DCORES 2017 Abstracts

Short Papers
Paper Nr: 1

The Route Network Development Problem based on QSI Models


Assia Kamal Idrissi, Arnaud Malapert and Rémi Jolin

Abstract: The growth of air passenger needs has forced airlines to improve their quality of service. Airlines have to choose flight schedules by considering demand, passengers preferences and competitors. The problem of allocating a new flight involves the route network development, and consists to determine a set of (Origin-Destination) pairs to serve and then choose flight schedules with respect to the Quality of Service Index (QSI) model. In this PhD project, we work with a software tool developed by the company Milanamos that helps airline managers to make decisions about destinations to serve. As a starting point, we define the flight radius problem related to this software. It is a sub-problem of the route network development problem and aims to optimize the visualization of the pertinent network by showing only interesting airports regarding QSI model. In this paper, we present the problem of allocating a new flight and formulate the flight radius problem as a problem of finding maximal sub-graph. Our objective is to locate in the network what routes represent business opportunities and are attractive regarding competition so it can be visualized. We construct the graph from Milanamos the database using the time-independent approach and store it in Neo4j a graph database. We describe the process of generating and storing the graph in Neo4j and sum up by outlining the expected outcome.

Paper Nr: 2

Langrangian Relaxation of Multi Level Capacitated Lot Sizing Problem with Consideration of Lead Time


Hanaa Razki and Ahmed Moussa

Abstract: Tactical planning consists to develop production plans by determining the quantities of products manufactured by period to best meet customer demand at lower costs. This issue has been widely discussed, according to two criteria: multi level and single level planning. The concept of multi level reflects well the manufacturing structure. For this, we propose in this work a new mathematical model of lot sizing finite capacity (Multi Level Capacitated Lot Sizing Problem) based on Lagrangian relaxation optimization approach. Comparisons of this new model with traditional one demonstrate the efficiency of this new approach as well in simulated case as real situations. The generated production plans are optimal with 68% -98% compared to classical models.