[PDF] Top 20 Adaptive Heterogeneous Multi-Population Cultural Algorithm

... Memetic Algorithm (MA) has been proposed to solve Job Shop Scheduling ...proposed algorithm has been applied on the well-known benchmark of classical Job Shop Scheduling Problems ...Genetic Algorithm ... See full document

... are population space, belief space and a protocol that defines the relationship between the population and the belief ...space. Population space can be modeled based on any population-based ... See full document

... dierent cultural algorithms, they do not communicate directly with each other, so to solve this problem multi-population cultural algorithms (MPCA) was ...of population over ...proposed ... See full document

... other algorithm. Zheng H. Q. et al. [5] designed a self-adaptive step cuckoo search algorithm (ASCS) by introducing the mechanism of the self-adaptive ...the algorithm. Cuckoo search ... See full document

... a multi-population adaptive version of inflationary differential evolution ...evolution algorithm (IDEA) combines basic differential evolution (DE) with some of the restart and local search ... See full document

... Elitism guarantees that the evolutionary algorithm will converge. Hence, once a global optimum basin is discovered, the algorithm will converge to that basin. However, the chances of converging to a local ... See full document

... metaheuristic algorithm to solve the Multi-Depot Vehicle Routing Problem with a Heterogeneous Fleet ...genetic algorithm, which generates an initial population with heuristic solutions ... See full document

... a Multi-Population Inflationary Differ- ential Evolution algorithm with Adaptive Local Restart is pre- sented and extensively tested over more than fifty test functions from the CEC 2005, CEC ... See full document

... one-buyer, multi-vendor, coordination model with a vendor selection problem in a centralized supply ...a multi-objective mixed integer nonlinear mathematical ...(SS), population based Harmony Search ... See full document

... In genetic algorithms, crossover is a genetic operator used to vary the programming of a chromosome or chromosomes from one generation to the next. It is analogous to reproduction and biological crossover, upon which ... See full document

... Genetic Algorithm (HIGA) Istin et ...the population of an EA. These estimates of population density can be used in both mating selection and environmental ...the population are assigned higher ... See full document

... Genetic Algorithm (AGA) is the proposed algorithm to solve distribution ...parameter population size and the number of ...classic algorithm is the parameter Cr and Mr functioning as ... See full document

... • Digalakis and Margaritis[34] proposed an MPCA called the parallel co-operating cultural algorithm (PARCA). The PARCA consists of several sub-components and each of the them runs a CA with different ... See full document

... Evolutionary optimization has achieved great success on many numerical and combinatorial optimization problems in recent years [1]. However classical evolutionary algorithms (EAs) often lose their efficacy and advantages ... See full document

... 165 Simulations results indicate that using conservative and easy backfilling combine in backfilling procedure shows better results in comparison to non-adaptive algorithm. K.- C. Huang, H.-Y. Chang [7] ... See full document

... our Multi-Population Cultural Algorithm, we have made use of the game theory ...of cultural algorithms which resembles very much with human culture and nature, so we have also ... See full document

... However, the practical applications of elastically homoge- nous composites are rather limited, because the materials with elastic modulus close to SMA could not elongate elasti- cally beyond 1.0% and superelastic effect ... See full document

... generation heterogeneous wireless networks (HWNs) will integrate various wireless access technologies, such as cellular networks, wireless local area network (WLAN), and Worldwide Interoperability for Microwave ... See full document

... efficient population-based ...a population methodology lies in the ease of integration with multi-objective strategies, which allow introducing practical aspects, such as profit, fuel consumption and ... See full document

... scheduling algorithm to improve MapReduce performance in an unbalanced ...scheduling algorithm where tasks are assigned to those nodes whose resources cannot be fully ...LBVP algorithm, this strategy ... See full document