Due to the combinatorial explosions in solution space for scheduling problems, the balance between genetic search and local search is an important issue when designing a memetic algorithm [23] for scheduling problems. The main motivation of this research is to resolve the combinatorial explosion problem by reducing the possible neighborhood combinations using guided operations to remove these i...

In recent years Cellular Manufacturing has become an effective tool for improving productivity. Attainment of full benefits of Cellular Manufacturing depends firstly on the design of the machine cells and part families, secondly on the method of operations which takes full advantage of cell properties. Inappropriate methods of loading and scheduling can even lead to the failure of the Cellular ...

Memetic algorithms usually employ long running times, since local search is performed every time a new solution is generated. Acceleration of a memetic algorithm requires focusing on local search, the most time-consuming component. This paper describes the application of two acceleration techniques to local search in a memetic algorithm: caching of values of objective function for neighbours an...

The capability to provide network service even under a significant network system element disruption is the backbone for the survival of route optimize of mobile network Technology in today’s world. Keeping this view in mind, the present paper highlights a new method based on memetic algorithm . KeywordsSurvivability, Mobile Network, memetic algorithm., PAN,.

In this paper, the problem of finding the optimal collision free path for a mobile robot, the path planning problem, is solved using an advanced evolutionary algorithm called memetic algorithm. What is new in this work is a novel representation of solutions for evolutionary algorithms that is efficient, simple and also compatible with memetic algorithm. The new representation makes it possible ...

In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...

A formal, representation-independent form of a memetic algorithm— a genetic algorithm incorporating local search—is introduced. A generalised form ofN -point crossover is defined together with representation-independent patching and hill-climbing operators. The resulting formal algorithm is then constructed and tested empirically on the travelling sales-rep problem. Whereas the genetic algorith...

In this paper, we examine the use of biased neighborhood structures for local search in multiobjective memetic algorithms. Under a biased neighborhood structure, each neighbor of the current solution has a different probability to be sampled in local search. In standard local search, all neighbors of the current solution usually have the same probability because they are randomly sampled. On th...

Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory on memetic algorithms is still in its infancy. Here, we introduce a simple memetic algorithm, the (1+1) Memetic Algorithm ((1+1) MA), working with a population size of 1 and no crossover. We compare it with the well-k...