An Empirical Comparison of MRPII and Demand‐Driven MRP
Romain MICLO(1), Franck FONTANILI(1), Matthieu LAURAS(1), Jacques LAMOTHE(1), Bernard MILIAN(2)
(1) Industrial Engineering Department, University of Toulouse Mines Albi
(2) AGILEA S.A.S.
Abstract: The Demand-Driven MRP (DDMRP) is a method for managing flows in manufacturing and distribution that is supposed to manage uncertainties better than traditional Manufacturing Resources Planning (MRP) using some principles of pull approaches. In this paper, a case-study is investigated in order to objectively and quantitatively compare these two systems. A Discrete-Event Simulation (DES) approach is used to evaluate impacts on system behaviors regarding both methods. Results show insights on the interests of DDMRP.
Keywords: Modeling, simulation, control and monitoring of manufacturing processes, Inventory control, production planning and scheduling, Discrete event systems in manufacturing
Robust Single Machine Scheduling with External‐Party Jobs
Paolo DETTI(1), Gaia NICOSIA(2), Andrea PACIFICI(3), Garazi ZABALO MANRIQUE DE LARA(1)
(1) Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Universit`a degli Studi di Siena,
(2) Dipartimento di Ingegneria, Universit`a degli Studi “Roma Tre”
(3)Dipartimento di Ingegneria Civile e Ingegneria Informatica, Universit`a degli Studi di Roma “Tor Vergata”
Abstract: In this paper we address a problem arising in a manufacturing environment in which the owner of a machining resource, besides its own jobs, must process also jobs belonging to an external party. Due to contract commitments, the jobs of the external party must be processed within a certain due date, that can be considered as a deadline. Moreover, these jobs have a given release date corresponding to their actual availability in the manufacturing system. The external party jobs arrive with an estimate of their durations and the owner of the machining resource, when planning the schedule of its jobs, must take into account possible deviations from the nominal values of the external processing times. It is therefore important to determine a schedule which is robust to any possible changes in the durations of the external jobs. We consider the total completion time objective for the owner of the machining resource. However, due to the uncertainty on the external jobs processing times, we seek for a solution minimizing the maximum absolute deviation from an optimal schedule. We derive some properties of such robust schedules and evaluate the performance two mixed integer linear programming formulations.
Keywords: Operations Research, Industrial and applied mathematics for production
An Efficient Heuristic for Scheduling on Identical Parallel Machines to Minimize Total Tardiness
Benjamin VINCENT(1), Christophe DUHAMEL(1), Libo REN(2), Nikolay TCHERNEV(1)
(1) LIMOS UMR CNRS 6158
(2) CRCGM EA3849
Abstract: This paper deals with the identical parallel machine scheduling problem to minimize total tardiness where each machine cannot have more than one job at a time. An efficient heuristic algorithm is proposed. It relies on a simulated annealing algorithm aimed at searching for a better solution during the schedule construction stage. The heuristic uses some well-known dominance properties for this problem which are usually used by exact methods and particularly by branch and bound algorithms. Some instances of the literature are used to show the effectiveness of this heuristic on computational results.
Keywords: Inventory control, production planning and scheduling
Efficient Approaches to Scheduling for Unrelated Parallel Machines with Release Dates
Tatiana AVDEENKO, Yury MEZENTSEV
Business Informatics Department, Novosibirsk State Technical University
Abstract: In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results of the proposed approach have been given that show its efficiency.
Keywords: Inventory control, production planning and scheduling, Operations Research
A GRASP Embedding a Bi‐Level ELS for Solving Flexible Job‐Shop Problems
Sylverin KEMMOE(1), Damien LAMY(2), Nikolay TCHERNEV(2)
(1) CRCGM EA3849
(2) LIMOS UMR CNRS 6158
Abstract: In this paper, an evolution of the GRASPxELS for the Flexible Job-shop problem is proposed, resulting in a GRASP with a bi-level ELS paradigm. As ELS is based on neighborhood search, a random neighborhood is developed, including three different neighborhood structures. This metaheuristic allowed to find state of the art solutions for Barnes and Chambers’ instances, two new best solutions for the famous instances of Dauzère-Pérès while still being competitive on all this set of instances. Results are compared with recent papers focusing on this challenging problem demonstrating that this metaheuristic approach is effective.
Keywords: Inventory control, production planning and scheduling