Abstract
Number partitioning is a classic problem in artificial intelligence. And balanced multi-way number partitioning problem (BMNP) aims to partition a set of numbers into multiple subsets, such that (1) each subset contains the same number of numbers and (2) the subset sums are equal. The BMNP problem has various applications in real world scenarios, including task allocation, CPU scheduling, file placement in data center, multi-source data processing, etc. In this paper, we consider the problem of diversity-aware balanced multi-way number partitioning (DBMNP). DBMNP differs from BMNP, in that each number is associated with a type attribute. In addition to the two goals of BMNP, DBMNP also requires that the types of numbers in each subset are as diversified as possible. To solve the problem, we propose three heuristic algorithms to minimize the difference between subset sums and at the same time maximize diversify of each subset. Extensive experiments are conducted to evaluate the effectiveness of our proposed algorithms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
