A green home health care supply chain: New modified simulated annealing algorithms

Abstract Generally, in Home Health Care (HHC) logistics, caregivers which are started from a pharmacy are scheduled and routed to do different care services at patients' home. At the end, they go to their laboratory to update the patients' health records. In addition to scheduling and routing of the caregivers, there are some other optimization decisions which can increase the competitive advantages of HHC organizations as a supply chain network. The location decisions of the pharmacies and laboratories and the assignment of patients to the nearest pharmacies are two of the several important logistics factors for an HHC organization. The literature shows that the green emissions and sustainability achievements for HHC logistics are still scarce. To cover more logistics and sustainability factors and make the HHC more practical, this study contributes a Green Home Health Care Supply Chain (GHHCSC) for the first time by a bi-objective location-allocation-routing model. Already applied successfully to this research area, the Simulated Annealing (SA) is also employed in this study. Another main innovation of this paper is to propose a set of new modified SA algorithms to better solve the proposed NP-hard problem. As a bi-objective optimization model, the epsilon constraint method is also utilized to check the algorithms’ results in small sizes. By using some multi-objective assessment metrics, the algorithms are compared with each other and their performance is evaluated. As such, some sensitivity analyses are performed to reveal the efficiency of the developed model. Finally, some managerial insights are deployed to achieve the sustainability for the HHC organizations.

[1]  Yong Shi,et al.  A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand , 2017, Expert Syst. Appl..

[2]  Reza Tavakkoli-Moghaddam,et al.  A bi-objective green home health care routing problem , 2018, Journal of Cleaner Production.

[3]  Lawrence V. Snyder,et al.  A random-key genetic algorithm for the generalized traveling salesman problem , 2006, Eur. J. Oper. Res..

[4]  Chun-Cheng Lin,et al.  Jointly rostering, routing, and rerostering for home health care services: A harmony search approach with genetic, saturation, inheritance, and immigrant schemes , 2018, Comput. Ind. Eng..

[5]  Patrick Hirsch,et al.  Home health care routing and scheduling: A review , 2017, Comput. Oper. Res..

[6]  Reza Tavakkoli-Moghaddam,et al.  A hybrid simulated annealing algorithm for location and routing scheduling problems with cross-docking in the supply chain , 2013 .

[7]  Jerzy Grobelny,et al.  A novel version of simulated annealing based on linguistic patterns for solving facility layout problems , 2017, Knowl. Based Syst..

[8]  Ran Liu,et al.  Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics , 2014 .

[9]  Reza Tavakkoli-Moghaddam,et al.  The Social Engineering Optimizer (SEO) , 2018, Eng. Appl. Artif. Intell..

[10]  Hideo Tanaka,et al.  Modified simulated annealing algorithms for the flow shop sequencing problem , 1995 .

[11]  Ibrahim Kucukkoc,et al.  Comprehensive review and evaluation of heuristics and meta-heuristics for two-sided assembly line balancing problem , 2017, Comput. Oper. Res..

[12]  Md. Abdul Moktadir,et al.  Barriers to Reverse Logistics in the Computer Supply Chain Using Interpretive Structural Model , 2018 .

[13]  Torsten Fahle,et al.  A hybrid setup for a hybrid scenario: combining heuristics for the home health care problem , 2006, Comput. Oper. Res..

[14]  G. Kabir,et al.  Prioritization of drivers of corporate social responsibility in the footwear industry in an emerging economy: A fuzzy AHP approach , 2018, Journal of Cleaner Production.

[15]  Marilyn D. Harris,et al.  Handbook of Home Health Care Administration , 2009 .

[16]  Kris Braekers,et al.  Production , Manufacturing and Logistics A bi-objective home care scheduling problem : Analyzing the trade-off between costs and client inconvenience , 2015 .

[17]  Amir Mohammad Fathollahi-Fard,et al.  Two Constructive Algorithms to Address a Multi-Depot Home Healthcare Routing Problem , 2019, IETE Journal of Research.

[18]  Reza Tavakkoli-Moghaddam,et al.  Solving a fuzzy fixed charge solid transportation problem using batch transferring by new approaches in meta-heuristic , 2017, Electron. Notes Discret. Math..

[19]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[20]  Louis-Martin Rousseau,et al.  A set partitioning heuristic for the home health care routing and scheduling problem , 2019, Eur. J. Oper. Res..

[21]  S. Ali,et al.  Modeling the interrelationships among barriers to sustainable supply chain management in leather industry , 2018 .

[22]  Seyedali Mirjalili,et al.  A set of efficient heuristics for a home healthcare problem , 2019, Neural Computing and Applications.

[23]  Jennifer Lynn Rich,et al.  A Home Health Care Routing and Scheduling Problem , 1998 .

[24]  Stefan Nickel,et al.  Mid-term and short-term planning support for home health care services , 2012, Eur. J. Oper. Res..

[25]  Reza Tavakkoli-Moghaddam,et al.  A Lagrangian Relaxation-based Algorithm to Solve a Home Health Care Routing Problem , 2018 .

[26]  Patrick Hirsch,et al.  Securing home health care in times of natural disasters , 2011, OR Spectr..

[27]  Genichii Taguchi,et al.  Introduction to quality engineering. designing quality into products a , 1986 .

[28]  Anita Abdi,et al.  A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty , 2019, International Journal of Systems Science: Operations & Logistics.

[29]  Mostafa Hajiaghaei-Keshteli,et al.  A set of efficient heuristics and metaheuristics to solve a two-stage stochastic bi-level decision-making model for the distribution network problem , 2018, Comput. Ind. Eng..

[30]  Yong Shi,et al.  Modeling and solving simultaneous delivery and pick-up problem with stochastic travel and service times in home health care , 2018, Expert Syst. Appl..

[31]  Jean-Charles Billaut,et al.  Home health care problem: An extended multiple Traveling Salesman Problem , 2009 .

[32]  Mikael Rönnqvist,et al.  Operations Research Improves Quality and Efficiency in Home Care , 2009, Interfaces.

[33]  Rosemarie Velik,et al.  Grid-price-dependent energy management in microgrids using a modified simulated annealing triple-optimizer , 2014 .

[34]  Chaoyong Zhang,et al.  Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint , 2019, Journal of Cleaner Production.

[35]  David M. Miller,et al.  An Integrated Spatial DSS for Scheduling and Routing Home-Health-Care Nurses , 1997 .

[36]  Kannan Govindan,et al.  A socio-technical approach to the assessment of sustainable tourism: Adding value with a comprehensive process-oriented framework , 2019, Journal of Cleaner Production.

[37]  Pisal Yenradee,et al.  PSO-based algorithm for home care worker scheduling in the UK , 2007, Comput. Ind. Eng..

[38]  Ana Beatriz Lopes de Sousa Jabbour,et al.  Do Environmental Practices Improve Business Performance Even in an Economic Crisis? Extending the Win-Win Perspective , 2019, Ecological Economics.

[39]  Mikael Rönnqvist,et al.  Laps Care - an operational system for staff planning of home care , 2006, Eur. J. Oper. Res..

[40]  Hamidreza Maghsoudlou,et al.  Bi-objective optimization of a three-echelon multi-server supply-chain problem in congested systems: Modeling and solution , 2016, Comput. Ind. Eng..

[41]  Abdul Moktadir,et al.  Drivers to sustainable manufacturing practices and circular economy: a perspective of leather industries in Bangladesh , 2018 .

[42]  Arne Strauss,et al.  Dynamically accepting and scheduling patients for home healthcare , 2018, Health Care Management Science.

[43]  Alfonsas Misevicius,et al.  A Modified Simulated Annealing Algorithm for the Quadratic Assignment Problem , 2003, Informatica.

[44]  Rasoul Haji,et al.  Determination of the economical policy of a three-echelon inventory system with (R, Q) ordering policy and information sharing , 2011 .

[45]  Jesper Larsen,et al.  The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies , 2012, Eur. J. Oper. Res..

[46]  G. Kabir,et al.  A framework for sustainable supplier selection with transportation criteria , 2020, International Journal of Sustainable Engineering.

[47]  Amir Hajjam El Hassani,et al.  A memetic algorithm for multi-objective optimization of the home health care problem , 2019, Swarm Evol. Comput..

[48]  Patrick Hirsch,et al.  A matheuristic for routing real-world home service transport systems facilitating walking , 2015 .

[49]  Rajesh Matai,et al.  Solving multi objective facility layout problem by modified simulated annealing , 2015, Appl. Math. Comput..

[50]  Guangdong Tian,et al.  A multi-objective supplier selection and order allocation through incremental discount in a fuzzy environment , 2019, J. Intell. Fuzzy Syst..

[51]  Ahmad Jafarian,et al.  Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic , 2015, Comput. Oper. Res..

[52]  Seyyed Mehdi Sajadifar,et al.  Deriving the cost function for a class of three-echelon inventory system with N-retailers and one-for-one ordering policy , 2010 .

[53]  Syed Mithun Ali,et al.  A grey approach to predicting healthcare performance , 2019, Measurement.

[54]  Xiaolan Xie,et al.  Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care , 2013, Eur. J. Oper. Res..

[55]  Christian Bierwirth,et al.  The home health care routing and scheduling problem with interdependent services , 2014, Health care management science.

[56]  Maria Grazia Scutellà,et al.  Demand uncertainty in robust Home Care optimization , 2017, Omega.

[57]  Matthias Prandtstetter,et al.  Metaheuristics for solving a multimodal home-healthcare scheduling problem , 2015, Central Eur. J. Oper. Res..

[58]  M. Hajiaghaei-Keshteli,et al.  Heuristic-based metaheuristics to address a sustainable supply chain network design problem , 2018 .