Balancing Staff Finishing Times vs. Minimizing Total Travel Distance in Home Healthcare Scheduling DOI Creative Commons
Payakorn Saksuriya, Chulin Likasiri

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(16), P. 7381 - 7381

Published: Aug. 21, 2024

Cost reduction and staff retention are important optimization objectives in home healthcare (HHC) systems. Home operators need to balance their by optimizing resource use, service delivery profits. Minimizing total travel distances control costs is a common routing problem objective while minimizing finishing time differences scheduling whose purpose enhance satisfaction. To optimize scheduling, we propose mixed integer linear programming with bi-objective function, which subset of the vehicle windows (VRPTWs). VRPTWs known NP-hard problem, optimal solutions very hard obtain practice. Metaheuristics offer an alternative solution this type problem. Our metaheuristic uses simulated annealing algorithm weighted sum approach convert problems single-objective equipped including swapping, moving, path exchange ruin recreate. The results show, firstly, that can effectively find Pareto front, secondly, number jobs per caretaker efficient way tackle HHC scheduling. A statistical test shows front lower problems.

Language: Английский

Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains DOI Creative Commons
Jie Zhang,

Junnan He,

Shihao Ren

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 11, 2025

In the face of forest fire emergencies, fast and efficient dispatching rescue vehicles is an important means mitigating damage caused by fires, effective method avoiding secondary minimizing fires to ecosystem, losses economic development. this paper takes actual problem as starting point, constructs a reasonable mathematical model problem, for special characteristics emergency vehicle scheduling taking into account road conditions in northern pristine area, through analysis cost paths between area highway, obtain least obstructed paths, narrow gap theoretical actual. Improvement ordinary genetic algorithm, design double population strategy selection operation, introduction chaotic search initialization population, improve algorithm's solution efficiency accuracy, Daxing'anling real cases generation large-scale random point simulation experimental test verify effectiveness ensure that reasonableness program. It enriches Great Khingan which great significance capability case sudden fire. Through experiments, proposed Improved Genetic Algorithm (IGA) achieved average time reduction 8.5% compared conventional (GA) 3.5% Artificial Bee Colony (IABC) with 9.4 ms.

Language: Английский

Citations

0

A Routing Model for the Distribution of Perishable Food in a Green Cold Chain DOI Creative Commons
Gilberto Pérez Lechuga, José Francisco Martínez-Sánchez, Francisco Venegas-Martı́nez

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(2), P. 332 - 332

Published: Jan. 19, 2024

In this research, we develop an extension of the stochastic routing model with a fixed capacity for distribution perishable products time window. We use theoretical probability distributions to life transported and travel times in network. Our main objective is maximize delivering within established deadline certain level customer service. project justified from perspective reducing pollution caused by greenhouse gases generated process. To optimize proposed model, Generic Random Search Algorithm. Finally, apply idea real problem designing strategies optimal management food routes that involve window, being meeting limit assigned route reducing, way, refrigerated transport.

Language: Английский

Citations

3

Balancing Staff Finishing Times vs. Minimizing Total Travel Distance in Home Healthcare Scheduling DOI Creative Commons
Payakorn Saksuriya, Chulin Likasiri

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(16), P. 7381 - 7381

Published: Aug. 21, 2024

Cost reduction and staff retention are important optimization objectives in home healthcare (HHC) systems. Home operators need to balance their by optimizing resource use, service delivery profits. Minimizing total travel distances control costs is a common routing problem objective while minimizing finishing time differences scheduling whose purpose enhance satisfaction. To optimize scheduling, we propose mixed integer linear programming with bi-objective function, which subset of the vehicle windows (VRPTWs). VRPTWs known NP-hard problem, optimal solutions very hard obtain practice. Metaheuristics offer an alternative solution this type problem. Our metaheuristic uses simulated annealing algorithm weighted sum approach convert problems single-objective equipped including swapping, moving, path exchange ruin recreate. The results show, firstly, that can effectively find Pareto front, secondly, number jobs per caretaker efficient way tackle HHC scheduling. A statistical test shows front lower problems.

Language: Английский

Citations

0