New binary marine predators optimization algorithms for 0–1 knapsack problems

Mohamed Abdel-Basset, Reda Mohamed, Ripon K. Chakrabortty, Michael Ryan, Seyedali Mirjalili

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Recently, a novel meta-heuristic algorithm known as the marine predators algorithm (MPA) has been proposed for solving continuous optimization problems. Despite the significant superiority of MPA in solving continuous problems, the algorithm is not applicable to binary problems. This work proposes a binary version of MPA for solving the 0–1 knapsack (KP01) problem. To develop the binary variant of MPA (BMPA), a wide range of V-Shaped and S-shaped transfer functions is investigated for mapping continuous values to binary. The performance of a binary algorithm is first shown to heavily rely on the selection of an appropriate transfer function on a specific dataset. The performance of the proposed BMPA algorithm is then tested on a set of KP01 problems and compared to a number of existing algorithms. The results demonstate the merits of the BMPAs proposed in this work.

Original languageEnglish
Article number106949
JournalComputers and Industrial Engineering
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • 0–1 knapsack problem
  • Algorithm
  • Artificial Intelligence
  • Benchmark
  • Binary optimization
  • Combinatorial optimization
  • Marine predators algorithm
  • Repair infeasible solutions

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