Comparison With Other Works

The results in Table 4.5 are used to compare existing published research works with the method proposed within this thesis. A desirable solution is one that has as much as possible population covered within D, and the uncovered population within D totally covered within S. The table indicates if the farthest population will travel within or beyond S.

Church and ReVelle (1974) provides an optimal 5-facility solution for MCLP with mandatory closeness constraints of D “ 10 and S “ 15. While these parameters were fixed in their work, this thesis has endogenously indicated that the uncovered pop-ulation can be covered within 14.60 distance units with five facilities (highlighted in red). Table 4.7 compares the optimal solution of Church and ReVelle (1974) with the results for this thesis. This research has produced a better solution with increased pop-ulation coverage of 5370 (83.91%) within D compared to the optimal solution of 3540 (55.31%) population coverage. The graphic solution for the optimal 5-facility config-uration is shown in Figure 4.7 (Church and ReVelle, 1974) and Figure 4.8 shows the Spatial-ABM 5-facility graphic output.

Table 4.7: Five facilities solutions for MCLP with mandatory closeness constants Optimal solution Spatial ABM solution (Church and ReVelle, 1974)

facilities on nodes facilities in discrete space

Demand within 10 3540 (55.31%) 5370 (83.91%)

Demand outside 10, inside 15 2860 (44.69%) 1030 (16.09%)

Demand outside 15 0 0

It is a clear indication that by placing facilities in the centroid of any of the finite set of patches within the boundary without restricting facilities to the nodes, better solutions are obtainable with the Spatial-ABM covering model.

O. Olowofoyeku 4.5. LOCATION-ALLOCATION VALIDATION ON 55-NODE DATASET

Figure 4.7: Optimal solution for mandatory closeness constraints for 55-node (Adapted from Church and ReVelle (1974))

Figure 4.8: Spatial-ABM solution for MCLP with mandatory closeness constraints for 55-node

O. Olowofoyeku 4.5. LOCATION-ALLOCATION VALIDATION ON 55-NODE DATASET

4.5.2.1 Distance Consideration

The decision maker may prefer some level of equity and not want large populations outside of D. Table 4.5 proves that this strategy can be achieved still using five facilities by increasing D which in turn increases the coverage. For example, with D “ 12 dis-tance units, 5770 (90.16%) population is covered within D and 630 (9.84%) out of D will travel within 12.88 to get to a facility. Further increase in D leads to an increased coverage up to 14 and 15 distance units that gives 100% coverage within the service distance.

With D “ 14, the Location Set Covering Problem (LSCP) (discussed in Section 2.4.2) is solved by this model. The LSCP achieves total coverage within a specified covering distance with as few number of facilities as possible. The four-facility solution to the MCLP is an improvement to the LSCP five-facility solution of previous works (Toregas et al., 1971; Church and ReVelle, 1974).

The distance that the farthest population outside D will travel to its closest facil-ity was not considered by previous works (Church, 1984; Galvão and ReVelle, 1996), and so cannot be compared with this model. However, the solutions with total cov-erage by any of the works will be considered. Table 4.8 compares the 100% covcov-erage solutions with service distance values of 10 and 12 optimal solutions of these previous works. Church (1984) considered locating facilities in an infinite continuous plane, Church (1984); Galvão and ReVelle (1996) provided solutions for facilities restricted to the nodes, while this thesis locates facilities in a gridded discrete plane.

Table 4.8: Comparison of total coverage (%) for facilities restricted to the nodes, facilities placed in continuous plane and Spatial-ABM facilities located at discrete plane.

Church and

ReV-elle (1974) Galvão and

ReV-elle (1996) Church

(1984) Spatial-ABM

D p facilities at nodes planar gridded plane

% % % %

10 7 98.91 98.91 100.00 99.53

8 99.69 99.69 100.00 100.00

Table 4.8 shows that this work agrees with previous works and also gives better solutions in some instances. For example, with D “ 10, eight facilities are required

O. Olowofoyeku 4.5. LOCATION-ALLOCATION VALIDATION ON 55-NODE DATASET

for total coverage in the planar and Spatial-ABM methods, in contrast to nine facilities required for placing facilities on nodes. The Spatial-ABM methods provides greater coverage of 99.53% with seven facilities compared to 98.91% coverage for restricting facilities at nodes. However the planar method has 100% coverage. With D “ 12, six facilities are required for total coverage compared to the optimal seven-facility solution of Galvão and ReVelle (1996).

The results for four-facility and five-facility solutions highlighted in Table 4.5 also show that an increase in population coverage with D using p-facility does not neces-sarily imply that the uncovered population with D will travel greater distance to their closest facility than when the coverage is reduced. For example, the four-facility solu-tions for D “ 10 and D “ 12 indicates a lower maximum distance with an increase in coverage. On the other hand, the four-facility solutions for D “ 13 and D “ 15; and five-facility solutions for D “ 12 show an increase in maximum distance for increased population coverage.

4.5.2.2 Facility Capacity in Cost of Establishment

The determining factors for total coverage are not only p and S, but the costs of es-tablishing the HCFs based on the size of the population that is covered by each HCF.

The cost objective serves a valuable role in healthcare facility coverage. According to the WHO standard (World Health Organization, 1998), facility density is one HCF to 5,000 population or two HCFs to 10,000 population. To introduce this concept to the 55-node dataset, a facility density of 1 to 500 is assumed due to the small values of the population in the dataset. For the 6400 population, the required number of facilities is the round value of 6400{500. A selected facility may therefore require additional facil-ity or facilities within its catchment if the population within the catchment is greater than the value of 500 + (50% of 500). Where such is the case, the selected HCF hatches the additional number of HCFs and they are located within the catchment of that par-ent HCF. In the application to this research, it is assumed that if a facility has excess population that is less than 50% of the carrying capacity of 500, no additional facility will be needed. A facility is regarded as a low-cost facility if it covers less than 50% of the carrying capacity.

By comparing the cost of establishing fewer standard facilities to the cost of estab-lishing more facilities driven by the number of low-cost facilities, the decision maker may consider establishing more facilities. The D “ 10 and S “ 15 five-facility solution with four standard facilities and one low-cost facility is shown in Figure 4.8. Also, the seven-facility solutions offer options such as five standard facilities and two low-cost facilities; four standard and three low-cost facilities; and three standard facilities and four low-cost facilities (Figure 4.9). The cost of establishing these seven facilities may be lower than providing five standard facilities with the five-facility solution. This is a novel and substantial contribution of this thesis. Although Church and ReVelle (1974) and Church (1984) suggest that the choice of placing fewer facilities may be based on

O. Olowofoyeku 4.5. LOCATION-ALLOCATION VALIDATION ON 55-NODE DATASET

the decreasing marginal difference in coverage as the number of facilities increases.

This is also revealed in Figure 4.6 and Table 4.5 where only little incremental coverage results from increasing the number of HCFs. For example, in the solution for D “ 10 distance units, the decision maker may want to establish seven HCFs that will provide 99.53% coverage instead of eight HCFs that will give 100.00% coverage. However this thesis has also shown that more facilities may be established at a lower level of expen-diture, based on the cost that is driven by the population size within a HCF catchment.

Figure 4.9: Alternative 7-facility solutions for 55-node dataset