Hi Benmesbah Ouissem

You should first define your problem and decide which problem class it is associated with. If your problem is, for example, linear and in reasonable sizes, I suggest you to focus on exact solution approaches. You may develop a mathematical model and solve it using well-known solvers such as GUROBI or CPLEX.

If your problem is a mixed-integer programming problem such as assignment, knapscak or TSP, then you can consider heuristics. Typically, these problems are diffuclt to solve and since your problem is a difficult problem, heuristics are good options for you.

Then you can look at the literature for the exact and heuristic solution approaches developed for your problem class. There are many papers comparing the performances of different heuristics. Their results may help you to decide the best option for your problem.

You should first investigate methods with a solid theory behind it - metaheuristics are famous for NOT providing any guidelines, or for that matter any guarantees to find a satisfying answer. In any case, you should mention whatever you know about the problem, in order for any of us to provide pointers to the right way of modelling the problem, perhaps, and also what tools to use when trying to solve the problem you have.

By the way - Hill climbing is not a metaheuristic.

Thank you Mr Michael Patriksson and Mr Erdi Dasdemir for your answers,

Iam working on adaptive and context aware learning path generation, A learning path can be defined as a series of learning units leading to a particular learning outcome. Learning path adaptation problem

(LPA) concerns the dynamic generation of a personal optimal learning path for a learner. Since this problem is Combinatorial Optimization problem and NP-hard, heuristics and meta-heuristics are usually used to approximate its solutions, in particular Evolutionary Computation approaches (EC) as GA, ACO, PSO and Immune Algo. That's why i am asking for the way to select between the different meta heuristic algo?

thank you very much, but can you tell me please Whats are the latest meta heuristic algorithms proposed in last 1 to 2 years .

Thank you in advance

The selection between heuristics, meta-heuristics and evolutionary algorithms depends on your problem. Anyway, over the years, Differential Evolution (DE) and its improved variants, showed good performance in many optimization problems over many other Evolutionary Algorithms. My suggestions to you is to study your problem first, and then carefully select the most suitable method.

Thank you very much Mr Karam M Sallam and Mr Mohamed abdel-Basset for your share.

I agree with the answers that the metaheuristics should be selected according to the problem to be solved. In fact, the first thing to consider is that whether the optimization problem is continuous or combinatorial. If it is continuous, the good options are Particle Swarm Optimization, Differential Evolution, Evolution Strategies and their current variants. If it is combinatorial, you should consider using Ant Colony Optimization, Tabu Search, Genetic Algorithm, Simulated Annealing, Iterated Local Search, GRASP etc.

I should also mention that discrete versions of continuous algorithms exist and vice versa. But, in my opinion the first choice should be the original ones unless there are good reasons to use their transformed versions.