In this paper, we consider a flow shop scheduling problem with availability constraints (FSSPAC) for the objective of minimizing the makespan. In such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. We proposed a mixed-integer linear programming (MILP) model for this problem which can generate non-permutation schedules. Furthermor...

Optimization of noisy non-linear problems plays a key role in engineering and design problems. These optimization problems can't be solved effectively by using conventional optimization methods. However, metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) seem very efficient to approach in these problems and became very popular. The efficiency of these ...

In this paper, the quantitative structure activity-relationship (QSAR) of the CCR2b receptor inhibitors was scrutinized. Firstly, the molecular descriptors were calculated using the Dragon package. Then, the stepwise multiple linear regressions (SW-MLR) and the genetic algorithm multiple linear regressions (GA-MLR) variable selection methods were subsequently employed to select and implement th...

If both Reference Station (RS) and navigational device in Differential Global Positioning System (DGPS) receive signals from the same satellite, RS Position Components Error (RPCE) can be used to compensate for navigational device error. This research used hybrid method for RPCE prediction which was collected by a low-cost GPS receiver. It is a combination of Genetic Algorithm (GA) computing an...

A novel hybrid genetic algorithm (GA) for jointly optimizing source and channel codes is presented in this paper. The algorithm first uses GA for the coarse search of source and channel codes. An iterative search is then followed for the refinement of the coarse search. The hybrid GA enhances the robustness of the design of source and channel codes. The distributed GA scheme can also be used in...

Abstract The author proposes a model evaluation based on the GA-SVM to better understand of company’s relationship and core competitiveness. system index is reduced by relative gray analysis, support vector machine optimized genetic algorithm, specific algorithm steps are introduced. Select models from top 100 enterprises in China’s construction industry 2020 published China Construction Indust...

Stock price prediction is considered a strategic and challenging issue in the stock markets. Considering complexity of market data fluctuations, improvement effective approaches for crucial essential task. Therefore, this study, new model based on “Adaptive Neuro-Fuzzy Inference System (ANFIS), Particle Swarm Optimization (PSO) Genetic Algorithm (GA)” employed to predict accurately. ANFIS has b...

This paper describes application of Genetic algorithm (GA) for design of network configuration and for learning of neural network. Design of network configuration is the first area for GA exercise in relation to neural network. The number of neurons in network and placement to the layers has big influence over effectivity of whole system. If we are able to formulate quality classification of de...