Mariana Evangelina Coccola

Toward integrated production and distribution management in multi-echelon supply chains

Abstract The effective management of multi-site systems involves the proper coordination of activities performed in multiple factories, distribution centers (DCs), retailers and end-users located in many different cities, countries and/or continents. To optimally manage numerous production and transportation decisions, a novel monolithic continuous-time MILP-based framework is developed to determine the best short-term operational planning to meet all customer requests at minimum total cost. The formulation lies on the unit-specific general precedence concept for the production scheduling problem whereas the immediate precedence notion is used for transportation decisions. To illustrate the applicability and potential benefits of the model, a challenging example corresponding to a supply chain comprising several locations geographically spread in six European countries has been solved to optimality with modest CPU times. Several scenarios with different logistics features were addressed in order to remark the significant advantages of using the integrated approach.

A branch-and-price approach to evaluate the role of cross-docking operations in consolidated supply chains

Abstract Supply-chain management and optimization aims at reducing costs and inventories. One way to increase the supply-chain efficiency is to use cross-docking for consolidating shipments from different suppliers. Cross-docking is a warehousing strategy used in logistics that consists on moving goods from suppliers to customers through a cross-dock facility. The employment of this strategy must be carefully evaluated because sometimes transportation requests can be better directly moved from source-sites to destination. A realistic problem studying the convenience of direct delivery, avoiding some cross-docking transfers, is here discussed. An efficient methodology for finding (near)optimal solutions is also described. The methodology is based on the use of column generation embedded into an incomplete branch-and-price tree. The approach provides (near)optimal solutions by solving the column generation sub-problems without necessarily considering all unexplored nodes in the search-tree. Finally, we show computational results on numerous test problems and on four configurations of the addressed case study.

A MILP-based column generation strategy for managing large-scale maritime distribution problems

Abstract This paper presents a novel column generation algorithm for managing the logistics activities performed by a fleet of multi-parcel chemical tankers. In our procedure, for providing elementary routes, the conventional dynamic programming routes-generator is replaced by an efficient continuous-time MILP-slave problem. The performance of the decomposition method is evaluated by solving several examples dealing with the operations of a shipping company operating in the Asia Pacific Region. Computational results show that the proposed approach outperforms a pure exact optimization model and an alternative heuristic solution method reported in the literature.

Integrated production and distribution management with cross docking in supply chains

Abstract In the current context of a global and very competitive economy, multiple production and distribution activities must be properly coordinated in order to satisfy strict market requirements at the right time and with minimum cost. In typical multi-site systems, products are usually manufactured in one or more factories, moved to warehouses for intermediate storage, and subsequently shipped to retailers or final consumers. In turn, cross-docking platforms may be also used to consolidate multi-product customer demands without storing at intermediate depots. Consequently, the effective operation of complex production and distribution networks involves the management of activities performed in multiple factories, distribution centers (DCs), retailers and end users, which are usually geographical spread in many different cities, countries and/or continents. To optimally manage such complex multi-site systems, an integrated MILP-based framework for production and distribution scheduling with cross-docking in supply chains is proposed. In order to illustrate the applicability and effectiveness of the proposed method, a complex example taken from literature is solved to optimality with modest CPU times.

A robust MILP-based approach to vehicle routing problems with uncertain demands

Abstract The Vehicle Routing Problem with Stochastic Demands (VRPSD) has attracted the attention of the research community over the last decades by introducing the random behavior of the demand into the traditional routing problem. Many related works were focusing on providing suitable approaches of this large combinatorial problem for many different cases of uncertainly demand. Moreover, exact approaches that were developed up to now provide reliable results for specific demand values, e.g. using the highest demand value or the most expected value, but these solutions do not consider the concurrent effect of many possible scenarios into the objective function. So, the real necessity of more efficient and reliable approaches for this problem that provides optimal solutions for small and medium size cases in a reasonable time and also that response consistently to the random behavior of the demand has been clearly appeared in the last years ( Novoa and Storer, 2009 ). In this work a robust MILP-based formulation for the VRPSD problem is developed. The main goal of this method is to find a reliable solution that provides an optimal result considering the occurrence of many possible scenarios in simultaneous.

A decomposition framework for managing inventory and distribution of fluid products by an order-based-resupply methodology

Abstract Fluid chemicals are usually distributed according two main methodologies; the vendor managed inventory modality and the order-based re-supply modality. In this paper, the problem of optimizing the delivery of fluids by tanker trucks on a daily basis according the order-basedresupply methodology is addressed. According to this modality, replenishment orders are triggered by customers specifying the quantity of fluids and time-windows within which the delivery must be fulfilled. The objective is to minimize the replenishment cost while meeting customers orders over the pre-defined time-horizon. An Integer Program modelling the problem is proposed and used to develop an incomplete branch & price procedure with the purpose of finding near optimal solutions to instances arising from realistic examples. A computational study on realistic examples with different topologies demonstrates that the method is effective and able to provide solutions with integrality gaps below the 16% threshold for instances with 120 orders.

Optimizing the design and operation of a beer packaging line through an advanced simio-based des tool

Discrete event simulation (DES) techniques cover a broad collection of methods and applications that allows imitating, assessing, predicting and enhancing the behavior of large and complex real-world processes. This work introduces a modern DES framework, developed with SIMIO simulation software, to optimize both the design and operation of a complex beer packaging system. The proposed simulation model provides a 3D user-friendly graphical interface which allows evaluating the dynamic operation of the system over time. In turn, the simulation model has been used to perform a comprehensive sensitive analysis over the main process variables. In this way, several alternative scenarios have been assessed in order to achieve remarkable performance improvements. Alternative heuristics and optimization by simulation can be easily embedded into the proposed simulation environment. Numerical results generated by the DES model clearly show that production and efficiency can be significantly enhanced when the packaging line is properly set up.

Knowledge-based Approach for the Integration of the Planning and Scheduling Decision-making Levels

This work aims to integrate the tactical and operational decision making levels. A typical Scheduling mixed integer linear programming (MILP) model has been solved using several demand scenarios. The results have been analyzed and accordingly the operation cost vs. production levels nonlinear equations have been obtained. The aforementioned equations have been included as constraints of the SC planning problem. Hence, production, inventory and distribution variables along the complete SC have been optimized using a NLP model.

Towards Integrated Production and Distribution Management

Abstract In the current context of a global and very competitive economy, multiple production and distribution activities must be properly coordinated in order to satisfy strict market requirements at the minimum cost. In multi-site systems, products are usually manufactured in one or more factories, moved to warehouses for intermediate storage, and subsequently shipped to retailers or final consumers. Consequently, the effective operation of complex production and distribution networks involves the management of activities performed in multiple factories, distribution centers (DCs), retailers and end users, which are usually geographical distributed in many different cities, countries and/or continents. This paper introduces a novel optimization approach to the integrated operational planning of multi-echelon multiproduct production and transportation networks.

Optimizing the inventorying and distribution of chemical fluids: An innovative nested column generation approach.

Abstract Vendor-managed-inventory is a successful business practices based on the cooperation between a supplier and its customers in which demand and inventory information from the customers are shared with the supplier. This practice is gaining popularity in the chemical industry and relies on the inventory-routing-problem, which integrates inventory management, vehicle routing, and delivery scheduling decisions. This one is a difficult combinatorial optimization problem both theoretically and practically. However, because of the large expenses involved in distribution and inventorying of chemical products, it is attractive to make use of optimization tools for exploiting as many degrees of freedom as possible with the goal of minimizing both distribution and inventorying costs. Consequently, we propose a nested column generation algorithm for solving an inventorying and distribution problem that models the delivery of several chemicals fluids. The approach is building on a column generation & incomplete branch-and-price algorithm in which for each delivery route, the delivery patterns of fluids are also determined by column generation. We detail the implementation and provide computational results for realistic test instances.