Heuristics for two-machine flowshop scheduling with setup times and an availability constraint

2006-2007 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Mixed integer linear programming models for Flow Shop Scheduling with a demand plan of job types

This is a post-peer-review, pre-copyedit version of an article published in Central european journal of operations research. The final authenticated version is available online at: http://www.doi.org/10.1007/s10100-018-0553-8This paper presents two mixed integer linear programming (MILP) models that extend two basic Flow Shop Scheduling problems: Fm/prmu/Cmax and Fm/block/Cmax. This extension incorporates the concept of an overall demand plan for types of jobs or products. After using an example to illustrate the new problems under study, we evaluated the new models and analyzed their behaviors when applied to instances found in the literature and industrial instances of a case study from Nissan’s plant in Barcelona. CPLEX solver was used as a solution tool and obtained acceptable results, allowing us to conclude that MILP can be used as a method for solving Flow Shop Scheduling problems with an overall demand plan.Peer ReviewedPostprint (published version

A study of maintenance contribution to joint production and preventive maintenance scheduling problems in the robustness framework.

International audienceIn this paper, we deal with a joint production and Preventive Maintenance (PM) scheduling problem in the robustness framework. The contributions of this paper are twofold. First, we will establish that the insertion of maintenance activities during production scheduling can hedge against some changes in the shop environment. Furthermore, we will check if respecting the optimal intervals of maintenance activities guarantees a minimal robustness threshold. Then, we will try to identify from the used optimisation criteria those that allow making predictive schedules more robust. The computational experiments in a flowshop show that joint production and PM schedules are more robust than production schedules and maintenance provides an acceptable tradeoff between equipment reliability and performance loss under disruption

Heuristics for two-machine flowshop scheduling with setup times and an availability constraint

This paper studies the two-machine flowshop scheduling problem with anticipatory setup times and an availability constraint imposed on only one of the machines where interrupted jobs can resume their operations. We present a heuristic algorithm from Wang and Cheng to minimize makespan and use simulation to determine the actual error bound

Joint scheduling of jobs and preventive maintenance operations in the flowshop sequencing problem: A resolution with sequential and integrated strategies.

International audienceUsually, scheduling of maintenance operations and production sequencing are dealt with separately in the literature and, therefore, also in the industry. Given that maintenance affects available production time and elapsed production time affects the probability of machine failure, this interdependency seems to be overlooked in the literature. This paper presents a comparative study on joint production and preventive maintenance scheduling strategies regarding flowshop problems. The sequential strategy which consists of two steps: first scheduling the production jobs then inserting maintenance operations, taking the production schedule as a strong constraint. The integrated one which consists of simultaneously scheduling both maintenance and production activities based on a common representation of these two activities. For each strategy, a constructive heuristic and two meta-heuristics are proposed: NEH heuristic, Genetic algorithm and Taboo search. The goal is to optimize an objective function which takes into account both production and maintenance criteria. The proposed heuristics have been applied to non-standard test problems which represent joint production and maintenance benchmark flowshop scheduling problems taken from Benbouzid et al. (2003). A comparison of the solutions yielded by the heuristics developed in this paper with the heuristic solutions given by Taillard (1993) is undertaken with respect to the minimization of performance loss after maintenance insertion. The comparison shows that the proposed integrated GAs are clearly superior to all the analyzed algorithms

The problem of uninterrupted hybrid flow shop scheduling with regard to the fuzzy processing time

Purpose: In this paper, an uninterrupted hybrid flow shop scheduling problem is modeled under uncertainty conditions. Due to the uncertainty of processing time in workshops, which is due to delays in receiving raw materials or machine failure, fuzzy programming method has been used to control the processing time parameter. In the proposed model, there are several jobs that must be processed by machines in sequence. The main purpose of the proposed model is to determine the correct sequence of operations and assign operations to each machine at each stage, so that the total completion time (Cmax) is minimized. Methodology: In this paper, the fuzzy programming method is used to control the uncertain parameter. Also, The GAMS software and CPLEX solver have also been used to solve the sample problems. Findings: The results of solving the problem in small and medium size show that with increasing the rate of uncertainty, the amount of processing time increases and therefore the completion time of the whole work increases. On the other hand, with the increase in the number of machines in each stage due to the high efficiency of the machines, the completion time of all works has decreased. Originality/Value: The most important innovation of this article is the design of uninterrupted hybrid flow shop scheduling with regard to the fuzzy processing time

Transformación de una línea de montaje de modelos mixtos en un taller de flujo regular: Caso de estudio en la factoría Nissan de Barcelona

En este trabajo aplicamos dos modelos de Programación lineal entera mixta, sobre problemas de taller de flujo regular con demanda generalizada de tipos de trabajos, con el propósito de transformar una línea de modelos mixtos en un taller de flujo regular. Para ilustrar dicha aplicación, presentamos un caso de estudio basado en una línea de motores mixtos de la factoría de Nissan en Barcelona. En el estudio se comparan los costes de producción de los dos sistemas productivos enfrentados, llegando a la conclusión de que el sistema taller de flujo regular sin bloqueos entre estaciones es el más competitivo. Como herramienta de resolución hemos empleado el solucionador CPLEX con resultados satisfactorios. Para llevar a la práctica la transformación de la línea de producción en un taller de flujo regular, proponemos un conjunto de requisitos, así como la asistencia al sistema productivo con un sistema de información basado en tecnologías IoT en el marco de la Industria 4.0.Postprint (author's final draft

Minimizing the Makespan for the Flow Shop Scheduling Problem with Availability Constraints

Article dans revue scientifique avec comité de lecture. internationale.International audienceThis paper deals with the scheduling of a flow shop with availability constraints (FSPAC). In such a problem, machines are not continuously available for processing jobs due to a preventive maintenance activity. A small number of solution methods exists in the literature for solving problems with at most two machines and to the author's knowledge only a few of them make use of the non-preemptive constraint. In this paper, two variants of the non-preemptive FSPAC with an arbitrary number of machines and an arbitrary number of unavailability periods on each of them are considered. In the first variant, starting times of maintenance tasks are fixed while in the second one the maintenance tasks must be performed on given time windows. Since the FSPAC is NP-hard in the strong sense, a heuristic approach based on a genetic algorithm and a tabu search is proposed to approximately solve the makespan minimization problem. Computational experiments are performed on randomly generated instances to show the efficiency of the proposed approaches

Minimizing the Makespan for the Flow Shop Scheduling Problem with Availability Constraints

Colloque avec actes et comité de lecture. internationale.International audienceThis paper deals with the scheduling of a flow shop with availability constraints (FSPAC). In such a problem, machines are not continuously available for processing jobs due to a preventive maintenance activity. A small number of solution methods exists in the literature for solving problems with at most two machines and to the author's knowledge only a few of them make use of the non-preemptive constraint. In this paper, two variants of the non-preemptive FSPAC with an arbitrary number of machines and an arbitrary number of unavailability periods on each of them are considered. In the first variant, starting times of maintenance tasks are fixed while in the second one the maintenance tasks must be performed on given time windows. Since the FSPAC is NP-hard in the strong sense, a genetic algorithm and a tabu search approach are proposed to approximately solve the makespan minimization problem. Computational experiments are performed on randomly generated instances to show the efficiency of the proposed approaches