In this paper, a new hybrid metaheuristic algorithm based on the scatter search approach is developed to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the iN forward/backwar...

This work arises from the research of the Metaheuristics Network on the University Course Timetabling Problem. In a first phase straightforward implementations of different metaheuristics were compared on a common local search framework [4]. In a second phase problem specific knoweldge was exploited and several alternatives for local search and metaheuristics were considered. Many possibilities...

This paper presents two GRASP metaheuristic algorithms for the vehicle routing problem, considering the capacity and shared demand of the customers. In this paper the solution obtained is compared with a greedy solution and two hybrid solutions (greedy and random). The results obtained show that the GRASP algorithm obtains a better quality solution for this kind of problem.

Dynamic response of a structure is a remarkable characteristic which can be optimized (controlled) by imposing constraints on natural frequencies. But it is mentionable that size and shape optimization of trusses with multiple frequency constraints is a very non-linear and non-convex problem that may be converged to local optima when using meta-heuristic algorithms. To concur this problem, rese...

The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) metho...

In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorpora...

This paper describes a new metaheuristic for combinatorial optimisation problems with specific reference to the jobshop scheduling problem (JSP). A fuzzy greedy search algorithm (FGSA) which is a combination of a genetic algorithm (GA) and a greedy randomised adaptive search procedure (GRASP) is considered to solve the problem. The effectiveness and efficiency of the proposed hybrid method will...

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...

We proposed a population-based metaheuristic called the spy algorithm for solving optimization problems and evaluated its performance. The design of our ensures benefit exploration exploitation as well cooperative non-cooperative searches in each iteration. compared with genetic algorithm, improved harmony search, particle swarm on set non-convex functions that focus accuracy, ability detecting...