choices per item type weight constraints. Although several efficient algorithms are known and properties their solutions have been examined significant extent for KPs, there paucity studies solution GMDKP. To gain insight into problem, assess typical achievable limit random ensemble using replica method. Our findings summarized as follows: (1) when profits types normally distributed, grows in leading order with respect number maximum x max increases while it depends only sub-leading if constant among types. (2) A greedy-type heuristic can find nearly optimal whose lower than value low computational cost. (3) The difference from be improved algorithm based cavity Extensive numerical experiments support these findings.

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ژورنال

عنوان ژورنال: Journal of Physics A

سال: 2022

ISSN: ['1751-8113', '1751-8121']

DOI: https://doi.org/10.1088/1751-8121/ac8381