Traditional　outpatient　medical　services　require　patients　to　visit　hospitals　for　treatment,　inhibiting　patients　from　receiving　convenient,　efficient,　and　high-quality　medical　services.　With　the　popularization　and　application　of　internet　technology,　the　emergence　of　“internet-nursing　service”　has　enabled　users　to　receive　health　care　at　home,　bringing　them　great　convenience　and　efficiency.　However,　the　supply　of　medical　resources　varies　across　different　regions　and　institutions,　and　it　is　difficult　for　a　single　institution　to　meet　the　diverse　and　personalized　needs　of　users　with　rapid　growth.　Collaborative　services　were　introduced　into　home　health　care　as　a　solution　to　the　imbalanced　supply　and　demand　for　medical　resources,　and　the　collaborative　multi-depot　home　health　care　problem　was　discussed,　considering　the　collaborative　service　of　multiple　care　centers　for　multi-demand　customers.　This　study　aims　to　minimize　the　operating　costs　of　care　centers　by　coordinating　and　optimizing　medical　resources　and　by　planning　flexible　and　reasonable　scheduling　plans　for　caregivers　while　meeting　customers’needs.　The　problem　is　formulated　as　a　mathematical　programming　model　with　the　objective　of　minimizing　the　total　cost　of　fixed,　traveling,　normal　working,　overtime　working,　and　constraints　of　customer　demand　and　caregiver　working　duration.　Moreover,　considering　the　characteristics　of　the　studied　problem,　a　hybrid　greedy　randomized　adaptive　search　procedure　with　an　adaptive　feedback　mechanism　combining　greedy　random　heuristic　and　iterative　local　search　methods　was　designed　based　on　greedy,　random,　and　adaptive　ideas.　Finally,　the　performance　of　the　designed　algorithm　was　evaluated　by　testing　benchmark　instances　in　simulation　experiments.　Compared　with　the　optimization　software　GUROBI　and　the　standard　greedy　randomized　adaptive　search　procedure,　the　proposed　algorithm　solved　the　studied　problem　more　efficiently,　providing　high-quality　solutions.　Therefore,　collaborative　services　can　significantly　reduce　operating　costs　and　improve　caregiver　utilization.　©　2024　Southwest　Jiaotong　University.　All　rights　reserved.