I am trying to group arrays of addresses with the nearest and same location with max 4 people in a group from database input.

This is the code I am trying to use now:

export const sortRoute = async (data: z.infer<typeof sortRouteSchema>) => {
      const validate = sortRouteSchema.safeParse(data);
    
      if (!validate.success) return { success: false, error: "Invalid Field" };
    
      const { staffs, organization_id, route_id } = validate.data;
    
      // staffs variable is array of object like this and all address are for one country (Singapore)
    
    
    [
      {
        "name": "Staff 17",
        "address": "37 HOUGANG AVENUE 7 EVERGREEN PARK SINGAPORE 538803",
        "place_id": "",
        "department": "",
        "postal_code": "538803"
      },
      {
        "name": "Staff 16",
        "address": "38 LORONG 5 TOA PAYOH EAST PAYOH SPRING SINGAPORE 310038",
        "place_id": "",
        "department": "",
        "postal_code": "310038"
      },
      {
        "name": "Staff 15",
        "address": "467A YISHUN AVENUE 6 CASA SPRING @ YISHUN SINGAPORE 761467",
        "place_id": "",
        "department": "",
        "postal_code": "761467"
      },
      {
        "name": "Staff 14",
        "address": "326 YISHUN RING ROAD YISHUN RIVERGREEN SINGAPORE 760326",
        "place_id": "",
        "department": "",
        "postal_code": "760326"
      },
      {
        "name": "Staff 13",
        "address": "615 YISHUN RING ROAD SINGAPORE 760615",
        "place_id": "",
        "department": "",
        "postal_code": "760615"
      },
      {
        "name": "Staff 12",
        "address": "476 SEMBAWANG DRIVE SINGAPORE 750476",
        "place_id": "",
        "department": "",
        "postal_code": "750476"
      },
      {
        "name": "Staff 11",
        "address": "17 WOODLANDS AVENUE 9 REPUBLIC POLYTECHNIC (CAMPUS HEIGHTS) SINGAPORE 738968",
        "place_id": "",
        "department": "",
        "postal_code": "738968"
      },
      {
        "name": "Staff 10",
        "address": "21 WOODLANDS CROSSING BLK A (WOODLANDS CHECKPOINT) SINGAPORE 738203",
        "place_id": "",
        "department": "",
        "postal_code": "738203"
      },
      {
        "name": "Staff 9",
        "address": "21 WOODLANDS CROSSING BLK A (WOODLANDS CHECKPOINT) SINGAPORE 738203",
        "place_id": "",
        "department": "",
        "postal_code": "738203"
      },
      {
        "name": "Staff 8",
        "address": "21 WOODLANDS CROSSING BLK A (WOODLANDS CHECKPOINT) SINGAPORE 738203",
        "place_id": "",
        "department": "",
        "postal_code": "738203"
      },
      {
        "name": "Staff 7",
        "address": "17 WOODLANDS AVENUE 9 REPUBLIC POLYTECHNIC (CAMPUS HEIGHTS) SINGAPORE 738968",
        "place_id": "",
        "department": "",
        "postal_code": "738968"
      },
      {
        "name": "Staff 6",
        "address": "27 WOODLANDS AVENUE 9 REPUBLIC POLYTECHNIC SINGAPORE 737909",
        "place_id": "",
        "department": "",
        "postal_code": "737909"
      },
      {
        "name": "Staff 5",
        "address": "463 ANG MO KIO AVENUE 10 SINGAPORE 560463",
        "place_id": "",
        "department": "",
        "postal_code": "560463"
      },
      {
        "name": "Staff 4",
        "address": "223A SERANGOON AVENUE 4 SINGAPORE 551223",
        "place_id": "",
        "department": "",
        "postal_code": "551223"
      },
      {
        "name": "Staff 3",
        "address": "37 HOUGANG AVENUE 7 EVERGREEN PARK SINGAPORE 538803",
        "place_id": "",
        "department": "",
        "postal_code": "538803"
      },
      {
        "name": "Staff 2",
        "address": "165 HOUGANG AVENUE 1 SINGAPORE 530165",
        "place_id": "",
        "department": "",
        "postal_code": "530165"
      },
      {
        "name": "Staff 1",
        "address": "157 LORONG 1 TOA PAYOH PCF SPARKLETOTS PRESCHOOL @ TOA PAYOH CENTRAL BLK 157 (KN) SINGAPORE 310157",
        "place_id": "",
        "department": "",
        "postal_code": "310157"
      }
    ]
    
       
    
      const geocodedAddresses: geocodedAddressesType[] = [];
      const postalCodeBoundary: postalCodeBoundary[] = [];
      const groupedAddresses: any = [];
      const processedAddresses = new Set();
    
      const promise = staffs.map(async (staff) => {
        const { results } = await geoCodeByAddress(staff.address);
    
        const location = results[0].geometry.location;
        const address_comp = results[0].address_components;
        const boundaries = [
          { lat: location.lat + 0.01, lng: location.lng + 0.01 },
          { lat: location.lat + 0.01, lng: location.lng - 0.01 },
          { lat: location.lat - 0.01, lng: location.lng - 0.01 },
          { lat: location.lat - 0.01, lng: location.lng + 0.01 },
          { lat: location.lat + 0.01, lng: location.lng + 0.01 },
        ];
    
        geocodedAddresses.push({
          ...staff,
          address: staff.address,
          lat: location.lat,
          lng: location.lng,
          staff_name: staff.name as string,
        });
    
        postalCodeBoundary.push({
          code: address_comp[address_comp.length - 1].long_name,
          boundaries,
          latLng: { lat: location.lat, lng: location.lng },
        });
      });
    
      await Promise.all(promise);
    
      geocodedAddresses.map((address) => {
        postalCodeBoundary.map((postCode) => {
          const latLng = new geometry.LatLng(address.lat, address.lng);
          const inRange = geometry.computeDistanceBetween(latLng, postCode.latLng);
    
          if (inRange <= 8000) {
            if (postCode.code && !processedAddresses.has(address.staff_name)) {
              if (!groupedAddresses[postCode.code]) {
                groupedAddresses[postCode.code] = [];
              }
              groupedAddresses[postCode.code].push(address);
              processedAddresses.add(address.staff_name);
            }
          }
        });
      });
    
      const grouped_address = Object.values(groupedAddresses);
      
      const empty: any = [];
    
      grouped_address.map((address: any) => {
        if (address.length > 4) {
          empty.push(..._.chunk(address, 4));
        } else {
          empty.push(address);
        }
      });
    
      const payload = empty.map((address: [], index: number) => ({
        route_id,
        organization_id,
        staffs: address as Prisma.InputJsonValue,
      }));
    
    
    
      await db.routesGroup.createMany({
        data: payload,
      });
    
    };

Current function seems ok but not give best group that should be like:

• Not adding as first priority with same and nearest first

• need to group all-together WOODLANDS address first in 4 people then rest will next group if existing group already reach to max people allow.

• on recalculate result are not same

Any way to make more accurate and best grouping solution for this ?