This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of find...This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon.Thus,a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint.Nevertheless,when the time horizon become large,practical-sized instances become very difficult to solve in a reasonable computational time.Therefore,a new Learning Genetic Algorithm for mTSP(LGA-mTSP)is proposed to solve the problem.LGA-mTSP is composed of a new genetic algorithm for mTSP,combined with a learning approach,called learning curves.Learning refers to that caregivers’productivity increases as they gain more experience.Learning curves approach is considered as a way to save time and costs.Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.展开更多
The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based ...The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based digital approaches tends to become widespread.However,achieving the target values for all the rules is difficult.This impacts the social,environmental and aesthetic objectives of these rules.This paper proposes a classification of urban morphological rules to assist the digital morphosis of urban form.The aim is to endow the system of rules with a hierarchy,which can make efficient the automatic generation of the urban forms respectful of the urban law.Thus,this work promotes the concerns of artificial intelligence in urban morphology.展开更多
文摘This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon.Thus,a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint.Nevertheless,when the time horizon become large,practical-sized instances become very difficult to solve in a reasonable computational time.Therefore,a new Learning Genetic Algorithm for mTSP(LGA-mTSP)is proposed to solve the problem.LGA-mTSP is composed of a new genetic algorithm for mTSP,combined with a learning approach,called learning curves.Learning refers to that caregivers’productivity increases as they gain more experience.Learning curves approach is considered as a way to save time and costs.Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.
文摘The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based digital approaches tends to become widespread.However,achieving the target values for all the rules is difficult.This impacts the social,environmental and aesthetic objectives of these rules.This paper proposes a classification of urban morphological rules to assist the digital morphosis of urban form.The aim is to endow the system of rules with a hierarchy,which can make efficient the automatic generation of the urban forms respectful of the urban law.Thus,this work promotes the concerns of artificial intelligence in urban morphology.
