Nathalie Grangeon

An iterative two-step heuristic for the parallel drone scheduling traveling salesman problem

A recent evolution in urban logistics involves the usage of drones. In this article, we address a heuristic solution of the parallel drone scheduling traveling salesman problem, recently introduced by Murray and Chu. In this problem, deliveries are split between a vehicle and drones. The vehicle performs a classical delivery tour, while the drones are constrained to perform back and forth trips. The objective is to minimize completion time. We propose an iterative two-step heuristic, composed of: a coding step that transforms a solution into a customer sequence, and a decoding step that decomposes the customer sequence into a tour for the vehicle and trips for the drones. Decoding is expressed as a bicriteria shortest path problem and is carried out by dynamic programming. Experiments conducted on benchmark instances confirm the efficiency of the approach and give some insights on this drone delivery system.

Medical Imaging : Exams Planning and Resource Assignment : Hybridization of a Metaheuristic and a List Algorithm

The presented work is about optimization of the hospital system. An existing solution is the pooling of resources within the same territory. This may involve different forms of cooperation between several hospitals. Problems of sizing, planning and scheduling may be considered. We define the problem of activities planning with resource assignment. To solve this problem, we propose a hybridization between a metaheuristic and a list algorithm. Single based metaheuristics are used. This proposition requires a new encoding inspired by permutation problems. This method is easy to apply: it combines already known methods. With the proposed hybridization, the constraints to be considered only need to be integrated into the list algorithm. For big instances, the solver used as a reference returns only lower and upper bounds. The results of our method are very promising. It is possible to adapt our method on more complex issues through integration into the list algorithm of the constraints. It would be particularly interesting to test these methods on real hospital authorities to assess their significance.

Improving Efficiency of Metaheuristics for Cellular Automaton Inverse Problem

The aim of this paper concerns several propositions to improve previous works based on a combination between metaheuristic and cellular automaton for the generation of 2D shapes. These improvements concern both the reduction of the search space and of the computational time. The first proposition concerns a new approach which delegates the determination of the number of generation to the cellular automaton. The second proposition consists in the reduction of the number of times the cellular automaton is requested. The last proposition concerns the adaptation of the method by exploiting the properties of the expected shape, in particular in case of symmetric shapes. Obtained results show that these propositions permit to improve the results as well as the computational times and the quality of the solution.

Optimization of Logistics Systems Using Metaheuristic-Based Hybridization Techniques

In the postwar years, the development of operational research provided companies with tools to deal with their logistical problems in a quantitative way. For a long time, these problems were split into unrelated subproblems, each subproblem often being tackled separately. This is mainly due to the fact that the subproblems considered, such as the localization problem, planning problem, scheduling problem, and transportation problem, are generally NP-hard problems and their computational complexity remains a significant issue for many researchers. Nevertheless, in an increasingly competitive industrial environment, companies continue to have a strong demand for decision aid tools to provide a global view of their organization.

Notation and classification for logistic network design models

This paper presents a notation and a classification system for the design models of logistic network. Our notation consists of three fields (analogous to Graham’s α | β | γ notation for scheduling problems). The proposed notation is applied for several articles from the literature. We focus on multi-period models with deterministic and stochastic demands. The proposed notation is based on three criteria corresponding to the main characteristics of the logistic networks: the structure (field α ), the management rules (field β ) and the performance criteria (field γ ). A description of solution methods, datasets and results is also provided. Most articles deal with deterministic, multi-level models and only few of them include the international aspect of logistics, lead-times or subcontracting. Datasets used to test the methods are randomly generated by the authors and have different sizes. The heuristic methods are most commonly used.

Extending metaheuristics based on bin packing for SALBP to PALBP

Parallel assembly line balancing problem (PALBP) considers a production system which consists of many parallel assembly lines. On each line, a product of a given type is manufactured according to the same cycle time. By arranging the lines in a favourable manner, it is possible to increase efficiency of the production system by combining stations of neighbouring lines when balancing the lines, i.e., an operator can work on two adjacent lines. The objective is to minimise the number of required operators. This problem has been considered first by Gokcen et al. (2006). We have already proposed efficient metaheuristics for SALBP-1. In this paper, we propose to investigate the link between SALBP-1 and PALBP and to adapt our metaheuristics for this problem. Two cases are considered. [Received 10 September 2009; Revised 10 June 2010; Accepted 23 November 2010]