Hyper-heuristics are easy-to-implement emerging search and optimisation strategies which have been used instead of meta-heuristics for providing higher level generalized structures to solve mainly combinatorial optimisation problems. The motivation behind them is generally expressed as raising the level of generality. That is, they are the answers to the following question: How can we create or...

Wireless Sensor Network WSN deployment is an active research area. Its goal to deploy sensors in certain environment efficiently optimize some evaluation measures. Meta heuristic searching optimization approaches have been proven be effective solving problem. They strong power exploring the solution space and converging toward theoptimal region. One key factor achieving more meta-heuristic sele...

In this paper, an online task scheduling and mapping method based on a fuzzy neural network (FNN) learned by evolutionary multi-objective algorithm (NSGA-II) to jointly optimize the main design challenges of heterogeneous MPSoCs is proposed. approach, first, FNN parameters are trained using NSGA-II-based optimization engine considering including temperature, power consumption, failure rate, exe...

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...

Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...

Load shedding has been extensively studied because of multiple power system failure occurrences worldwide. Reliable techniques are required to provide rapid and precise load shedding to avert voltage collapse in power networks. Meta-heuristic optimization approaches are currently the widely developed methods because of their robustness and flexibility in dealing with complex and non-linear syst...

The quadratic assignment problem (QAP) belongs to the class of NP-Hard problems and also is one of the hardest problems in this class. Today, regarding current hardware, solving the large size instances of this problem, using exact methods, is not possible in reasonable amount of time. In this way many heuristic (Meta-heuristic) and approximation methods and soft-computing approaches have been ...

An efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic (guided-random-search-based) methods for finding a suboptimal schedule. Due to the large solution space that a meta-heuristic algorithm is required to cover,...

this article addresses a single row facility layout problem where the objective is to optimize the arrangement of some rectangular facilities with different dimensions on a line. regarding the np-hard nature of the considered problem, a hybrid meta-heuristic algorithm based on simulated annealing has been proposed to obtain a near optimal solution. a number of test problems are randomly generat...