Fernando D. Mele

An agent-based approach for supply chain retrofitting under uncertainty

In this work, decisions that have a long lasting effect on the supply chain (SC) such as the design and retrofit of a production/distribution network are considered. The retrofitting tasks are accomplished by using a SC agent-oriented simulation system, which model each entity belonging to the SC as an independent agent. The starting point is a set of possible design options for the existing SC. For each design alternative a performance index is obtained through the agent-based framework by looking for the best value of the operational variables associated to the resulting network. The proposed methodology allows to address the design of complex SCs which are hard to be modelled otherwise, for example by means of standard mathematical programming tools. Specifically, the multi-agent system is suitable for SCs that are either driven by pull strategies or operate under uncertain environments, in which the mathematical programming approaches are likely to be inferior due to the high computational effort required. The advantages of our approach are highlighted through a case study comprising several plants, warehouses and retailers.

Optimal Planning of Supply Chains for Bioethanol and Sugar Production with Economic and Environmental Concerns

Abstract This work addresses the design of supply chains (SC) for sugar/ethanol production with economic and environmental concerns. The design task is formulated as a bi-criterion mixed-integer linear program (MILP) that simultaneously minimizes the total cost of the network and its environmental performance over the entire life cycle of the product (i.e., sugar and ethanol). The capabilities of our approach are highlighted through a case study based on a real scenario, for which a set of Pareto optimal alternatives is calculated.

Integrating pricing policies in the strategic planning of supply chains: A case study of the sugar cane industry in Argentina

In this paper, we address the strategic planning of supply chains for ethanol and sugar production under uncertainty in the market trends. The design task is formulated as a mixed-integer linear programming (MILP) problem that decides on the capacity expansions of production and storage facilities over time along with the associated sales decisions. The main novelty of the work lies in the incorporation of a price-demand relationship explicitly at the modeling stage. Thus, prices are regarded in our work as decision variables, whereas the demand is determined based on the prices calculated by the model. To incorporate the trade-off between the expected profit and risk that naturally exists in an uncertain environmental of this type, we employ the sample average approximation (SAA) algorithm. The capabilities and possibilities of this approach are demonstrated thought case studies based on Argentinean sugar cane industry.

Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties

A multipurpose/multiproduct plant has to deal with many combinations of tasks sequences and operation rates that lead to accumulation problems. These problems can be handled using storage tanks, but usually their location within the flowsheet is predetermined and not subject to optimization, missing the opportunity to better satisfy the customers. In this work we will determinate the optimal location of storage tanks for the short-term scheduling under uncertainty. A hybrid simulation-based optimization (SBO) strategy was developed and implemented to solve the problems combining stochastic and deterministic solution algorithms.

Financial risk control in a discrete event supply chain

Abstract In this work, a discrete event supply chain is modeled from the point of view of one of the members. The model takes into account uncertainty and it determines an optimal ordering policy so that profit is maximized and financial risk is controlled. Two cases are considered. In one case, uncertain the behavior of the other members of the chain is known while in the other they are not.

Optimal Planning of the Sustainable Supply Chain for Sugar and Bioethanol Production

Abstract The interest in renewable fuels such as bioethanol has significantly increased in the last years all over the world. In this work, a decision-support tool based on a mixed integer linear model for the design of sugarcane supply chains (SC) is developed. The approach considers the minimization of the total SC costs and environmental impact, which is determined according to the Life-Cycle Assessment principles. The solution is a set of Pareto optimal alternatives, i.e. SC configurations with associated strategic planning decisions. The capabilities of the proposed framework are illustrated through a case-study designed on the basis of the current situation in Argentina.

MINLP-based Analytic Hierarchy Process to simplify multi-objective problems: Application to the design of biofuels supply chains using on field surveys

Abstract Multi-objective optimization (MOO) is widely used in engineering systems design and planning. The solution of a MOO problem leads to a set of efficient points (Pareto set) from which decision-makers should identify the one that best fits their preferences. Generating this set requires large computational efforts, and the post-optimal analysis of the solutions becomes difficult as the number of objectives increases. This work introduces an approach based on the Analytic Hierarchy Process (AHP) to overcome these limitations. Through the definition of an aggregated objective function calculated using the AHP algorithm, a single-objective model is constructed that provides a unique Pareto solution of the original MOO model. The AHP is combined with a mixed-integer non-linear programming (MINLP) formulation that simplifies its application and is particularly suited to deal with many objectives (like those arising in sustainable engineering problems). The capabilities of the approach are demonstrated through a case study addressing the sustainable sugar/ethanol supply chain design problem.

Objective reduction in multi-criteria optimization of integrated bioethanol-sugar supply chains

Abstract The design of more sustainable bioethanol supply chains (SCs) has recently emerged as an active area of research. Most of the approaches presented so far focus on minimizing the emitted greenhouse gases (GHG) as unique criterion, neglecting the damage caused in other impact categories. In this work, we address the multi-objective design of integrated sugar/bioethanol SCs considering several life cycle assessment (LCA) impacts. To overcome the numerical difficulties of dealing with several objective functions, we apply a rigorous MILP-based dimensionality reduction method that minimizes the error of omitting objectives.

Multi-objective optimization of integrated bioethanol-sugar supply chains considering different LCA metrics simultaneously

Abstract This work addresses the strategic planning of integrated bioethanol-sugar supply chains (SCs) with economic and environmental concerns. We present a multi-objective mixed-integer linear programming (MILP) formulation that accounts for the simultaneous minimization of cost and environmental impact. The latter criterion is assessed according to the life-cycle assessment (LCA) methodology. The mathematical model is applied to a case study based on the Argentinean sugarcane industry in order to highlight its main advantages.

Event-based Approach for Supply Chain Fault Analysis

This work is a contribution to fault propagation analysis in a supply chain network. An event-based fault detection method is applied to fault propagation analysis validation. The goal of this methodology is to discover and validate fault propagation effects on system variables. This knowledge could be used to improve corrective action design in order to compensate negative effects. The methodology has been applied to supply chain fault propagation analysis over inventory data. Once validated, fault propagation effects on inventory level could be compensated by adapting the inventory control policy. Thus, unnecessary inventory holding could be reduced.