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Jack G.a.j. Van Der Vorst - One of the best experts on this subject based on the ideXlab platform.

  • modeling a green inventory routing problem for Perishable Products with horizontal collaboration
    Computers & Operations Research, 2018
    Co-Authors: Mehmet Soysal, Rene Haijema, Jacqueline M Bloemhofruwaard, Jack G.a.j. Van Der Vorst
    Abstract:

    Increasing concerns on energy use, emissions and food waste requires advanced models for food logistics management. Our interest in this study is to analyse the benefits of horizontal collaboration related to perishability, energy use (CO2 emissions) from transportation operations and logistics costs in the Inventory Routing Problem (IRP) with multiple suppliers and customers by developing a decision support model that can address these concerns. The proposed model allows us to analyse the benefits of horizontal collaboration in the IRP with respect to several Key Performance Indicators, i.e., emissions, driving time, total cost comprised of routing (fuel and wage cost), inventory and waste cost given an uncertain demand. A case study on the distribution operations of two suppliers, where the first supplier produces figs and the second supplier produces cherries, shows the applicability of the model to a real-life problem. The results show that horizontal collaboration among the suppliers contributes to the decrease of aggregated total cost and emissions in the logistics system. The obtained gains are sensitive to the changes in parameters such as supplier size or maximum product shelf life. According to experiments, the aggregated total cost benefit from cooperation varies in a range of about 424% and the aggregated total emission benefit varies in a range of about 833% compared to the case where horizontal collaboration does not exist. HighlightsA chance-constrained model for the multi-supplier IRP is presented.Model accounts for perishability, explicit fuel consumption and demand uncertainty.Model allows us to analyse the benefits of horizontal collaboration in the IRP.A case study on the distribution operations of two suppliers shows model applicability.Horizontal collaboration contributed to the decrease of total cost and emissions.

  • logistics network design for Perishable Products with heterogeneous quality decay
    European Journal of Operational Research, 2017
    Co-Authors: Marlies De Keizer, Rene Haijema, Renzo Akkerman, Martin Grunow, Jacqueline M Bloemhof, Jack G.a.j. Van Der Vorst
    Abstract:

    The duration of logistics operations, as well as the environmental conditions during these operations, significantly impact the performance of a logistics network for fresh agricultural Products. When durations or temperatures increase, product quality decreases and more effort is required to deliver Products in time and with the right quality. Different network designs lead to different durations and conditions of transport, storage, processing, etc. Therefore, when making network design decisions, consequences for lead time and product quality should be taken into account. As decay of Perishable Products, for instance food, is often not uniform, heterogeneity in product quality decay also has to be considered. The aim of this paper is to show how product quality decay as well as its heterogeneity can be integrated in a network design model. A new mixed integer linear programming formulation is presented, which positions stocks and allocates processes to maximise profit under quality constraints. It is applied to several test instances from the horticultural sector. Results show that different levels of decay lead to different network structures. Changing decay rates due to processing particularly affect the level of postponement. Heterogeneity in product quality causes a split in product flows with high and low product quality. All in all, it is shown that heterogeneous product quality decay should be taken into account in network design as it significantly influences network designs and their profitability, especially when the supply chain includes processes that change the level of decay, and product quality differences can be exploited in serving different markets.

  • hybrid optimization and simulation to design a logistics network for distributing Perishable Products
    Computers & Industrial Engineering, 2015
    Co-Authors: Marlies De Keizer, Rene Haijema, Jacqueline M Bloemhof, Jack G.a.j. Van Der Vorst
    Abstract:

    Network designs can strongly depend on product quality decay.Product quality constraints added to MILP for hub location and process allocation.Simulation of MILP solution determines detailed product quality service levels.Quality service levels are updated in an iterative optimization-simulation approach.Results depend on whether locations or allocations are varied across iterations. Dynamics in product quality complicate the design of logistics networks for Perishable Products, like flowers and other agricultural Products. Complications especially arise when multiple Products from different origins have to come together for processes like bundling. This paper presents a new MILP model and a hybrid optimization-simulation (HOS) approach to identify a cost-optimal network design (i.e. facility location with flow and process allocation) under product quality requirements. The MILP model includes constraints on approximated product quality. A discrete event simulation checks the feasibility of the design that results from the MILP assuming uncertainties in supply, processing and transport. Feedback on product quality from the simulation is used to iteratively update the product quality constraints in the MILP. The HOS approach combines the strengths of strategic optimization via MILP and operational product quality evaluation via simulation. Results, for various network structures and varying degrees of dynamics and uncertainty, show that if quality decay is not taken into account in the optimization, low quality Products are delivered to the final customer, which results in not meeting service levels and excess waste. Furthermore, case results show the effectiveness of the HOS approach, especially when the change from one iteration to the next is in the choice of locations rather than in the number of location. It is shown that the convergence of the HOS approach depends on the gap between the product quality requirements and the quality that can be delivered according to the simulation.

  • modeling an inventory routing problem for Perishable Products with environmental considerations
    International Journal of Production Economics, 2015
    Co-Authors: Mehmet Soysal, Rene Haijema, J M Bloemhof, Jack G.a.j. Van Der Vorst
    Abstract:

    The transition to sustainable food supply chain management has brought new key logistical aims such as reducing food waste and environmental impacts of operations in the supply chain besides the traditional cost minimization objective. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the Inventory Routing Problem (IRP) literature restrict the usage of the proposed models in current food logistics systems. From this point of view, our interest in this study is to enhance the traditional models for the IRP to make them more useful for the decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements and thus offers better support to decision makers.

  • Modeling an Inventory Routing Problem for Perishable Products with environmental considerations and demand uncertainty
    International Journal of Production Economics, 2015
    Co-Authors: Mehmet Soysal, Rene Haijema, Jacqueline M. Bloemhof-ruwaard, Jack G.a.j. Van Der Vorst
    Abstract:

    The transition to sustainable food supply chain management has brought new key logistical aims such as reducing food waste and environmental impacts of operations in the supply chain besides the traditional cost minimization objective. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the Inventory Routing Problem (IRP) literature restrict the usage of the proposed models in current food logistics systems. From this point of view, our interest in this study is to enhance the traditional models for the IRP to make them more useful for the decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements and thus offers better support to decision makers.

Michael Baldea - One of the best experts on this subject based on the ideXlab platform.

  • an efficient optimization framework for tracking multiple quality attributes in supply chains of Perishable Products
    European Journal of Operational Research, 2021
    Co-Authors: Fernando Lejarza, Michael Baldea
    Abstract:

    Abstract Improved supply chain optimization strategies can play a major role in addressing global food security and safety in years to come. In particular, tighter safety regulations, changing consumer quality requirements and more stringent market competition call upon integrated supply chain decision-making frameworks that explicitly consider product quality control. This effort requires metrics of quality that accurately reflect product physico-chemical properties, as well as consumer purchasing preferences. However, a critical challenge linked to embedding the complex dynamics of the evolution of product quality in time within supply chain models is the large-scale nature of the ensuing optimization problems, which are computationally intractable even for moderate-size, single-item systems. In the present work, we introduce a computationally efficient optimal production and distribution planning framework for Perishable Products having multiple quality attributes that evolve in time as a function of environmental conditions during shipment and storage. We also propose a model reduction strategy and a decomposition framework that enhance the scalability of our approach. We perform extensive numerical simulations using different network instances to validate our theoretical findings, as well as to demonstrate the advantages of the proposed supply chain management scheme.

  • closed loop real time supply chain management for Perishable Products
    IFAC-PapersOnLine, 2020
    Co-Authors: Fernando Lejarza, Michael Baldea
    Abstract:

    Abstract Supply chain networks are dynamical systems with particular control challenges that stem from inventory deterioration and external disturbances (i.e., unanticipated consumer demand, time delays, etc.). For industries handling highly Perishable inventory (e.g, fresh produce, vaccines, biologics) controlling product quality throughout the multiple echelons of the supply chain is critical to minimize inventory waste and satisfy consumer quality requirements. However, quality, as a function of time and environmental conditions (i.e., temperature, humidity, light, etc.), is difficult to model accurately resulting in unpredicted inventory spoilage. In this paper we demonstrate a novel closed-loop, feedback-based control framework that employs real-time product quality measurements for optimal supply chain management. A moving horizon approach is used to periodically update decisions (i.e., production, transportation, storage, and respective environmental conditions) based on fed-back information. We demonstrate that the postulated feedback controller effectively stabilizes the supply chain dynamics, while minimizing costs. An illustrative case study is provided.

R Haijema - One of the best experts on this subject based on the ideXlab platform.

  • optimal ordering issuance and disposal policies for inventory management of Perishable Products
    International Journal of Production Economics, 2014
    Co-Authors: R Haijema
    Abstract:

    Abstract Perishables, such as packed fresh food and pharmaceutical Products (a.o. blood Products), typically have a fixed shelf life set by a fixed use-by date or sell-by date. Despite their limited life time, orders in practice are usually based on the stock level irrespective of the ages of the Products in stock. The management of inventories of such Products can be improved by applying stock-age dependent ordering, issuing, and disposal policies. This paper investigates cost reductions that can be achieved by an optimal stock-age dependent ordering, issuing, or disposal policy as obtained by Stochastic Dynamic Programming. Orders are made before the uncertain demand is revealed. When demand turns out to be relatively low, a disposal policy enables to get rid of excess (old) stock. Disposal decisions are an understudied area, but may be relevant to retailers for which displaying the freshest items is of high importance. Also blood banks prefer not to issue Products that are about to expire as transfusion of younger blood Products is more effective. This paper fills a research gap identified in Karaesmen et al. (2011) : the paper appears to be the first to report optimal stock-age dependent disposal decisions, both under a base stock policy and under optimal stock-age dependent ordering. Results of optimal stock-age dependent ordering, disposal, and issuance are compared to a base stock policy, which is commonly used in practice. Under FIFO issuance, the added value of an optimal disposal policy is high. An optimal disposal policy in combination with optimal ordering reduces the average costs only when issuing old Products is penalized, e.g. by selling at a discounted price. Under LIFO issuance, an optimal disposal policy has significant impact when orders are set by a BSP, but not under optimal stock-age dependent ordering. When no penalty or discount applies, disposals reduce costs only in case of suboptimal ordering, e.g. by a BSP.

  • an milp approximation for ordering Perishable Products with non stationary demand and service level constraints
    International Journal of Production Economics, 2014
    Co-Authors: K G J Paulsworm, R Haijema, Eligius M T Hendrix, Jack G.a.j. Van Der Vorst
    Abstract:

    Abstract We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a Perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at lowest cost. Every production run a setup cost is incurred. Moreover, the producer has to deal with unit production cost, unit holding cost and unit cost of waste. The production plan for a finite time horizon specifies in which periods to produce and how much. We formulate this single item—single echelon production planning problem as a stochastic programming model with a chance constraint. We show that an approximate solution can be provided by an MILP model. The generated plan simultaneously specifies the periods to produce and the corresponding order-up-to levels. The order-up-to level for each period is corrected for the expected waste by explicitly considering for every period the expected age-distribution of the Products in stock. The model assumes zero lead time and backlogging of shortages. The viability of the approach is illustrated by numerical experiments. Simulation shows that in 96.4% of the periods the service level requirements are met with an error tolerance of 1%.

Anvar Nigmatullin - One of the best experts on this subject based on the ideXlab platform.

Eligius M T Hendrix - One of the best experts on this subject based on the ideXlab platform.

  • an milp approximation for ordering Perishable Products with non stationary demand and service level constraints
    International Journal of Production Economics, 2014
    Co-Authors: K G J Paulsworm, R Haijema, Eligius M T Hendrix, Jack G.a.j. Van Der Vorst
    Abstract:

    Abstract We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a Perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at lowest cost. Every production run a setup cost is incurred. Moreover, the producer has to deal with unit production cost, unit holding cost and unit cost of waste. The production plan for a finite time horizon specifies in which periods to produce and how much. We formulate this single item—single echelon production planning problem as a stochastic programming model with a chance constraint. We show that an approximate solution can be provided by an MILP model. The generated plan simultaneously specifies the periods to produce and the corresponding order-up-to levels. The order-up-to level for each period is corrected for the expected waste by explicitly considering for every period the expected age-distribution of the Products in stock. The model assumes zero lead time and backlogging of shortages. The viability of the approach is illustrated by numerical experiments. Simulation shows that in 96.4% of the periods the service level requirements are met with an error tolerance of 1%.