R. Haijema

Blood platelet production: a novel approach for practical optimization

BACKGROUND: The challenge of production and inventory management for blood platelets (PLTs) is the requirement to meet highly uncertain demands. Shortages are to be minimized, if not to be avoided at all. Overproduction, in turn, leads to high levels of outdating as PLTs have a limited “shelf life.” Outdating is to be minimized for ethical and cost reasons.

Modeling a green inventory routing problem for perishable products with horizontal collaboration

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.

Hybrid optimization and simulation to design a logistics network for distributing perishable products

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.

Logistics network design for perishable products with heterogeneous quality decay

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.

Traffic Responsive Control of Intersections with Predicted Arrival Times: A Markovian Approach

The dynamic adaptive control of traffic lights can be formulated as a Markov decision problem (MDP). This framework is hardly used, as solving an MDP can be very time-consuming and is only possible for simple infrastructures with a small number of traffic flows. Nevertheless, we show that the MDP framework can be used to construct control policies that approximately minimize the long-run average waiting time at intersections. The MDP-based approach is fast and thus allows real-time use of actual information on traffic conditions, like queue lengths and the arrival times of near-future arrivals. Simulation of an isolated intersection as well as a small network shows that the new policies with arrival information improve pretimed as well as exhaustive control. The new control policies and underlying algorithms scale up well to control networks.

Using vulnerability performance indicators to attain food supply chain robustness

High effectiveness and leanness of modern supply chains (SCs) increase their vulnerability, i.e. susceptibility to disturbances reflected in non-robust SC performances. Both the SC management literature and SC professionals indicate the need for the development of SC vulnerability assessment tools. In this article, a new method for vulnerability assessment, the VULA method, is presented. The VULA method helps to identify how much a company would underperform on a specific Key Performance Indicator in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision about whether process redesign is appropriate and what kind of redesign strategies should be used in order to increase the SCs robustness. The applicability of the VULA method is demonstrated in the context of a meat SC using discrete-event simulation to conduct the performance analysis.

Optimal issuing of perishables with a short fixed shelf life

The management of inventories of perishable products with a short maximal shelf life takes a good issuing policy next to a good ordering policy. Ordering policies of non-perishables are well studied in literature and implemented in Automated Store Ordering (ASO) systems and Computer Assisted Ordering (CAO) systems. These ordering policies are stock-level dependent and do not take the product ages into account. As a consequence when applied to perishable products they do not anticipate expected future outdating of products and thus result in unnecessary outdating and shortages. Improved ordering policies are proposed in the literature but hardly implemented in ASO and CAO systems as these are designed for the management of non-perishables. Without changing the order policies of such systems one may reduce outdating and shortages by issuing the products in a sophisticated way. We present therefore a stochastic model that is solved by stochastic dynamic programming.

On solving a stochastic programming model for perishable inventory control

This paper describes and analyses a Stochastic Programming (SP) model that is used for a specific inventory control problem for a perishable product. The decision maker is confronted with a non-stationary random demand for a fixed shelf life product and wants to make an ordering plan for a finite horizon that satisfies a service level constraint. In literature several approaches have been described to generate approximate solutions. The question dealt with here is whether exact approaches can be developed that generate solutions up to a guaranteed accuracy. Specifically, we look into the implications of a Stochastic Dynamic Programming (SDP) approach.

On Computing Order Quantities for Perishable Inventory Control with Non-stationary Demand

The determination of order quantities in an inventory control problem of perishable products with non-stationary demand can be formulated as a Mixed Integer Nonlinear Programming problem (MINLP). One challenge is to deal with the \(\beta \)-service level constraint in terms of the loss function. This paper studies the properties of the optimal solution and derives specific algorithms to determine optimal quantities.

Floricultural Supply Chain Network Design and Control: Developments and Research Challenges

The floricultural sector is facing market developments that have forced a redesign of the European logistics network. Via workshops and interviews with key stakeholders the main developments and industry needs are identified. These are then summarised in three central themes that require further investigation, i.e. decision problems (e.g. network design and control), context factors (e.g. demand uncertainty and product perishability), and objectives (e.g. efficiency and product quality). Thereafter, 17 articles that review Supply Chain Management (SCM) research are analysed to obtain more insight into the state-of-the-art on these themes and to identify the main issues within the themes and their interrelationships. This resulted in a conceptual research framework in which particular attention is given to how decision problems could be modelled and solved in order to get quantitative insights into the impact of logistics network redesign. Successively, 71 SCM articles were analysed in depth to classify current SCM research and to determine research gaps and challenges. Results show that Floricultural SCM research challenges can be found in integrated, quality-driven and responsive network design and control using hybrid optimisation and simulation.