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....

Goel’s Okomtou model is based on the Exponential model and simple non-homogeneous Poisson process (NHPP) model. Some optimization technique has been discussed which can be used to optimize the Goel’s Okomtou models. Simulated Annealing (SA) is a heuristic optimization modelling technique that can been applied to solve many difficult problems in the various fields such as scheduling, modelling e...

The problem addressed in this paper is scheduling jobs on unrelated parallel machines with sequence-dependent setup times to minimize the maximum completion time (i.e., the makespan). This problem is NP-hard even without including setup times. Adding sequence-dependent setup times adds another dimension of complexity to the problem and obtaining optimal solutions becomes very difficult especial...

Recently, the use of the particle swarm optimization (PSO) technique for the reconstruction of microwave images has received increasing interest from the optimization community due to its simplicity in implementation and its inexpensive computational overhead. However, the basic PSO algorithm is easily trapping into local minimum and may lead to the premature convergence. When a local optimal s...

Quality-of-service routing (QoSR) is to find an optimal path that satisfies multiple constraints simultaneously. As an NPC problem, it is a challenge for the next-generation networks. In this paper, we propose a novel heuristic SA MCOP to the general multi-constrained optimal path problem by extending simulated annealing into Dijkstra’s algorithm. The heuristic first translates multiple QoS wei...

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population o...

In this paper we describe the use of coupling to interconnect different Simulated Annealing (SA) processes. The objective is to allow cooperative behavior among the processes in order to improve performance. Coupled Simulated Annealing (CSA) permits a high degree of parallelization while delivering much better results than a typical Parallel SA (PSA) algorithm. This is possible due to the intro...

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic ...

Earth dam is a structure as homogeneous or non-homogeneous forms for raising water level or water supply. Earth dam consist of different parts that one of the main parts is clay core. Choosing an optimal non permeable core which causes reduction of seepage through dam body and also being stable is necessary. The objective of this research is to optimize the geometry of earth dam clay core such ...

Bus network design is an important problem in public transportation. A main step to this design is determining the number of required terminals and their locations. This is a special type of facility location problem, which is a time-consuming, large scale, combinatorial problem. In a previous attempt by the authors, this problem had been solved by GAMS, based on a branch and bound algorithm. ...