This paper addresses the dynamic vehicle routing problem. The proposed work includes the optimization in path selection using simulated annealing and hybrid memetic-genetic algorithm. In this paper, first we apply simulated annealing approach to the input of VRP.We use standard SA method that includes various types of move including insertion move, swap move,2-opt move,3-opt move to solve VRP.T...

Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for optimization and control. BFOA is inspired by the social foraging behavior of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. Simula...

The log-likelihood function of threshold vector error correction models is neither differentiable, nor smooth with respect to some parameters. Therefore, it is very difficult to implement maximum likelihood estimation (MLE) of the model. A new estimation method, which is based on a hybrid algorithm and MLE, is proposed to resolve this problem. The hybrid algorithm, referred to as genetic-simula...

The permutation flowshop scheduling problem with the objective of minimizing total flow time is known as a NP-hard problem, even for the two-machine cases. Because of the computational complexity of this problem, a multi-start simulated annealing (MSA) heuristic, which adopts a multi-start hill climbing strategy in the simulated annealing (SA) heuristic, is proposed to obtain close-to-optimal s...

An appropriate combination of multiple biometric sensors increases the reliability of verification through biometrics. In this paper we propose an effective method of fusion of biometrics based on a dynamic selection of threshold point of fingerprint and iris biometrics towards identifier of an optimal set of rules for fusion. The effectiveness of the method has been established using several b...

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...