In this paper, we present a discrete artificial bee colony algorithm to solve the no-idle permutation flowshop scheduling problem with the total tardiness criterion. The no-idle permutation flowshop problem is a variant ...

This paper presents two meta-heuristic algorithms to solve the quadratic assignment problem. The iterated greedy algorithm has two main components, hich are destruction and construction procedures. The algorithm starts ...

In this study, a general variable neighborhood search (GVNS) is presented to solve no-idle permutation flowshop scheduling problem (NIPFS), where idle times are not allowed on machines. GVNS is a metaheuristic, where inner ...

In this paper, we present a variable iterated greedy algorithm where its parameters (basically destruction size and probability of whether or not to apply the iterated greedy algorithm to an individual) are optimized by ...

This paper proposes a hybrid particle swarm optimization (PSO) algorithm for solving the job-shop scheduling problem with fuzzy processing times. The objective is to minimize the maximum fuzzy completion time, i.e., the ...

In this paper, a discrete artificial bee colony (DABC) algorithm is proposed to solve the lot-streaming flow shop scheduling problem with the criterion of total weighted earliness and tardiness penalties under both the ...

Obtaining an optimal solution for a permutation flowshop scheduling problem with the total flowtime criterion in a reasonable computational timeframe using traditional approaches and optimization tools has been a challenge. ...

In this paper, a local-best harmony search (HS) algorithm with dynamic sub-harmony memories (HM), namely DLHS algorithm, is proposed to minimize the total weighted earliness and tardiness penalties for a lot-streaming flow ...

In this paper, the dynamic multi-swarm particle swarm optimizer (DMS-PSO) is improved by hybridizing it with the harmony search (HS) algorithm and the resulting algorithm is abbreviated as DMS-PSO-HS. We present a novel ...

Differential evolution (DE) has attracted much attention recently as an effective approach for solving numerical optimization problems. However, the performance of DE is sensitive to the choice of the mutation strategy and ...