This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing strategies and genetic local search, aiming at a more flexible and effective exploration and exploitation in the search space of the complex problem to find more non-dominated solutions in the Pareto Front. Due to t...

Simulated annealing is a powerful stochastic search method, but it still has the disadvantage of blind search. Tabu search (TS) which can prevent cycling and enhance diversi/cation, is an adaptive strategy based on tabu list. By reasonably combining simulated annealing with TS, an e#ective hybrid algorithm for the problem of packing circles into a larger containing circle is presented. Based on...

We have developed a hybrid optimization algorithm for inversion of gravity data using a binary formulation. The new algorithm utilizes the Genetic Algorithm (GA) as a global search tool, while implementing Quenched Simulated Annealing (QSA) intermittently for local search. The hybrid has significantly decreased computational cost over GA or Simulated Annealing (SA) alone and has allowed for suc...

Hybrid sorting immune simulated annealing technique (HSISAT), a Meta heuristic is proposed for solving the multi objective flexible job-shop scheduling problem (FJSP). The major objectives are distributing the time of machines among the set of operations and scheduling them to minimize the criterion (makespan, total workload and maximum workload). The processing time is sorted for isolating the...

Memetic algorithms (MAs) are hybrid evolutionary algorithms (EAs) that combine global and local search by using an EA to perform exploration while the local search method performs exploitation. Combining global and local search is a strategy used by many successful global optimization approaches, and MAs have in fact been recognized as a powerful algorithmic paradigm for evolutionary computing....

This paper addresses the Vehicle Routing Problem with Delivery Time Cost. This problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. In this research, a hybrid metaheuristic approa...

<span lang="EN-US">In this paper, we consider the hybrid vehicle routing problem (HVRP) at which consumes two types of power: fuel and electricity. The aim is to minimize total cost travelling between customers, provided that each customer visited only once. departs from depot returns after completing whole route. This optimization solved using a modified simulated annealing (SA) heuristi...

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers...