Performance Comparison of Cuckoo Search Algorithm to Solve the Hybrid Flow Shop Scheduling Benchmark Problems with Makespan Criterion

Marichelvam M. K., TOSUN Ö.

INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH, cilt.7, sa.2, ss.1-14, 2016 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 2
  • Basım Tarihi: 2016
  • Doi Numarası: 10.4018/ijsir.2016040101
  • Dergi Adı: INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.1-14
  • Anahtar Kelimeler: Cuckoo Search Algorithm (CSA), Hybrid Flow Shop (HFS), Makespan, Scheduling, PARTICLE SWARM OPTIMIZATION, HEURISTIC ALGORITHMS, GENETIC ALGORITHM, IMMUNE ALGORITHM, BOUND ALGORITHM, 2-STAGE, SYSTEM, BRANCH, SETUP, TIMES
  • Akdeniz Üniversitesi Adresli: Evet

Özet

In this work, the performance of cuckoo search algorithm (CSA) is measured solving the multistage hybrid flow shop (HFS) scheduling problems with parallel machines. The objective is the minimization of makespan. The HFS scheduling problems are proved to be strongly non-deterministic polynomial time-hard (NP-hard). Proposed CSA algorithm has been tested on benchmark problems addressed in the literature against other well-known algorithms. The results are presented in terms of percentage deviation (PD) of the solution from the lower bound. The results indicate that the proposed CSA algorithm is quite effective in reducing makespan because average PD is observed as 1.531, whereas the next best algorithm has result of average PD of 2.295 which is in general nearly 50% worse and other algorithms start from 3.833.