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Thanks to smart technological tools, customers can at any moment create or modify their commands. This reality forced many production firms to become sensitive in rescheduling processes. In the literature, most of rescheduling problems consider classical efficiency measures. However, some existing works also consider stability as a measure for limiting the deviation from initial schedule. In this work, we aim to bridge the gap in existing works on rescheduling by investigating a new approach to measure simultaneously efficiency by the total weighted waiting times and stability by the total weighted completion time deviation. This combination of criteria is very significant in industrial and hospital environments. In this paper, a single machine rescheduling problem with jobs arriving over time is considered. A mixed integer linear programming (MILP) model is designed for this problem and an iterative predictive-reactive strategy for dealing with the online part. Numerical results show that, at each time the jobs are rescheduled, the low weight ones move forward. Consequently, a new concept consisting in increasing the jobs weight as function of time is established. The effect of this new conception is evaluated by the variation of the average flowtime. Eventually, the computing time of the MILP resolution is studied to explore its limitations.
Ayoub Tighazoui; Christophe Sauvey; Nathalie Sauer. Minimizing the Total Weighted Waiting Times and Instability in a Rescheduling Problem with Dynamic Jobs Weight. Applied Sciences 2021, 11, 7040 .
AMA StyleAyoub Tighazoui, Christophe Sauvey, Nathalie Sauer. Minimizing the Total Weighted Waiting Times and Instability in a Rescheduling Problem with Dynamic Jobs Weight. Applied Sciences. 2021; 11 (15):7040.
Chicago/Turabian StyleAyoub Tighazoui; Christophe Sauvey; Nathalie Sauer. 2021. "Minimizing the Total Weighted Waiting Times and Instability in a Rescheduling Problem with Dynamic Jobs Weight." Applied Sciences 11, no. 15: 7040.
Through new technologies development, customers can make or cancel an order at any time, which disrupts the established production schedule. This reality forced many companies to become sensitive in dealing with this situation through rescheduling processes. While efficiency criteria are used to assess the performance of a scheduling system, in dynamic environments, stability criteria measure the impact of job deviation. Differently from previous works, this paper investigates a new performance measure to simultaneously assess schedule efficiency by the total weighted waiting times, and schedule stability by the weighted completion time deviation. This mix could be a very helpful and significant criterion in industrial and health care environments. The studied problem considers an identical parallel machine rescheduling with jobs arriving over time. Based on a predictive-reactive strategy, a Mixed Integer Linear Programming model (MILP) is developed, as well as an iterative methodology for dealing with the online part. At last, numerical results are presented, discussing the impact of the efficiency-stability coefficient on the system performance, as well as the computing time to solve the described problem.
Ayoub Tighazoui; Christophe Sauvey; Nathalie Sauer. Predictive-reactive strategy for identical parallel machine rescheduling. Computers & Operations Research 2021, 134, 105372 .
AMA StyleAyoub Tighazoui, Christophe Sauvey, Nathalie Sauer. Predictive-reactive strategy for identical parallel machine rescheduling. Computers & Operations Research. 2021; 134 ():105372.
Chicago/Turabian StyleAyoub Tighazoui; Christophe Sauvey; Nathalie Sauer. 2021. "Predictive-reactive strategy for identical parallel machine rescheduling." Computers & Operations Research 134, no. : 105372.
Due to the fourth revolution experiencing, referred to as Industry 4.0, many production firms are devoted to integrating new technological tools to their manufacturing process. One of them, is rescheduling the tasks on the machines responding to disruptions. While, for static scheduling, the efficiency criteria measure the performance of scheduling systems, in dynamic environments, the stability criteria are also used to assess the impact of jobs deviation. In this paper, a new performance measure is investigated for a flowshop rescheduling problem. This one considers simultaneously the total weighted waiting time as the efficiency criterion, and the total weighted completion time deviation as the stability criterion. This fusion could be a very helpful and significant measure for real life industrial systems. Two disruption types are considered: jobs arrival and jobs cancellation. Thus, a Mixed Integer Linear Programming (MILP) model is developed, as well as an iterative predictive-reactive strategy for dealing with the online part. At last, two heuristic methods are proposed and discussed, in terms of solution quality and computing time.
Ayoub Tighazoui; Christophe Sauvey; Nathalie Sauer. Predictive-reactive Strategy for Flowshop Rescheduling Problem: Minimizing the Total Weighted Waiting Times and Instability. Journal of Systems Science and Systems Engineering 2021, 1 -23.
AMA StyleAyoub Tighazoui, Christophe Sauvey, Nathalie Sauer. Predictive-reactive Strategy for Flowshop Rescheduling Problem: Minimizing the Total Weighted Waiting Times and Instability. Journal of Systems Science and Systems Engineering. 2021; ():1-23.
Chicago/Turabian StyleAyoub Tighazoui; Christophe Sauvey; Nathalie Sauer. 2021. "Predictive-reactive Strategy for Flowshop Rescheduling Problem: Minimizing the Total Weighted Waiting Times and Instability." Journal of Systems Science and Systems Engineering , no. : 1-23.
Due to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originality of this work consists in simultaneously considering carbon emissions strategies, carbon tax and mandatory emission in a manufacturing-reconditioning system. The proposed system is composed of two parallel machines, a manufacturing stock, a reconditioning stock and a recovery inventory. In order to make the proposed green manufacturing system more realistic, it is assumed that manufactured (new products) and reconditioned products are distinguishable. The quantity of worn products (used products) depends on the sales in the previous periods, and the repair periods of the machines are stochastic and independent. The aim of this work is to determine the optimal capacities of manufacturing and reconditioning stocks that maximize the total profit, as well as the optimal value of worn products under two carbon emissions’ limitations. An evolutionary algorithm is developed, along with an efficient improvement method, to find the optimal value of decision variables. Ultimately, numerical results are provided to show the impact of the period of carbon limit and the worn products (returned products) on decision variables.
Sadok Turki; Soulayma Sahraoui; Christophe Sauvey; Nathalie Sauer. Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation. Applied Sciences 2020, 10, 3534 .
AMA StyleSadok Turki, Soulayma Sahraoui, Christophe Sauvey, Nathalie Sauer. Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation. Applied Sciences. 2020; 10 (10):3534.
Chicago/Turabian StyleSadok Turki; Soulayma Sahraoui; Christophe Sauvey; Nathalie Sauer. 2020. "Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation." Applied Sciences 10, no. 10: 3534.
Since its creation by Nawaz, Enscore, and Ham in 1983, NEH remains the best heuristic method to solve flowshop scheduling problems. In the large body of literature dealing with the application of this heuristic, it can be clearly noted that results differ from one paper to another. In this paper, two methods are proposed to improve the original NEH, based on the two points in the method where choices must be made, in case of equivalence between two job orders or partial sequences. When an equality occurs in a sorting method, two results are equivalent, but can lead to different final results. In order to propose the first improvement to NEH, the factorial basis decomposition method is introduced, which makes a number computationally correspond to a permutation. This method is very helpful for the first improvement, and allows testing of all the sequencing possibilities for problems counting up to 50 jobs. The second improvement is located where NEH keeps the best partial sequence. Similarly, a list of equivalent partial sequences is kept, rather than only one, to provide the global method a chance of better performance. The results obtained with the successive use of the two methods of improvement present an average improvement of 19% over the already effective results of the original NEH method.
Christophe Sauvey; Nathalie Sauer. Two NEH Heuristic Improvements for Flowshop Scheduling Problem with Makespan Criterion. Algorithms 2020, 13, 112 .
AMA StyleChristophe Sauvey, Nathalie Sauer. Two NEH Heuristic Improvements for Flowshop Scheduling Problem with Makespan Criterion. Algorithms. 2020; 13 (5):112.
Chicago/Turabian StyleChristophe Sauvey; Nathalie Sauer. 2020. "Two NEH Heuristic Improvements for Flowshop Scheduling Problem with Makespan Criterion." Algorithms 13, no. 5: 112.
In this paper, we consider a job-shop scheduling problem with mixed blocking constraints. Contrary to most previous studies, where no blocking or only one type of blocking constraint was used among successive operations, we assume that, generally, we may address several different blocking constraints in the same scheduling problem depending on the intermediate storage among machines, the characteristics of the machines, the technical constraints, and even the jobs. Our objective was to schedule a set of jobs to minimize the makespan. Thus, we propose, for the first time, a mathematical model of the job-shop problem taking into account the general case of mixed blocking constraints, and the results were obtained using Mosel Xpress software. Then, after explaining why and how groups of jobs have to be processed, a blocking constraint conflict-free warranted evaluation function is proposed and tested with the particle swarm optimization and genetic algorithm methods. The results prove that we obtained a near-optimal solution to this problem in a very short time.
Christophe Sauvey; Wajdi Trabelsi; Nathalie Sauer. Mathematical Model and Evaluation Function for Conflict-Free Warranted Makespan Minimization of Mixed Blocking Constraint Job-Shop Problems. Mathematics 2020, 8, 121 .
AMA StyleChristophe Sauvey, Wajdi Trabelsi, Nathalie Sauer. Mathematical Model and Evaluation Function for Conflict-Free Warranted Makespan Minimization of Mixed Blocking Constraint Job-Shop Problems. Mathematics. 2020; 8 (1):121.
Chicago/Turabian StyleChristophe Sauvey; Wajdi Trabelsi; Nathalie Sauer. 2020. "Mathematical Model and Evaluation Function for Conflict-Free Warranted Makespan Minimization of Mixed Blocking Constraint Job-Shop Problems." Mathematics 8, no. 1: 121.
Due to rigorous environmental legislations and competitive economics worldwide, a growing number of companies are devoted to recovering and remanufacturing used products. Consequently, over the past few decades, the management of manufacturing/remanufacturing systems has been receiving increasing attention from researchers and companies leaders. Most of the existing research papers in the literature considered that remanufactured products have the same quality and price as new ones. However, in practice, the market perceives new items as higher quality products rather than remanufactured items. This paper aims to bridge the gap in research on manufacturing/remanufacturing supply chain, by investigating an optimal storage and manufacturing/remanufacturing planning, while taking into consideration the difference between new and remanufactured items, random machine failures, carbon constraints and distinct random customer demands for both items types. Furthermore, to make our system more realistic, it is assumed that the return rate of used items depends on the sales in the past periods, machine repair time is stochastic and set-up time period is not negligible. In this study, two models are developed, considering carbon emissions or not, to determine the optimal values of the manufacturing/remanufacturing period lengths and serviceable stock capacities of new and remanufactured items. Numerical results are provided to illustrate the impact of set-up cost, percentage of returned used items, machine availability, carbon cap and carbon trading price on the optimal storage and production planning. Moreover, the influences of carbon cap, carbon trading price and percentage of returned used items on carbon emissions have been analyzed. The results reveal that set-up cost, percentage of returned used items and machine availability have significant impact on storage and production planning of new and remanufactured items. In addition, the results indicate that a lower carbon cap and/or a high carbon trading price, induce the producer to collect and remanufacture used items and curb carbon emissions.
Sadok Turki; Christophe Sauvey; Nidhal Rezg. Modelling and optimization of a manufacturing/remanufacturing system with storage facility under carbon cap and trade policy. Journal of Cleaner Production 2018, 193, 441 -458.
AMA StyleSadok Turki, Christophe Sauvey, Nidhal Rezg. Modelling and optimization of a manufacturing/remanufacturing system with storage facility under carbon cap and trade policy. Journal of Cleaner Production. 2018; 193 ():441-458.
Chicago/Turabian StyleSadok Turki; Christophe Sauvey; Nidhal Rezg. 2018. "Modelling and optimization of a manufacturing/remanufacturing system with storage facility under carbon cap and trade policy." Journal of Cleaner Production 193, no. : 441-458.
This paper deals with the optimization of a manufacturing–remanufacturing–transport–warehousing closed-loop supply chain, which is composed of two machines for manufacturing and remanufacturing, manufacturing stock, purchasing warehouse, transport vehicle and recovery inventory. The proposed system takes into account the return of used end-of-life products from the market. Manufactured and re-manufactured products are stored in the manufacturing stock. The used end-of-life products are stored in the recovery inventory for remanufacturing. The vehicle transports products from the manufacturing stock to the purchasing warehouse. The objective of this work is to simultaneously evaluate the optimal capacities of manufacturing stock, purchasing warehouse and the vehicle, as well as the optimal value of returned used end-of-life products. Those four decision variables minimize the total cost function. A discrete flow model, which is supposed to be the most realistic, is used to describe the system. An optimization program, based on a genetic algorithm, is developed to find the decision variables. Numerical results are presented to study the influence of transportation time, unit remanufacturing cost and configuration of the manufacturing/remanufacturing machines on the decision variables.
Sadok Turki; Stanislav Didukh; Christophe Sauvey; Nidhal Rezg. Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain. Sustainability 2017, 9, 561 .
AMA StyleSadok Turki, Stanislav Didukh, Christophe Sauvey, Nidhal Rezg. Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain. Sustainability. 2017; 9 (4):561.
Chicago/Turabian StyleSadok Turki; Stanislav Didukh; Christophe Sauvey; Nidhal Rezg. 2017. "Optimization and Analysis of a Manufacturing–Remanufacturing–Transport–Warehousing System within a Closed-Loop Supply Chain." Sustainability 9, no. 4: 561.