An integrated planning model for multi-supplier, multi-facility, multi-customer, multi-product and multi-period : application to the wood furniture industry

Typiquement, un réseau de création de valeur dans l'industrie du meuble en bois, est composé de fournisseurs de billes de bois, de scieries, de séchoirs, d'usines de meubles, de centres de distribution et de détaillants. Dans cette thèse, nous nous concentrons sur l'étude du réseau qui assure l'approvisionnement des usines de meubles en bois. La problématique à laquelle font face les entreprises de ce réseau se situe principalement au niveau de la synchronisation des flux de matière. Ces derniers doivent respecter les contraintes de capacité, de procédés, de transport et la diversité des produits, pour satisfaire la demande. La planification, dans ce contexte, repose sur une vision locale ce qui affecte la performance globale du réseau. L'objectif de cette thèse est de proposer un modèle de planification intégrée dans un contexte, multifoumisseurs, multiusines, multiproduits, multiclients et multipériodes, qui vise la synchronisation des flux, et la maximisation de la performance globale tout en respectant les différentes contraintes du réseau. Nous proposons un modèle générique du problème de planification intégrée qui permet de déterminer les décisions tactiques d'approvisionnement, d'inventaire, de flux de matière et de sous-traitance. Ce modèle est un programme linéaire mixte en nombres entiers de grande taille. Nous avons développé une heuristique basée sur la décomposition dans le temps qui exploite l'aspect multipériodes du problème de planification. Nous avons aussi proposé deux solutions basées sur la décomposition de Benders et la décomposition croisée pour réduire le temps de résolution. Enfin, ce modèle a été validé en utilisant les données réelles de l'entreprise partenaire du projet et les résultats, montrent des réductions potentielles du coût total des opérations de l'ordre de 22%. L'approche de planification intégrée adoptée ainsi que les méthodes de résolution proposées dans cette thèse peuvent être exploitées pour la planification des réseaux dans d'autres secteurs d'activités ayant des similarités avec la problématique traitée dans cette thèse

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Pomiar wydajności zarządzania zielonymi łańcuchami dostaw

Only what is measured can be managed properly. And the measurement process should serve a continuous improvement of companies and whole supply chains. Data from the performance measurement system should cause an increase of cooperation and help in taking right decisions about changes at the operational level, and on the other hand, are an important information when redefining strategies. This will allow for the development of the supply chain based on knowledge, in which the scope of cooperation is literally unlimited (including green aspects). There are two basic approaches to measuring the performance of supply chains: a comprehensive measurement that measures the results of the entire chain (which can be divided into individual tiers and levels) and partial measurement when we measure only certain aspects. Often, in practice, only measurement of separately operating companies is practiced by companies, not throughout chains. And the problem is even more evident when it comes to measuring performance of green activities in integrated supply chains. The paper presents the possibilities of evaluation of GSCM performance. The major challenges and obstacles are presented and assessed.Tylko to, co jest mierzone, może być właściwie zarządzane. Proces pomiaru powinien służyć ciągłemu doskonaleniu przedsiębiorstw i całych łańcuchów dostaw. Dane z systemu pomiaru powinny powodować wzrost współpracy i pomagać w podejmowaniu decyzji o zmianach na poziomie operacyjnym, a z drugiej strony może to być ważna informacja przy przedefiniowaniu strategii. Pozwala to na rozwój łańcuchów dostaw opartych na wiedzy, gdzie zakres współpracy jest dosłownie nieograniczony (dotyczy to również aspektów ekologicznych). Istnieją dwa podstawowe podejścia do pomiaru wydajności łańcucha dostaw: kompleksowy pomiar, który patrzy na wyniki całego łańcucha (który można rozdzielić na poszczególne szczeble i poziomy), oraz pomiar częściowy, gdy mierzymy tylko niektóre aspekty. Często praktykowany jest tylko pomiar oddzielnie działających firm, a nie całego łańcucha. Problem jest jeszcze bardziej widoczny, jeśli chodzi o pomiar wydajności działań ekologicznych w zintegrowanych łańcuchach dostaw. W artykule opisano możliwości oceny wyników GSCM. Przedstawiono i oceniono główne wyzwania i przeszkody stojące przed pomiarem wyników zielonych łańcuchów dostaw

A Review on Remanufacturing Reverse Logistics Network Design and Model Optimization

Remanufacturing has gained great recognition in recent years due to its economic and environmental benefits and effectiveness in the value retention of waste products. Many studies on reverse logistics have considered remanufacturing as a key node for network optimization, but few literature reviews have explicitly mentioned remanufacturing as a main feature in their analysis. The aim of this review is to bridge this gap. In total, 125 papers on remanufacturing reverse logistics network design have been reviewed and conclusions have been drawn from four aspects: (1) in terms of network structure, the functional nodes of new hybrid facilities and the network structure combined with the remanufacturing technologies of products are the key points in the research. (2) In the mathematical model, the multi-objective function considered from different aspects, the uncertainty of recovery time and recovery channel in addition to quantity and quality, and the selection of appropriate algorithms are worth studying. (3) While considering product types, the research of a reverse logistics network of some products is urgently needed but inadequate, such as medical and furniture products. (4) As for cutting-edge technologies, the application of new technologies, such as intelligent remanufacturing technology and big data, will have a huge impact on the remanufacturing of a reverse logistics network and needs to be considered in our research

On the time-consistent stochastic dominance risk averse measure for tactical supply chain planning under uncertainty

In this work a modeling framework and a solution approach have been presented for a multi-period stochastic mixed 0–1 problem arising in tactical supply chain planning (TSCP). A multistage scenario tree based scheme is used to represent the parameters’ uncertainty and develop the related Deterministic Equivalent Model. A cost risk reduction is performed by using a new time-consistent risk averse measure. Given the dimensions of this problem in real-life applications, a decomposition approach is proposed. It is based on stochastic dynamic programming (SDP). The computational experience is twofold, a compar- ison is performed between the plain use of a current state-of-the-art mixed integer optimization solver and the proposed SDP decomposition approach considering the risk neutral version of the model as the subject for the benchmarking. The add-value of the new risk averse strategy is confirmed by the compu- tational results that are obtained using SDP for both versions of the TSCP model, namely, risk neutral and risk averse.The authors would like to thank to the two anonymous review- ers for their help on clarifying some concepts presented in the manuscript and strongly improving its presentatio

Optimal Kiln Dry Allocation for Dry Timber Preparation to Minimize Cost

Optimization models are increasingly developed for planning and scheduling in manufacturing of natural resources. However, the uncertainty of material from natural resources makes it more difficult to develop a model. In this paper, we concern about the cost of dry timber preparation for finishing process in a wood-board manufacturer. Based on characteristics of the material and wood-board production process, we develop two models to minimize transportation and drying cost of wood supply. The models consider the capacity of facilities, distances among facilities, and timber specification-based drying periods. The model is solved using linear programming, result in drying allocation of kiln dry�s chambers that gives the minimum cost of the process. A sensitivity analysis is conducted to demonstrate the effect of variation of internal capacity and external capacity to the objective function value. The results show that the total cost is more sensitive to the variation of the external capacity of kiln dry than the variation of the internal capacity

Integrated tactical planning in the lumber supply chain under demand and supply uncertainty

Lumber supply chain includes forests as suppliers, sawmills as production sites, distribution centers, and different types of customers. In this industry, the raw materials are logs that are shipped from forest contractors to sawmills. Logs are then sawn to green/finished lumbers in sawmills and are distributed to the lumber market through different channels. Unlike a traditional manufacturing industry, the lumber industry is characterized by a divergent product structure with the highly heterogeneous nature of its raw material (logs). Moreover, predicting the exact amount of the product demand and the availability of logs in the forest is impossible in this industry. Thus, considering random demand and supply in the lumber supply chain planning is essential. Integrated tactical planning in a supply chain incorporates the synchronized planning of procurement, production, distribution and sale activities in order to ensure that the customer demand is satisfied by the right product at the right time. Briefly, in this dissertation, we aim at developing integrated planning tools in lumber supply chains for making decisions in harvesting, material procurement, production, distribution, and sale activities in order to obtain a maximum robust profit and service level in the presence of uncertainty in the log supply and product demand. In order to gain the latter objectives, we can categorize this research into three phases. In the first phase, we investigate the integrated annual planning of harvesting, procurement, production, distribution, and sale activities in the lumber supply chain in a deterministic context. The problem is formulated as a mixed integer programming (MIP) model. The proposed model is applied on a real-size case study, which leads to a large-scale MIP model that cannot be solved by commercial solvers in a reasonable time. Consequently, we propose a Lagrangian Relaxation based heuristic algorithm in order to solve the latter MIP model. While improving significantly the convergence, the proposed algorithm also guarantees the feasibility of the converged solution. In the second phase, the uncertainty is incorporated in the lumber supply chain tactical planning problems. Thus, we propose a multi-stage stochastic mixed-integer programming (MS-MIP) model to address this problem. Due to the complexity of solving the latter MS-MIP model with commercial solvers or relevant solution methodologies in the literature, we develop a Hybrid Scenario Cluster Decomposition (HSCD) heuristic algorithm which is also amenable to parallelization. This algorithm decomposes the original scenario tree into a set of smaller sub-trees. Hence, the MS-MIP model is decomposed into smaller sub-models that are coordinated by Lagrangian terms in their objective functions. By embedding an ad-hoc heuristic and a Variable Fixing algorithm into the HSCD algorithm, we considerably improve its convergence and propose an implementable solution in a reasonable CPU time. Finally, due to the computational complexity of multi-stage stochastic programming approach, we confine our formulation to the robust optimization method. Hence, at the third phase of this research, we propose a robust planning model formulated based on cardinality-constrained method. The latter provides some insights into the adjustment of the level of robustness of the proposed plan over the planning horizon and protection against uncertainty. An extensive set of experiments based on Monte-Carlo simulation is also conducted in order to better validate the proposed robust optimization approach applied on the harvesting planning in lumber supply chains

Models, methods and algorithms for supply chain planning

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.An outline of supply chains and differences in the problem types is given. The motivation for a generic framework is discussed and explored. A conceptual model is presented along with it application to real world situations; and from this a database model is developed. A MIP and CP implementations are presented; along with alternative formulation which can be use to solve the problems. A local search solution algorithm is presented and shown to have significant benefits. Problem instances are presented which are used to validate the generic models, including a large manufacture and distribution problem. This larger problem instance is not only used to explore the implementation of the models presented, but also to explore the practically of the use of alternative formulation and solving techniques within the generic framework and the effectiveness of such methods including the neighbourhood search solving method. A stochastic dimension to the generic framework is explored, and solution techniques for this extension are explored, demonstrating the use of solution analysis to allow problem simplification and better solutions to be found. Finally the local search algorithm is applied to the larger models that arise from inclusion of scenarios, and the methods is demonstrated to be powerful for finding solutions for these large model that were insoluble using the MIP on the same hardware