Menkes van den Briel

America West Airlines Develops Efficient Boarding Strategies

In September 2003, America West Airlines implemented a new aircraft boarding strategy that reduces the airlines average passenger boarding time by over two minutes, or approximately 20 percent, for full and nearly full flights. The strategy, developed by a team of Arizona State University and America West Airlines personnel, is a hybrid between traditional back-to-front boarding and outside-inside boarding used by other airlines. Field observations, numerical results of analytical models, and simulation studies provided information that resulted in an improved aircraft-boarding strategy termed reverse pyramid. With the new boarding strategy, passengers still have personal seat assignments, but rather than boarding by rows from the back to the front of the airplane, they board in groups minimizing expected passenger interference in the airplane. The analytical, simulation, and implementation results obtained show that the method represents a significant improvement in terms of boarding time over traditional pure back-to-front, outside-inside boarding strategies.

An LP-based heuristic for optimal planning

One of the most successful approaches in automated planning is to use heuristic state-space search. A popular heuristic that is used by a number of state-space planners is based on relaxing the planning task by ignoring the delete effects of the actions. In several planning domains, however, this relaxation produces rather weak estimates to guide search effectively. We present a relaxation using (integer) linear programming that respects delete effects but ignores action ordering, which in a number of problems provides better distance estimates. Moreover, our approach can be used as an admissible heuristic for optimal planning.

Optiplan: unifying IP-based and graph-based planning

The Optiplan planning system is the first integer programming-based planner that successfully participated in the international planning competition. This engineering note describes the architecture of Optiplan and provides the integer programming formulation that enabled it to perform reasonably well in the competition. We also touch upon some recent developments that make integer programming encodings significantly more competitive.

Loosely coupled formulations for automated planning: an integer programming perspective

We represent planning as a set of loosely coupled network flow problems, where each network corresponds to one of the state variables in the planning domain. The network nodes correspond to the state variable values and the network arcs correspond to the value transitions. The planning problem is to find a path (a sequence of actions) in each network such that, when merged, they constitute a feasible plan. In this paper we present a number of integer programming formulations that model these loosely coupled networks with varying degrees of flexibility. Since merging may introduce exponentially many ordering constraints we implement a so-called branch-and-cut algorithm, in which these constraints are dynamically generated and added to the formulation when needed. Our results are very promising, they improve upon previous planning as integer programming approaches and lay the foundation for integer programming approaches for cost optimal planning.