A hybrid particulate swarm optimization (hybrid) combination of an algorithm the particle and a variable neighborhood search is proposed for multi-objective permutation flow shop scheduling problem (PFSP) with smallest cumulative completion time total time. Algorithm (HPSO) applied to maintain fair centralized decentralized search. The Nawaz-Enscore-Ham )NEH) heuristic in this used initialize p...

Two-sided assembly lines are designed to produce large and complex products, where workers can perform on both sides at the same time. This paper establishes a mathematical model for multi-objective two-sided line balancing problems with additional constraints (MOATALBP). The considers workers’ skill balance of line, aimings maximize efficiency minimize cost smoothness index. A harmony search a...

Analysis of 132 group A streptococcal (GAS) isolates from 151 invasive episodes, including streptococcal toxic shock syndrome (STSS), from 1983 to 1995 showed great genetic variation by use of T serotyping in combination with restriction fragment length polymorphism. In contrast, genetically homogenous T1M1 isolates appeared in epidemic patterns with significantly increased risk of STSS. The sp...

Mobile Ad-hoc Networks (MANETs) are composed of a set of communicating devices which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenario, broadcasting becomes an operation of tremendous importance for the own existence and operation of the network. Optimizing a broadcasting strategy in MANETs is a multiobjective problem accounting for three goals: re...

In this paper, we describe a multi-objective evolutionary algorithm, that uses clustering selection and does not need any additional parameter like others. It clusters the population into a exible number of clusters employing x-means from [Pelleg and Moore, 2000]. First, the selective tness is assigned to clusters and in second place to individuals of clusters. We show three hybrid variants inc...

We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multiobjective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, a...

Unlike the Newsvendor model, a system based on lateral transshipments allows the unsold inventories to be moved from locations with surplus inventory to fulfill more unmet demands at stocked out locations. Both models were thoroughly studied and researches were usually confined to cost minimization or profit maximization. In this paper, we proposed a more realistic multiobjective study of both ...

Multiobjective cellular genetic algorithms (MOcGAs) are variants of evolutionary computation algorithms by organizing the population into grid structures, which are usually 2D grids. This paper proposes a new MOcGA, namely cosine multiobjective cellular genetic algorithm (C-MCGA), for continuous multiobjective optimization. The CMCGA introduces two new components: a 3D grid structure and a cosi...

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral Transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-l...