This research deals with a hybrid flow shop scheduling problem with parallel batching, machine eligibility, unrelated parallel machine, and different release dates to minimize the sum of the total weighted earliness and tardiness (ET) penalties. In parallel batching situation, it is supposed that number of machine in some stages are able to perform a certain number of jobs simultaneously. First...

This paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. The fuzzy set theory is applied to describe this situation. A novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. Due to the computational complexities, the prop...

The main purpose of this research is portfolio optimization in Tehran securities exchange using the black hole algorithm and the Gravitational Research algorithm. We also propose an algorithm named Hybrid Algorithm which combines the two algorithms above to cover the weaknesses of these two algorithms. Finally we compare the results with the Markowitz model and choose the optimal algorithm.<br ...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

The forward kinematics of the 6-6 leg parallel manipulator is solved using hybrid meta-heuristic techniques in which the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results are compared with the standard simulated annealing and genetic algorithm. It shows that the standard simulated annealing algorithm outperforms standard genetic algorithm in terms ...

this study presents the effects of project uncertainties on nonlinear time-cost tradeoff (tct) profile of real life engineering projects by the fusion of fuzzy logic and artificial neural network (ann) models with hybrid meta-heuristic (hmh) technique, abridged as fuzzy-ann-hmh. nonlinear time-cost relationship of project activities is dealt with ann models. ann models are then integrated with ...

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...

in this paper, matlab code for a recently developed meta-heuristic methodology, the vibrating particles system (vps) algorithm, is presented. the vps is a population-based algorithm which simulates a free vibration of single degree of freedom systems with viscous damping. the particles gradually approach to their equilibrium positions that are achieved from current population and historically b...