Supply Chains and Inventory I

Contributed Session

Time Slot: Friday Morning

Room: 001

Chair: Giuseppe Stecca

Mathematical programming models for managing the profitability-sustainability trade-off in complex chemical value chains

Time: 11:30

Matteo Cosmi (University of Luxembourg), Arts Joachim, Klosterhalfen Steffen

Limiting the effects of global warming and climate change is one of the main objectives that the international community has set for the next decades. Therefore, several countries approved laws legally binding them to achieve net-zero targets within the next 25-30 years. One of the major greenhouse gases emitted by human activity is carbon dioxide (CO2) which accounts for more than 75% of the global greenhouse gas emissions. Industry and transport sectors account for more than 35% of the global emissions and there is increasing pressure on industry to pledge net-zero emissions. To remain competitive in their markets while reducing their emissions, companies need to re-optimize their entire supply chain focusing not only on financial key performance indicators (KPIs), such as costs, but also on non-financial KPIs, in particular greenhouse gas emissions. In this work we propose two linear programming models to optimize a deterministic multi-objective supply chain problem aimed at minimizing CO2 emissions and their related costs. We perform an extensive campaign of tests motivated by a real-world industry setting to compare the efficiency of the two model formulations and to analyze the differences with the former supply chain structure when emissions were not a primary concern.

Generalized Model of a Production System with Fixed Supplies and Deliveries

Time: 11:50

Giorgio Romanin Jacur (Dept of Management and Engineering, University of Padova, Italy), Arturo Liguori

Let us consider a generic production system; at a look from the outside, we see that it gets raw materials from its suppliers and delivers finished products to its customers; raw materials may be either stocked in a buffer, to be worked later, or immediately taken as semifinished products and addressed to the workshop; inside the workshop semifinished products are subjected to one or more successive operations, with the scope of creating final products requested by the customers at given delivery times; every operation may require specific technical resources (rooms, work benches, machines, work islands, etc.) and human resources (operators with different skills and tasks). The problem daily faced by managers consists in scheduling all operations in order to minimize total cost by satisfying all customers and respecting constraints imposed by resources’ and raw materials’ availability. Such a problem becomes more and more complex if final products are many, some final products can be obtained by different alternative working procedures, and/or from different raw materials, by means of different operations and related resources’ engagement, some resources can be engaged to work different semifinished products; moreover sometimes we cannot precisely forecast supplies, and sometimes customers’ requests may vary after the requested products’ working procedures have already started (such accidents happen in particular in the food field and when the system works on commission). Here we suggest an abstract metamodel which can describe such complex systems and permits to obtain an operation schedule which optimizes their management also in dynamic conditions. We may consider the environment and the following sets: semifinished products set, process set, resources set. Semifinished products are all objects entering the system, being subjected to operations and possible pauses inside it and finally delivered; every semifinished product is uniquely defined according to its physical characteristics (materials, shape, size, weight, etc.) and may be present in the system in lots of any size in different times: every lot is characterized by number of units and arise time, related either to entering from the environment or to production by an operation. Every process is uniquely defined by the performed operation, the input and output semifinished products, the engaged resources, and the related respective times: the possible adjiustment time before the operation start, the production time, the amounts of input and output products per production unit time, the amounts of engaged resources during the adjustment and/or during the production; two processes are different if any of the above definition characters is different; the same process may be iteratively activated in different times. The environment supplies semifinished products, either directly through suppliers in the form of raw materials or indirectly through buffers, and requests semifinished products, to be delivered either to customers in the form of finished products or to be stored in buffers. System structural parameters are stored in matrices reporting processes’ characters; problem data include products’ forecasted supplies, products’ requested deliveries and resource availability in time; decision variables include all processes’ activations start and end time, related to input and output products’ amount and to resources’ amounts. The management problem solution shall respect all constraints due to available semifinished products and available resources in time and obtain the minimum total cost. An optimal solution can be obtained by specialized packages for small problem size, while a heuristic method giving an acceptable suboptimal solution, adopting algorithms coming from the project management field is suggested for large problem size. An application in the food production and distribution field is reported.

A model and a solution approach for optimal green investment in a two stage supply chain

Time: 12:10

Giuseppe Stecca (Istituto di Analisi dei Sistemi e Informatica “Antonio Ruberti” IASI-CNR), Massimiliano Caramia

In order to contrast climate change, governments established strong chronological paths to reach emission reduction in the next years. The European Commission recently deployed the so called European Green Deal, i.e., a set of policy initiatives aimed at overarching the carbon neutrality in 2050 and achieving a reduction of 55% of net Green House Gas (GHG) within 2030.While clean technologies can help to decrease environmental impact, investment programs must be carefully planned to reach the green targets and maintain or improve industrial efficiency. This is extremely important in supply chains where industrial technologies have a complex impact on efficiency, service level, and emissions of entire production and distribution chains. Moreover, investments in green technologies to increase sustainability in supply chains has become a common practice also because the awareness of consumers on green products is continuously increasing and, therefore, people are more and more willing to buy green products in place of non-green ones. Therefore, even if there are higher costs in producing with green technologies and processes, there is also a higher mark up on the price of products which rewards the former costs.In this work, we propose a multi-period mathematical model for deciding the optimal chronological allocation of a given investment budget on production technologies and on environment protection to meet an aggregate demand in a two layered supply chain. The model has two objectives and non-linear constraints. The main decisional variables are the flow of products from suppliers to facilities, and the environment protection investment for each facility and for each planning period. The objective function measures the total cost of CO2 emission produced by the plants over time plus the cost associated with the investment over time. Other than flow and capacity constraints, a non-linear constraint defines the relation between the investment made until a certain time,
for each facility, and the emission for unit of flow at that time, for the same facility.Being the model very difficult to solve by means of a commercial solver, we propose lower bounds and an approximate solution approach. The proposed model and algorithms have been tested on synthetic instances properly generated to evaluate their ability in finding effective schedules of the investments in a given planning horizon.

Design forward and reverse closed-loop supply chain to improve economic and environmental performances

Time: 12:30

EP Mezatio (University of Technology of Troyes (UTT), Troyes, France), MM. Aghelinejad, L. Amodeo, I. Ferreira

This paper focuses on modelling and solving the problems related to fourlevel supply chain (SC) management with reverse logistics, from the supplier to the retailers and the recycling center. A new mathematical integer programming model has been developed. This model can be used as a decision support tool for all types of industries that want to improve their economic and environmental performances. In this study, we adressed specially the case of the textile industry. The results show that by recycling and reusing recycled resources, the textile industry can reduce its CO2 emissions up to 42.5%, for an additional investment of 34.19%, with a carbon price of 86 € per ton of emissions. While, without recycling and for the same carbon price, industries would invest 68.73% more, for an emissions’ reduction of 12.74%.