Municipal　solid　waste　(MSW)　collection　has　become　a　major　challenge　for　clean　city　management　and　social　sustainable　development　in　developing　economies.　A　new　variant　of　the　collection　vehicle　routing　problem　(CVRP)　is　addressed　with　the　characteristics　of　full　loads　and　multiple　trips　of　the　collection　vehicles,　and　multiple　demands　of　the　garbage　facilities,　which　is　called　the　collection　vehicle　routing　problem　of　the　garbage　facilities　(CVRPGF)　in　this　study.　Dummy　customers　are　introduced　to　equivalently　transform　the　CVRPGF　problem　to　the　vehicle　routing　problem　with　simultaneous　pickup-delivery　and　time　windows　(VRPSPDTW).　A　parallel　simulated　annealing　algorithm　(Par-SAA)　is　developed　to　solve　the　VRPSPDTW　problem.　When　applied　to　an　international　benchmark　dataset,　the　computational　results　prove　the　superiority　of　the　proposed　algorithm,　in　which　the　number　of　collection　vehicles　(NV)　in　four　instances　is　reduced　by　one.　Finally,　when　the　model　and　algorithm　are　applied　to　a　real　CVRPGF　problem　in　the　Xuanwu　District　of　Beijing,　the　NV　needed　is　reduced　by　30　&　x0025;,　and　the　total　travel　time　is　decreased　by　12　&　x0025;.　Thus,　the　effectiveness　of　the　Par-SAA　is　demonstrated,　and　the　proposed　solution　has　practical　value　in　China.