The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

There are many numerous methods for solving large-scale problems in which some of them are very flexible and efficient in both linear and non-linear cases. League championship algorithm is such algorithm which may be used in the mentioned problems. In the current paper, a new play-off approach will be adapted on league championship algorithm for solving large-scale problems. The proposed algori...

Medical image segmentation identifies an area that should be analyzed later in the processing process, such as for disease recognition and classification. As search is reduced, this action allows faster computation analysis. We propose use of a heuristic red fox optimization algorithm (RFOA) medical paper. The heuristics’ operation was adapted to analysis two-dimensional images, with focus on e...

Time-dependent vehicle routing problem (TDVRP) is concerned with vehicle routing optimization in road networks with fluctuant link travel time. Firstly, Time-dependent functions about routing time indicator and routing threat indicator are introduced. Secondly, a time-dependent heuristic function including routing distance indicator, routing time indicator and routing threat indicator is constr...

Elements of statistics, computer science, and operations research are connected with optimization heuristics as the catalyst. Heuristic search is used as a basis for a maximum likelihood clustering algorithm and it is demonstrated that clustering can be used to improve heuristic search algorithm performance. An important problem is described, a neighborhood structure for the problem is provided...

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations ...

Planning Municipal Wireless Access Networks is a challenging task, since many optimization choices must be taken into account in large metropolitan areas and, in turn, the number of free variables is very large, on the order of several millions, if the position of wireless access points is to be optimized, as well as their connection to the backbone network. This paper formalizes the problem of...

A new population-based search algorithm called the Bees Algorithm (BA) is presented in this paper. The algorithm mimics the food foraging behavior of swarms of honey bees. This algorithm performs a kind of neighborhood search combined with random search and can be used for both combinatorial optimization and functional optimization and with good numerical optimization results. ABC is a meta-heu...

Decentralized supply chain management is found to be significantly relevant in today’s competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final produc...