In combinatorial solution spaces Iterated Local Search turned out to be exceptionally successful. The question arises: is the Iterated Local Search heuristic also able to improve the optimization process in real-valued solution spaces? This paper introduces a hybrid meta-heuristic based on Iterated Local Search and Powell’s optimization method combined with elements from stochastic search in re...

A dynamic facility layout problem (DFLP) is concerned with finding a set of facility layouts across multiple time periods that minimizes the total cost of material flows and rearrangement costs. Unlike other heuristic approaches that focus mainly on the searching aspect, this research takes another approach by streamlining the data structure of solution representation to improve the solution sw...

This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) are recognized as promising swarm intelligence methods due to their successful ability solve machine learning problems, especially problems. reviews all relevant literature meta-heuristic-based application...

Software systems evolve and change with time due to change in business needs with the result that at some stage, the original design and architecture descriptions may not give exact representation of the actual software system. Accurate understanding of software architecture is very important for software maintenance because it helps in estimating scope of change, re-usability, cost, and risk i...

In many meta-heuristics greedy choices are performed and usually measured by means of an immediate gain eventually leading to suboptimal choices. Usually, the measure of this gain as well as a mechanism to guide the choices given the evaluations is performed rather shortsighted. Therefore, especially in the artificial intelligence community researchers have thought about looking ahead (see, e.g...

A new meta-heuristic algorithm to find the minimum height for twodimensional strip rectangular packing problem is presented. This algorithm is mainly based on the heuristic recursive strategy and simulated annealing algorithm. The computational results on a class of benchmark problems have shown that this algorithm not only finds shorter height than known meta-heuristic but also runs in shorter...

Combinatorial optimization problems are those problems that have a finite set of possible solutions. The best way to solve a combinatorial optimization problem is to check all the feasible solutions in the search space. However, checking all the feasible solutions is not always possible, especially when the search space is large. Thus, many meta-heuristic algorithms have been devised and modifi...

In this paper, a hybrid gradient simulated annealing algorithm is guided to solve the constrained optimization problem. trying problems using deterministic, stochastic methods or hybridization between them, penalty function are most popular approach due their simplicity and ease of implementation. There many approaches handling existence constraints in The simulated-annealing (SA) one successfu...

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuin...