This paper aims at integrating machine learning techniques into meta-heuristics for solving
combinatorial optimization problems. Specifically, our study develops a novel efficient …

This paper proposes a total of nine algorithms to minimize the makespan for the hybrid
flowshop scheduling problem with sequence-dependent setup times. The first six algorithms …

The most efficient approximate procedures so far for the flowshop scheduling problem with
makespan objective–ie the NEH heuristic and the iterated greedy algorithm–are based on …

The technological advances recently brought to the manufacturing arena (collectively known
as Industry 4.0) offer huge possibilities to improve decision-making processes in the shop …

This paper presents the forecasting of Turkey's electricity domestic consumption using
hybrid algorithm, which bases on Ant Colony Optimization (ACO) and Iterated Local Search …

The no-wait flowshop scheduling problem (NWFSP) is a variant of the classical flowshop
scheduling problem in which the jobs must be processed without any interruption between …

In this paper, we advance the state of the art for solving the Permutation Flowshop
Scheduling Problem with total flowtime minimization. For this purpose, we propose a Biased …

The permutation flowshop scheduling problem is a widely studied combinatorial
optimization problem with several real-world applications. In this paper we address a green …

Abstract Iterated Local Search (ILS) is one of the most popular single-solution-based
metaheuristics. ILS is recognized by many authors as a relatively simple yet efficient …

In this paper we address the non-permutation flow shop scheduling problem, a more
general variant of the flow shop problem in which the machines can have different …