Philippe Marier

The generalized Shifting Bottleneck Procedure

Abstract We generalize the Shifting Bottleneck Procedure (SBP), proposed by Adams et al. in 1988 for jobshop scheduling, to solve various types of scheduling problems including openshops, assembly shops and shops where only a partial ordering on operations pertaining to each job or machine is specified. In its original version, SBP uses a clever definition of the bottleneck value of a machine to iteratively construct a schedule by solving a number of a certain one machine scheduling problem. We show how the same definition can be extended to measure the bottleneck value of a job. The optimization procedure then proceeds to iteratively fix both job and machine sequences. The outcome of this study is a unified solution procedure for solving various classes of scheduling problems namely openshops, jobshops, assembly shops and shops with partial precedence constraints. Computational testing on a set of randomly generated problems demonstrates that performance depends on the distribution of the work content of jobs and machines: the higher the coefficient of variation of the work content, the better the solutions.

Optimization/simulation-based framework for the evaluation of supply chain management policies in the forest product industry

This work describes a framework for the elaboration and evaluation of management policies for production and transportation supply chains in the forest product industry. The approach deals with the issue of coordination between the tactical and operational decision levels. First, we introduce LogiLab, a software system allowing to model the network and to optimize product flows in the supply chain. We than show how one can use this tactical aggregated plan to identify management policies that will guide day to day operations at the operational level. Finally, a discrete event simulation model allows assessing with more details what would be the impact of implementing these policies at the operational/execution level.

Evaluating order acceptance policies for divergent production systems with co-production

The impacts of using different order acceptance policies in manufacturing sectors are usually well known and documented in the literature. However, for industries facing divergent processes with co-production (i.e. several products produced at the same time from a common raw material), the evaluation, comparison and selection of policies are not trivial tasks. This paper proposes a framework to enable this evaluation. Using a simulation model that integrates a custom-built ERP, we compare and evaluate different order acceptance policies in various market conditions. Experiments are carried out using a case from the forest products industry. Results illustrate how and when different market conditions related to divergent/co-production industries may call for available-to-promise (ATP), capable-to-promise (CTP), and other known strategies. Especially, we show that advanced order acceptance policies like CTP may generate a better income for certain types of market and, conversely to typical manufacturing industries, ATP performs better than other strategies for a specific demand patterns.

Human-machine interaction for real-time linear optimization

Mixed-Initiative-Systems (MIS) are hybrid decision-making systems in which human and machine collaborate in order to produce a solution. This paper described an MIS system adapted to business optimization problems. These problems can be solved in less than an hour as they show a linear structure. However, this delay is unacceptable for iterative and interactive decision-making contexts where users need to provide their input. Therefore, we propose a system providing the decision-makers with a convex hull of optimal solutions minimizing/maximizing the variables of interest. The users can interactively modify the value of a variable and the system is able to recompute a new optimal solution in a few milliseconds. Four real-time reoptimization methods are described and evaluated.

Developing training for industrial wood supply management

An understanding of supply chain management is a prerequisite for efficient supply operations. This paper presents the structure of training currently used in Sweden to prepare master’s-level foresters for managing wood supply operations. Based on a basic framework of professional tasks, eight key learning outcomes are targeted; one focuses on raw material requirements, three on securing supply, three on enabling delivery, and one on control and coordination. Sixteen exercises are used to meet the eight learning outcomes. An overview of the exercises is presented as well as the pedagogical approach used. Current training is focused on developing student understanding of the industrial context as well as competences and skills required to solve typical professional tasks. The paper concludes with a discussion of further development opportunities including a coupling of tasks and learning outcomes with applicable operations research methodology.

Improving a hardwood flooring cutting system through simulation and optimization

Hardwood flooring mills transform rough wood into several boards of smaller dimensions. For each piece of raw material, the system tries to select the cutting pattern that will generate the greatest value, taking into account the characteristics of the raw material. However, it is often necessary to choose less profitable cutting patterns in order to respect market constraints. This reduces production value, but it is the price to pay in order to satisfy the market. We propose an approach to improve production value. We first use simulation on a training set of virtual boards in order to generate a database associating cutting patterns to expected production value. Then, we use an optimization model to generate a production schedule maximizing the expected production value while satisfying production constraints. The approach is evaluated using industrial data. This allows recovering approximately 30 % of the value lost when using the original system.

Designing a generic human-machine framework for real-time supply chain planning

Abstract Mixed-Initiative-Systems (MIS) are hybrid decision-making systems in which human and machine collaborate in order to produce a solution. This paper described an MIS adapted to business optimization problems. These problems can usually be solved in less than an hour as they show a linear structure. However, this delay is unacceptable for iterative and interactive decision-making contexts where users need to provide their input. Therefore, we propose a system providing the decision-makers with a convex hull of optimal solutions that minimize/maximize the variables of interest. The users can interactively modify the value of a variable and the system is able to recompute a new optimal solution in a few milliseconds. Four real-time reoptimization methods are described and evaluated. We also propose an improvement to this basic scheme in order to allow a user to explore near-optimal solutions as well. Examples showing real case of how we have exploited this framework within interactive decision support software are given.

Game—The Online Wood Supply Game

This paper describes the Wood Supply Game (WSG), a prize-winning e-learning tool that is freely available for players all over the world. The game effectively helps students and managers realize the challenges in managing demand and supply in wood supply chains, and gain insight into the types of measures required to make these divergent chains effective. The WSG is an adaptation of the Beer game, a popular didactic tool used to empirically demonstrate demand amplification in a simple and generic context. The supply chain modeled by the Beer game does not involve co-products, and thus is very different from the wood supply chain, which is divergent by nature. The WSG presented in this paper models a supply network with one point of divergence and demand for two products. This preserves the simplicity of the game but enables it to offer a base for supply network simulation in a large number of industrial sectors with divergent processes. We describe an online version of the WSG, discuss our experiences pla...