Mathematical Programming Approaches for Stable Tactical and Operational Planning in Supply Chain and APS Context

Thomas, André; Genin, Patrick; Lamouri, Samir

doi:10.3166/jds.17.425-455

Cited by 11 publications

(7 citation statements)

References 20 publications

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“…Named hierarchical production planning by Hax and Meal (1973), this is a typical approach carried out in many research papers up to now (Thomas et al 2008).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Comelli et al (2008) propose an approach to synchronise financial and physical flows in supply chains at tactical level, allowing for budgeting in production planning with APS tools. Thomas et al (2008) present a procedure for tactical supply chain planning based on mathematical programming to produce stable master production schedules following a robust reference plan policy generated through sales and operations planning procedures. Based on the known MIT's Beer Game, von Lanzenauer and Pilz-Glombik (2002) propose a mixed-integer programming model to support tactical decision level covering ordering, producing and transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

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Agent-based experimental investigations of the robustness of tactical planning and control policies in a softwood lumber supply chain

Santa-Eulalia

Aït‐Kadi

D’Amours

et al. 2011

Production Planning & Control

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This article investigates the robustness of different tactical planning and control policies for a softwood supply chain using an agent-based environment that simulates a distributed advanced planning and scheduling system and its corresponding supply chain operations. Simulations were modelled using a novel agent-based methodology combined with a robust experimental design approach and an industrial data set obtained from two companies in Eastern Canada. Experimental results provide insights about the dynamic relations among factors related to control levels, planning methods and planning horizon lengths. Results indicate that supply chain control levels play a relevant role in defining robust service levels, while the planning horizon and the planning method have lower impact in this context. In addition, from the supply chain inventory level point of view, we verified that the three investigated tactical rules have to be configured together if one desires to maximise their contribution for a robust supply chain system capable of coping with uncertainties from the business environment. When these rules are evaluated individually, it is not possible to make the most of their potential due to interactions between them. The article concludes by proposing an optimum robust configuration of the tactical rules to minimise the impact of supply chain uncertainties.

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“…Named hierarchical production planning by Hax and Meal (1973), this is a typical approach carried out in many research papers up to now (Thomas et al 2008).…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Agent-based experimental investigations of the robustness of tactical planning and control policies in a softwood lumber supply chain

Santa-Eulalia

Aït‐Kadi

D’Amours

et al. 2011

Production Planning & Control

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“…In SCRM, supply chain planning basically covers three decision levels: strategic planning, tactical planning and operational planning [31]. In this section, we study the ABMS in terms of the planning decision levels they focus on in SCRM.…”

Section: Supply Chain Planning Decision Levelsmentioning

confidence: 99%

Agent-Based Modeling and Simulation for Supply Chain Risk Management - A Survey of the State-of-the-Art

Chen

Ong

Tan

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Due to the complex nature and numerous interacting factors that contributes to the increased vulnerability of supply chains, traditional methods have been found to be inadequate for Supply Chain Risk Management (SCRM). Agent-Based Modeling and Simulation (ABMS), an agent-oriented approach to model and simulate complex adaptive systems, represents a recent development in supply chain planning that has been regarded highly appropriate for studying risk management [1-4]. The objective of this paper is to provide a multi-perspective survey of the state-of-the-art agent based modeling and simulation approaches for SCRM.Keywords-supply chain risk management; agent-based modeling and simulation; survey; supply chain risk management process; planning decision levels;supply chain design goals

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“…Finally, Thomas et al (2008) propose a mathematical programming method to obtain a stable MPS. This approach is developed with a two steps model at tactical level.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation of Less Master Production Schedule Nervousness Model

Herrera¹,

Thomas²

2009

IFAC Proceedings Volumes

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In production decision making systems, Master Production Schedule (MPS) states the requirements for individual end items by date and quantity. The solution sensitivity to demand forecast changes, unforeseen supplier and production problem occurrences, is known as nervousness. This feature cause undesirable effects at tactical and operational levels. Some of these effects are production and inventory cost increases and, also, negative impacts on overall and labor productivity. To tackle this problem, we proposed a Mixed Integer Programming (MIP) model where nervousness reduction is carry out finding minimal suboptimal solutions. We perform a simulation under rolling planning horizon environment considering stochastic demand. Results of simulation show that, at each time demand changes take place the model can adjust the solution to achieve less nervousness without a significative change in cost performance.

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Mathematical Programming Approaches for Stable Tactical and Operational Planning in Supply Chain and APS Context

Cited by 11 publications

References 20 publications

Agent-based experimental investigations of the robustness of tactical planning and control policies in a softwood lumber supply chain

Agent-based experimental investigations of the robustness of tactical planning and control policies in a softwood lumber supply chain

Agent-Based Modeling and Simulation for Supply Chain Risk Management - A Survey of the State-of-the-Art

Simulation of Less Master Production Schedule Nervousness Model

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