This thesis investigates solution methodologies for concrete combinatorial problems in scheduling and planning. In all considered problems, it is assumed that the available information does not change over time; hence these problems have a deterministic structure. The problems studied in this thesis are divided into two groups; \workforce scheduling" and \planning". In workforce scheduling, the center problem is to build a schedule of tasks and technicians. It is assumed that the time line is split into workdays. In every workday, tasks must be grouped as sequences, each being performed by a team of technicians. Skill requirements of every task in a sequence must be met by the assigned team. This scheduling problem with some other aspects is di??cult to solve quickly and e??ciently. We developed a Mixed Integer Programming (MIP) based heuristic approach to tackle this complex scheduling problem. Our MIP model is basically a formulation of the matching problem on bipartite graphs and it enabled us to have a global way of assigning technicians to tasks. It is capable of revising technician-task allocations and performs very well, especially in the case of rare skills. A workday schedule of the aforementioned problem includes many-to-one type workforce assignments. As the second problem in workforce scheduling, stability of these workforce assignments is investigated. The stability de??nition of Gale-Shapley on the Marriage model is extended to the setting of multi-skill workforce assignments. It is shown that ??nding stable assignments is NP-hard. In some special cases stable assignments can be constructed in polynomial time. For the general case, we give linear inequalities of binary variables that describe the set of stable assignments. We propose a MIP model including these linear inequalities. To the best of our knowledge, the Gale-Shapley stability is not studied under the multi-skill workforce scheduling framework so far in the literature. The closed form description of stable assignments is also the ??rst embedding of the Gale-Shapley stability concept into an NP-complete problem. In the second problem group, two vehicle related problems are studied; the "dial a ride problem" and the "vehicle refueling problem". In the former, the goal is to check whether a list of pick-up and delivery tasks can be achieved under several timing constraints. It is shown this feasibility testing can be done in linear time using interval graphs. In the vehicle refueling problem, the goal is to make refueling decisions to reach a destination such that the cost of the travel is minimized. A greedy algorithm is presented to ??nd optimal refueling decisions. Moreover, it is shown that the vehicle refueling problem is equivalent to a ow problem on a special network.
|Qualification||Doctor of Philosophy|
|Award date||24 Apr 2012|
|Place of Publication||Eindhoven|
|Publication status||Published - 2012|