13h30 - 13h55
Medical mask reverse supply chain design and planning: a case study in Montreal region
The world is being exposed to a global health crisis due to COVID-19. This situation is generating an unprecedented increase in the use of single-use medical materials, notably procedural facemasks. This work studies the design and planning of a reverse supply chain for dealing with end-of-life procedural facemasks. The main benefits are the correct disposal of contaminated products, pollution reduction, new jobs creation and component recycling. An optimization model to efficiently collect and recycle used procedural facemasks is proposed. The reverse supply chain network considered includes virgin raw material suppliers, facemask manufacturing centers, warehouses, distribution centers, business clients, collection centers, dismantling and remanufacturing centers, and finally buyers of the recycled components. A realistic case study is created based on real data gathered from different industrial partners in Montreal region. Decisions to be made include material flows in the network as well as the location of new dismantling and remanufacturing centers to minimize the total costs of the supply chain and reduce pollution. Various scenarios will be analyzed to identify the conditions under which the reverse supply chain is profitable.
13h55 - 14h20
Optimization of production inventory in a multi-echelon supply chain under mixed production policies: an application in the pulp and paper industry
There are different ways for managing customer demands in the form of vendor managed inventory (VMI), make to order (MTO), and make to stock (MTS) policies, that have a direct effect on the performance of production systems in terms of service level and logistics costs. This study proposes an optimization model to coordinate production, inventory, and distribution decisions in a multi-echelon supply chain consisting of production units, cross docks, warehouses, and customers by determining the customers served under VMI, MTO and MTS policies. The applicability of the presented model is analyzed through a case study motivated from a real-world application in the pulp and paper industry.
14h20 - 14h45
Multi-period scheduling for ready-mixed concrete trucks
We study the problem of scheduling truck drivers over multiple periods for a ready-mixed concrete (RMC) company. Multiple production plants are available to satisfy the requests of several construction sites. A fixed fleet of heterogenous trucks is available each day to transport RMC from production plants to construction sites. The problem looks for a weekly schedule for drivers that minimizes travel times, waiting duration of trucks at construction sites, and idle durations of drivers. We propose a solution method based on an iterative two-stage approach. For each day and for each driver, we determine the starting working time in stage one, then we optimize the routes in stage two using a framework composed of a large neighborhood search and a local search. We assess our solution approach based on real data from an industrial partner. Computational results show that the proposed solution approach outperforms the approach used by the company.
14h45 - 15h10
Newsvendor problem in a multi-period supply chain
We study a modeling framework for the newsvendor problem in the context of short-life-cycle product management involving multiple stages comprising production, shipping, selling and discount periods. In this context, the aspects of time and holding cost are explicitly captured in the newsvendor model. Production and demand are gradually accumulated over time. This results in a problem where the standard newsvendor model can no longer be used. We present efficient solution procedure for this stochastic optimization problem. Approximation methods are also proposed which can take advantage of the standard newsvendor model. We conduct numerical studies, the results of which demonstrate the higher profitability of our modeling framework compared to the standard newsvendor model, in the context of the problem.