A Hybrid Shuffled Frog Leaping Algorithm for Solving No_Idle Permutation Flow Shop Scheduling Problems

Abstract

This paper presents a novel hybrid shuffled frog-leaping algorithm (HSFLA) for solving the no_idle permutation flow shop scheduling problems (NIFS) with the criterion to minimize the maximum completion time (makespan). First, the algorithm employs insert-neighborhood-based local search to enhance the searching ability. Second, it adopts roulette wheel selection operator to generate the global best frog in the early stage of the evolution which can expand the searching solution space. The experimental results show that the proposed algorithm is effective and efficient for different scale benchmarks of NIFS.

The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review

“…As a consequence of the continuous feature of SFLA, it is difficult to solve large-scale, complicated and combinatorial optimization problems (Li and Wang 2011). To handle these kinds of optimization problems and improve the performance, some previous works proposed different structures for modified SFLA (MSFLA).…”

“…To overcome the limitations of basic SFLA in the evolution phase and improving the memetic evolution process, it was recommended by Li and Wang (2011) to utilize local and global best information for frog leaping and transfer them between individual frogs.…”