50,220 research outputs found
Modelling Fresh Strawberry Supply "From-Farm-to-Fork" as a Complex Adaptive Network
The purpose of this study is to model and thereby enable simulation of the complete business entity of fresh food supply. A case narrative of fresh strawberry supply provides basis for this modelling. Lamming et al. (2000) point to the importance of discerning industry-specific product features (or particularities) regarding managing supply networks when discussing elements in "an initial classification of a supply network" while Fisher (1997) and Christopher et al. (2006, 2009) point to the lack of adopting SCM models to variations in products and market types as an important source of SCM failure. In this study we have chosen to move along a research path towards developing an adapted approach to model end-to-end fresh food supply influenced by a combination of SCM, system dynamics and complex adaptive network thinking...
Abridged Petri Nets
A new graphical framework, Abridged Petri Nets (APNs) is introduced for
bottom-up modeling of complex stochastic systems. APNs are similar to
Stochastic Petri Nets (SPNs) in as much as they both rely on component-based
representation of system state space, in contrast to Markov chains that
explicitly model the states of an entire system. In both frameworks, so-called
tokens (denoted as small circles) represent individual entities comprising the
system; however, SPN graphs contain two distinct types of nodes (called places
and transitions) with transitions serving the purpose of routing tokens among
places. As a result, a pair of place nodes in SPNs can be linked to each other
only via a transient stop, a transition node. In contrast, APN graphs link
place nodes directly by arcs (transitions), similar to state space diagrams for
Markov chains, and separate transition nodes are not needed.
Tokens in APN are distinct and have labels that can assume both discrete
values ("colors") and continuous values ("ages"), both of which can change
during simulation. Component interactions are modeled in APNs using triggers,
which are either inhibitors or enablers (the inhibitors' opposites).
Hierarchical construction of APNs rely on using stacks (layers) of submodels
with automatically matching color policies. As a result, APNs provide at least
the same modeling power as SPNs, but, as demonstrated by means of several
examples, the resulting models are often more compact and transparent,
therefore facilitating more efficient performance evaluation of complex
systems.Comment: 17 figure
Coordination and synchronization of material flows in supply chains: an analytical approach.
The coordination of joint material flows is a key element in supply chain management. Although analytical models for the coordination of materials are of great practical value, literature analyzing them remains scarce. This article contributes to this gap by studying a generic supply chain model. The supply chain is assumed to have a single production facility that is supplied by two independent suppliers. The field of combinatorics serves as a means to derive exact results for important performance measures, and the results suggest insights related to several supply chain management principles.Assembly; Synchronization; Coordination; Supply chain; Combinatorics;
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A survey of simulation techniques in commerce and defence
Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches
Numerical schemes for the optimal input flow of a supply-chain
An innovative numerical technique is presented to adjust the inflow to a
supply chain in order to achieve a desired outflow, reducing the costs of
inventory, or the goods timing in warehouses. The supply chain is modelled by a
conservation law for the density of processed parts coupled to an ODE for the
queue buffer occupancy. The control problem is stated as the minimization of a
cost functional J measuring the queue size and the quadratic difference between
the outflow and the expected one. The main novelty is the extensive use of
generalized tangent vectors to a piecewise constant control, which represent
time shifts of discontinuity points. Such method allows convergence results and
error estimates for an Upwind- Euler steepest descent algorithm, which is also
tested by numerical simulations
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