Pierrette P. Zouein

A multiple period capacitated inventory model for airline fuel management: a case study

One of the major operating cost items of an airline company is fuel, which can amount to approximately 20% of its overall operating cost. This paper presents a decision support model that determines the amount of fuel to be uplifted by a plane at each station along its route over a predetermined planning horizon so as to minimise overall fuel costs. The aforementioned fuel management problem is modelled as a multiple period capacitated inventory problem and solved using linear programming. An example application illustrates the applicability of this model to Middle East Airlines (MEA) operations and summarises the dollar savings obtained by applying it over a one week planning horizon.

An evolutionary algorithm for solving the geometrically constrained site layout problem

Construction site layout has been recognized as an important activity in construction site planning by field practitioners and researchers alike. This problem involves coordinating the use of limited space to accommodate temporary facilities (such as fabrication shops, trailers, materials or equipment) so that transportation costs of resources are minimized. The layout problem considered in this paper is a static layout problem characterized by affinity weights used to model transportation costs between facilities and by geometric constraints between relative positions of facilities on site. This paper presents an investigation of applying an evolutionary approach to optimally solve the aforementioned layout problem. The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. The paper concludes with a number of examples illustrating the strength and limitations of the proposed approach.

FORECASTING PASSENGER LOAD FOR A FIXED PLANNING HORIZON

This paper presents a forecasting system for predicting the number of boarding passengers on each of the next N departure dates of a particular flight leg using as input the booking levels made for the next N departure dates of that flight leg. A forecasting system that gives good estimates of future boardings of a particular flight leg is an important and essential tool for route management in the airline industry. The proposed forecasting system consists of a Kalman filter, which optimally integrates a large class of reservation measurements from a variety of sources and at arbitrary times, which is the case of the data, considered here. The accuracy of the predictions for a case study proved to be promising.

A PARALLEL GENETIC ALGORITHM FOR THE GEOMETRICALLY CONSTRAINED SITE LAYOUT PROBLEM WITH UNEQUAL-SIZE FACILITIES

Parallel genetic algorithms techniques have been used in a variety of computer engineering and science areas. This paper presents a parallel genetic algorithm to solve the site layout problem with unequal-size and constrained facilities. The problem involves coordinating the use of limited space to accommodate temporary facilities subject to geometric constraints. The problem is characterised by affinity weights used to model transportation costs between facilities, and by geometric constraints between relative positions of facilities on site. The algorithm is parallelised based on a message passing SPMD architecture using parallel search and chromosomes migration. The algorithm is tested on a variety of layout problems to illustrate its performance. In specific, in the case of: (1) loosely versus tightly constrained layouts with equal levels of interaction between facilities, (2) loosely versus tightly packed layouts with variable levels of interactions between facilities, and (3) loosely versus tightly constrained layouts. Favorable results are reported.

Activity-Level Space Scheduling

Activity-level space scheduling involves allocating site space over time to static and dynamic construction resources such as robots. The resulting coarse layouts pertaining to activity-related time intervals serve to coordinate the motion planning of multiple robots. This cannot be done with existing motion planning tools, as computational demands make path-planning for multiple robots in dynamic environments prohibitively expensive. An interactive and graphical decision-support tool, named MovePlan, is presented to assist in space scheduling. Its output layouts can be used to refine individual robots trajectories using traditional path-planning algorithms.

Case Study of Lean in Hospital Admissions to Inspire Culture Change

Abstract The hospital admissions process is a distinct experience for patients as this is where they start their journey for medical care, usually with a mix of anxiety and anticipation about what is to follow. This process also happens to be long and stressful, with numerous steps, frequent delays, and the occasional glitches along the way. In this study, we used lean thinking and discrete-event simulation to map and model the inpatient admissions process at a multi-specialty hospital in order to improve patient flow and reduce unnecessary waiting and handling by patients and staff. We found that by applying a combination of simple but complementary lean techniques, it was possible to reduce the total patient time in the system by up to 43%, without incurring additional costs or using more resources. The potential for achieving substantial improvements at low cost, combined with the approach of validation-prior-to-implementation adopted in this study, can both help process engineers and engineering managers to build support for any proposed lean initiative. This also makes it possible to sustain continuous improvement in the long term, which is at the heart of the lean approach.