Manuel D. Rossetti

Multiple‐buyer procurement auctions framework for humanitarian supply chain management

Purpose – The purpose of this paper is to address the inefficiency in resource allocation for disaster relief procurement operations. It presents a holistic and reconfigurable procurement auctions‐based framework which includes the announcement construction, bid construction and bid evaluation phases.Design/methodology/approach – The holistic framework is developed in a way that auctioneers and bidders compete amongst each other in multiple rounds of the procurement auction. Humanitarian organization in disaster locations are considered as auctioneers (buyers) and suppliers are considered as bidders.Findings – Unique system parameters (e.g. announcement options, priority of items, bidder strategies, etc.) are introduced to represent the disaster relief environment in a practical way. The framework is verified by simulation and optimization techniques using the system characteristics of the disaster relief environment as an input. Based on the parameters and their values, behavioural changes of auctioneers...

The vehicle scheduling problem with intermittent customer demands

Abstract The vehicle scheduling problem (VSP) is a problem of interest to many researchers and practitioners. The general VSP is concerned with minimizing the total distance associated with a fixed set of vehicle routes by determining which vehicles will satisfy the demands at various customer locations. The design of most general distribution systems usually involves the assignment of permanent customer routes even though customer demand patterns are often stochastic in nature. The traditional routing designs implicitly assume that each customer will be visited each period for each route. In reality, a certain number of customers may not require a delivery for a particular period. In this research, we consider three alternative approaches for modelling the VSP with uncertain customer demands. Our solution methodology is a simple but practical heuristic which captures the best of all three approaches in order to handle the dynamic nature of vehicle scheduling under uncertain demand. An experimental design was also implemented to show the sensitivity of the proposed solution methodology to various realistic scheduling situations.

Multi-objective analysis of hospital delivery systems

Automation introduction in hospital applications has become increasingly important in recent years. Delivery, transportation and distribution services are examples of critical operations that can be automated. This paper examines clinical laboratory and pharmacy deliveries in middle to large size hospitals, in order to evaluate whether or not a fleet of mobile robots can replace a traditional human-based delivery system. The complexity of the problem derives from its multi-objective character, since several, often contrasting factors must be taken under consideration. The problem has common characteristics with transportation system design and automation introduction evaluation in manufacturing. The Analytic Hierarchy Process was used to build a decision problem that synthesized economic and technical performance as well as social, human and environmental factors. The technical performance measures were assessed through computer simulation. This research provides a methodology to approach automation introduction evaluation in a hospital environment. The final results enable a better understanding of the delivery and transportation requirements of middle to large size hospitals and how a fleet of mobile robots can meet these requirements. We applied our methodology to the University of Virginia Health Science Center. We show with a high overall confidence that a fleet of mobile robots can achieve better final results than a human-based transportation system according to a representative preference structure formulated by a hospital manager. An ANOVA analysis indicates that the final results were not excessively dependent on the input data of the simulation model. In addition, a sensitivity analysis indicated that the results are stable with respect to variations in the decision makers preference structure.

A robustness study of a multi-echelon inventory model via simulation

Abstract This paper examines the robustness of a standard model of multi-echelon inventory systems, specifically the models discussed in Axsater (Oper. Res. 48(5) (2000) 686). A simulation model was developed to explore the models ability to predict system performance for a two-echelon one-warehouse, multiple retailer system using (R,Q) inventory policies under conditions that violate the models fundamental modeling assumptions. In particular, the impact of non-stationary demand on this stationary demand inventory model was examined. The model performs well at the low demand and large retailer order batch size situations, but our testing of the model indicated that care must be taken when applying this model to situations that violate its fundamental assumption. These results should help practitioners to better understand the assumptions of these models and to determine when or when not to apply these models in practice.

The use of multi‐attribute utility theory to determine the overall best‐in‐class performer in a benchmarking study

Purpose – To investigate the application of multi‐attribute utility theory (MAUT) to aid in the decision‐making process when performing benchmarking gap analysis.Design/methodology/approach – MAUT is selected to identify the overall best‐in‐class (BIC) performer for performance metrics involving inventory record accuracy within a public sector warehouse. A traditional benchmarking analysis is conducted on 14 industry warehouse participants to determine industry best practices for the four critical warehouse metrics of picking and inventory accuracy, storage speed, and order cycle time. Inventory and picking tolerances are also investigated in the study. A gap analysis is performed on the critical metrics and the absolute BIC is used to measure performance gaps for each metric. The gap analysis results are then compared to the MAUT utility values, and a sensitivity analysis is performed to compare the two methods.Findings – The results indicate that an approach based on MAUT is advantageous in its ability ...

Comparing static and dynamic threshold based control strategies

This research extends a static threshold based control strategy used to control headway variation to a dynamic threshold based control strategy. In the static strategy, buses are controlled by setting a threshold value that holds buses at a control point for a certain amount of time before allowing the bus to continue along the route. The threshold remains constant each time the bus stops at the control point. The dynamic strategy involves the same principle of holding buses at a bus stop; however, a different threshold value is chosen each time the bus holds at a control point. The results indicate that in cases where the static threshold is set equal to the scheduled headway, very low headway variation and passenger system times result; however, passengers on board the bus are penalized by extra delay on the bus while waiting at the control point. The dynamic strategy reduces the penalty to passengers delayed on-board the bus at a control point at the expense of a slight increase in overall passenger system time.The results indicate that in most cases, the tradeoff of the slight increase in waiting time for the significant decrease in on-board delay penalty makes the dynamic strategy an acceptable choice.

Robotic automation of coagulation analysis

Laboratory automation systems (LAS) have been installed in over 22 sites across North America providing automation of many preanalytical and analytical tasks in clinical laboratories. Only a few laboratories have automated the analysis of citrated whole blood for the diagnosis of hemostasis disorders. The analysis of coagulation factors in citrated blood requires a large amount of labor in order to provide rapid turnaround; thus automation of this analytical process is attractive. Therefore, we have created an automated coagulation workstation using a systematic approach to automation design and engineering. First, we used discrete event simulation to calculate potential throughput and to identify possible bottlenecks for the proposed coagulation workcell. We then created a three-dimensional animated computer model of the workstation to simplify workstation design. Finally, we constructed a prototype workcell using a mobile robot, an articulated robotic arm, and a coagulation analytical system.

Evaluation of segmentation techniques for inventory management in large scale multi-item inventory systems

This paper evaluates methodologies for the grouping of items and the setting of inventory policies in a large-scale multi-item inventory system. Conventional inventory segmentation techniques such as ABC analysis are often limited to using demand and cost when segmenting the inventory into groups for easier management. Two segmentation methodologies, (Multi-Item Group Policies (MIGP) and Grouped Multi-Item Individual Policies (GMIIP), that use statistical clustering were developed and compared to ABC analysis. An evaluation of these techniques via a set of experiments was performed. The analysis indicates that these techniques can improve inventory management for large-scale systems when compared to ABC analysis.

A multi-objective integrated facility location-hardening model: Analyzing the pre- and post-disruption tradeoff

Two methods of reducing the risk of disruptions to distribution systems are (1) strategically locating facilities to mitigate against disruptions and (2) hardening facilities. These two activities have been treated separately in most of the academic literature. This article integrates facility location and facility hardening decisions by studying the minimax facility location and hardening problem (MFLHP), which seeks to minimize the maximum distance from a demand point to its closest located facility after facility disruptions. The formulation assumes that the decision maker is risk averse and thus interested in mitigating against the facility disruption scenario with the largest consequence, an objective that is appropriate for modeling facility interdiction. By taking advantage of the MFLHP’s structure, a natural three-stage formulation is reformulated as a single-stage mixed-integer program (MIP). Rather than solving the MIP directly, the MFLHP can be decomposed into sub-problems and solved using a binary search algorithm. This binary search algorithm is the basis for a multi-objective algorithm, which computes the Pareto-efficient set for the pre- and post-disruption maximum distance. The multi-objective algorithm is illustrated in a numerical example, and experimental results are presented that analyze the tradeoff between objectives.

Quantifying the Effect of Transportation Practices in Military Supply Chains

Traditional multi-echelon inventory and readiness-based models have not fully examined the ability of effective transportation utilization to reduce cost, delay times, and improve readiness in the overall military logistics network. In this paper, we develop a simulation-based methodology for quantifying the effect of transportation options (i.e., truckload shipping, less-than-truckload shipping, transshipments, and express air shipping) on shipping costs, customer wait times, abort rates, and operational availability. Simulation was used to develop a multi-echelon (depots, bases) model of regional supply chain support for aircraft spare part maintenance activities. The resulting model was used for experimentation and to develop response surface equations for the behavior of the system. The logistics implications of the results are discussed as well as managerial insights into the behavior of such systems. Our analysis indicates that focusing more on local inventory and local repair can have a significant impact on the operational availability of the system. This shift should be looked at in terms of the cost of local repair resources compared to transportation costs.