Many companies are confronted with the problem of creating xed master
routes for a period of more than a day either for geographically dispersed
sales representatives or for
eets of delivery vehicles which operate from a
single depot. This involves the assignment of the company's customers to the
sales reps/vehicles as well as visit pro les. For the problems de ned herein,
these allocations of customers to a service group must remain xed for the
duration of the planning period. A pro le represents a valid combination of
visit days for a customer as well as a proportion of distributable workload
(time for sales reps or mass for delivery vehicles) for each visit. For the
sales rep problem, there is the option to solve for the optimal number of
salesmen and their home locations if they are not known. Also, routes for
the salesmen may include a new feature, sleep-outs, which are governed by
rules indicating possible combinations of nights spent away from home as
well as sleep-out locations. These combinatorial optimization problems are
solved using exact and heuristic branch-and-bound algorithms which also
assists in de ning the problem complexity. A genetic algorithm hybridised
with problem speci c heuristics (i.e. a memetic algorithm) is also applied
to problems which cannot be solved exactly in a reasonable amount of time.
This evolutionary programming metaheuristic technique uses natural multi-
level data structures and problem-sensitive genetic operators.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/14009 |
| Date | 04 March 2014 |
| Creators | Rademeyer, Angela Liza |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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