In this study, we propose a genetic algorithm (GA) for the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. The proposed GA employs a multi-chromosome solution ...

Stochastic nature of vessel arrivals and handling times adds to the complexity of the well-known NP-hard berth allocation problem. To aid real decision-making under customer differentiations, a dynamic stochastic model ...

This paper presents a differential evolution algorithm in order to find unique resonance frequencies of an electromagnetic target in the resonance scattering region. These frequencies are estimated from the roots of Laplace ...

In this paper, we investigate the use of a continuous algorithm for the no-idle permutation flowshop scheduling (NIPFS) problem with tardiness criterion. For this purpose, a differential evolution algorithm with variable ...

In this study we present a discrete artificial bee colony (DABC) algorithm to solve the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. In specific, our ...

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 ...

This paper extends the applications of differential evolution algorithms to the Median Cycle Problem. The median cycle problem is concerned with constructing a simple cycle composed of a subset of vertices of a mixed graph. ...

In this study we provide a Differential Evolution (DE) based heuristic to solve the Economic Lot Scheduling Problem (ELSP) under basic period approach. The problem is to find the best cyclic production schedule of n items ...

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 ...

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 ...