1,720,976 research outputs found
Enterprise optimization for solving an assignment and trim-loss non-convex problem
Get PDFIn the present work, the planning and cutting problem for the corrugated board boxes industries is presented. This problem belongs to the category of the trim-loss problem, which is essential in the paper-converting supply chain management. Bilinear terms in demand and stock constraints, for instance, lead to a non-convex formulation. Two global convex models are formulated and tested. Results obtained in the problem solution are shown. The most efficient model is implemented by means of Java programs and GAMS, a mathematical optimization program. The system is linked to the company ERP (enterprise resource planning) system. Several issues are optimized and improved: waste generation, energy demand, environmental impact and production costs. Paper reel stock management is improved due to more accurate and statistical information obtained by the system. The planning system linked to the ERP connection allows the integration of customers and suppliers increasing the company competitiveness.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin
Integrated planning and scheduling with due dates in corrugated board boxes industry
Get PDFAn integrated approach that solves the cutting stock problem and scheduling is considered in this article. The main challenging characteristics of this problem are given by its combinatorial nature, as well as the nonconvexities appearing in the formulation. Scheduling decisions are directly affected by cutting patterns and present changeover times that are sequence-dependent. Given the problem complexity, in general, cutting stock optimization has been considered independently from the scheduling problem. However, a cutting plan that defines the sequence in which patterns are processed is essential in order to obtain a solution in the context of corrugated board boxes industry. In order to obtain a global solution, the approach that has been developed uses a disjunctive technique to transform the original nonconvex formulation into a mixed-integer linear programming (MILP) model; whereas a continuous time representation is assumed to model sequencing decisions by applying general and immediate precedence constraints. Both scheduling models are presented and compared in three examples, showing efficient solutions for the integrated problem.Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin
Inventory and delivery optimization under seasonal demand in the supply chain
No full textThis work deals with the inventory, purchase and delivery optimization problem in the supply chain. The formulation of two problems is presented involving several decision levels. The first one optimizes the company inventory and purchase tasks in a medium-term horizon planning, assuming that the total amount purchased is delivered at the beginning of each period. Then, in a more detailed formulation, the purchased amount is distributed among several deliveries giving rise to a non-linear non-convex problem. Some transformation techniques are evaluated to overcome the non-convexities in order to find a global solution in a reasonable execution time. Finally, the results obtained considering some possible scenarios are analyzed and compared.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin
A comparative assessment of linearization methods for bilinear models
No full textIn this article, optimization problems with bilinear constraints involving one discrete variable are studied. Several industrial problems present bilinear non-convex constraints which are difficult to solve to global optimality. For this purpose models must be reformulated what in general terms increases the problem size. This article proposes two disjunctive transformation techniques which are compared to other approaches presented in the literature. An analysis is made comparing qualitative and quantitative characteristics of the methods employed. In order to implement proposed transformations, three industrial cases are studied: trim-loss in a paper mill, cutting stock in the production of carton board boxes and the purchase, inventory and delivery optimization problem. All of them are reformulated and solved using the strategies included in the paper. Several instances of each problem are evaluated and their results are analyzed comparing performance of the different methods.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin
Logical and generalized disjunctive programming for supplier and contract selection under provision uncertainty
Get PDFSupply-chain optimization is a key issue in gainnig competitiveness in today's economies where buyers and suppliers develop long-term relationships. Final agreements are formalized by signing contracts involving the purchasing of large amounts of materials, taking advantage of economies of scale. Although establishing agreements with suppliers is definitely an important step in reducing uncertainty, uncertainty never completely disappears. For that reason, the problem addressed in this article is the delivery and purchase optimization in a supply chain under provision uncertainty. Several decisions are presented in this problem that can naturally be posed in terms of of discrete decision models and generalized disjunctive programming. Uncertainty is modeled through a new approach that avoids the drawbacks of traditional methods. The goal pursued in this article is to contribute to better raw-material usage and tactical decisions to face an uncertain provision process in the supply chain.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin
Mid-term planning optimization model with sales contracts under demand uncertainty
No full textUncertainty modeling is a challenging topic in supply chain and operation management. When planning material purchase and stock levels, demand uncertainty could have an important impact on the plan results and its feasibility. Additionally, uncertainty could greatly affect customer satisfaction, inventory costs and company profits. From a modeling perspective, problems considering uncertainty are difficult to tackle and lead to complex optimization approaches. This work proposes a mid-term planning model dealing with sales contracts to diminish the effect of uncertainty. Another interesting feature is given by the selection of different price levels. Price elasticity functions are introduced for each customer in order to jointly decide demand targets and prices. A linear generalized disjunctive programming model is developed. Short execution time shows that this model can be applied to analyze several real scenarios to decide material purchase plan, inventory levels, sales strategies, prices and demand levels in a medium term horizon planning.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin
Characterizing nervousness at the shop-floor level in the context of Industry 4.0
No full textManufacturing systems are shifting from nonflexible to dynamic, self-aware, and self-adaptable ones. Scheduling systems, as the production activities' core, are turning online, with response capabilities. Nevertheless, even when immediate rescheduling actions are performed each time a disruption occurs, aimed at getting a new feasible and/or good quality solution, this adaptation-to-change response mechanism might not be well accepted on the shop floor. Repeated changes could lead to a continuous rearrangement of predefined manufacturing plans through different levels, from MRP to the control system. Traditionally, this behavior is known as schedule nervousness (SN). There are many contributions about nervousness at the planning level, as well as recent advances tackling it at the control level. Yet, further specification of nervousness happening at the shop floor (Shop-Floor Schedule Nervousness, SFSN), where a short-term on-going schedule drives the production, is needed. In this chapter, the SFSN issue is identified, characterized, and a first SFSN framework is proposed.Fil: Rodriguez, Maria Analia. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; ArgentinaFil: Novas, Juan Matias. Universidad Tecnológica Nacional. Facultad Regional Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentin
Multicriteria optimization model for supply process problem under provision and demand uncertainty
Get PDFSupply processes play an important role in customer satisfaction and company costs. The main characteristics of this problem are given by several decisions that follow a hierarchical structure and a very uncertain context, conditioning the success of the solutions proposed. Two significant sources of uncertainty are considered in this work, namely, provision and demand, both modeled as exogenous variables with random behavior. An optimization model is formulated to reduce the effects of the uncertainty in the company supply process. Because of the problem complexity, a multicriteria model is required to bring a comprehensive solution. Several Pareto-optimal solutions are obtained through application of the ε-constraint technique. The original formulation is a nonconvex one that is then transformed to obtain a disjunctive linear model that guarantees a global result.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin
Supply Chain Design and Inventory Management Optimization in the Motors Industry
Get PDFThis article studies the supply chain redesign under demand uncertainty over a multi-period planning. We propose an optimization model to solve the problem taking into account strategic and tactical plans. This model is applied to the electric motors industry but it can be easily extended to other supply chains. Long term decisions involve new installations, expansions and elimination of warehouses. Tactical decisions include deciding inventory levels (safety stock and expected inventory) for each type of product in distribution centers and customer plants, as well as the connection links between the supply chain nodes.
Capacity constraints are also considered when planning inventory levels. At the tactical level it is analyzed how demand of failing motors is satisfied, and whether to use new or used motors. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a
customer plant. In addition, the risk-pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piecewise linearization approach is applied to obtain a tight lower bound of the optimal solution.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Grossmann, Ignacion E.. University Of Carnegie Mellon; Estados UnidosFil: Harjunskonsky, Liro. ABB AG, Corporate Research Germany; Alemani
Generalized disjunctive programming models for the truck loading problem: A case study from the non-alcoholic beverages industry
No full textA real-world truck loading problem is considered for the major non-alcoholic beverages bottler in Argentina. The previous manual procedure to define the truck loading plan is improved by automatizing the process through a set of optimization models applying Generalized Disjunctive Programming. Most of the operational practices and restrictions are taken into account. Given that there is flexibility to load products in the trucks, a better use of their capacities is obtained and the balance of forces addressed avoids expensive penalties fees. By a set of examples, different metrics are tested and good quality results are obtained for an every-day practice.Fil: Novas, Juan Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina. Universidad Tecnológica Nacional. Facultad Regional Córdoba; ArgentinaFil: Ramello, Juan Ignacio. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. ; Argentina. Coca-cola Andina Argentina; ArgentinaFil: Rodriguez, Maria Analia. Universidad Nacional de Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación y Desarrollo en Ingeniería de Procesos y Química Aplicada; Argentin
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