Titlebook: Bioinspired Heuristics for Optimization; El-Ghazali Talbi,Amir Nakib Book 2019 Springer Nature Switzerland AG 2019 Bioinspired Heuristics.

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Prologue

Hidden Markov Model Classifier for the Adaptive ACS-TSP Pheromone Parameters,ifier is a special kind of these models that aims to find the posterior probability of each state given a sequence of observations and predicts the state with the highest probability. The purpose of this work is to enhance the performance of Ant Colony System algorithm applied to the Travelling Sale

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CHN and Min-Conflict Heuristic to Solve Scheduling Meeting Problems,ult task. This paper proposes a new hybrid approach to solve meeting scheduling problem (MSP). The proposed network combines the characteristics of neural networks and minimizing conflicts approach. Her the MSP is considerate as Constraint Satisfaction Problem, then we apply Continuous Hopfield Neur

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Hybrid Genetic Algorithms to Solve the Multidimensional Knapsack Problem,ybrid heuristics based on Genetic Algorithms (GA) are proposed: the Memetic Search Algorithm (MSA) and the Genetic Algorithm Guided by Pretreatment information (GAGP). MSA combines sequentially GA with the Stochastic Local Search-Simulated Annealing algorithm (SLSA). GAGP is composed of two steps, i

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Solving the Home Health Care Problem with Temporal Precedence and Synchronization,dium-term home health care problem (HHCP) model. This model considers qualification requirements, possible patients/nurses exclusions, temporal precedences, synchronized services, routing with time windows, and working time constraints. As building a proper HHC planning is a challenging task, we pro

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