Dynamic reorder point replenishment strategies for a capacitated supply chain with seasonal demand

Managing inventory and service levels in a capacitated supply chain environment with seasonal demand requires appropriate selection and readjustment of replenishment decision variables. This study focuses on the dynamic adjustment of decision variables within supply chains using continuous-review reorder point (ROP) replenishment. A framework is proposed to adjust reorder points and lot sizes based on optimal settings within different regions of a seasonal demand cycle. This framework also includes the optimal timing of adjustments defining these regions. A discrete-event simulation model of a simple, capacity-constrained supply chain is developed and simulation–optimization experiments are performed, the objective being to minimize the total supply chain inventory subject to a target delivery service level. The performance of ROP systems with optimal static and optimal dynamic decision variable settings are compared using two different seasonal demand patterns. The results confirm that performance with dynamic decision variable adjustment is better. For a given delivery service level, average work-in-process inventory levels are almost the same for both systems. However average finished goods inventory levels decrease significantly and are more stable under dynamic adjustment. The practical implication is that both finished goods holding costs and maximum storage capacity requirements are reduced.     

Hierarchical supply chain planning using artificial neural networks to anticipate base-level outcomes

Most Advanced Planning Systems decompose the task of production planning according to the planning horizon in two levels, mid-term and short-term planning. The mid-term planning level sets the targets for the short-term level. In response, the short-term planning level gives feedback to the mid-term level. Moreover, due to detailed knowledge, the short-term planning level should provide relevant input to the mid-term planning run. To compute accurate targets for the short-term planning level the mid-term planning should anticipate its major behaviour. In this article we present an artificial neural network based anticipation of a short-term planning level for a single-stage, multi-product flow line production environment.     

Optimal consumption and portfolio choice with ambiguity and anticipation

This paper, adopting the recursive multiple-priors utility, studies the optimal consumption and portfolio choice in a Merton-style model with anticipation when there is a difference between ambiguity and risk. The fundamental issue is what the effects of ambiguity and anticipation on the investor’s behavior are. In the case of a logarithmic felicity function, the paper also shows that no hedging demand arises that is affected by both ambiguity and anticipation. Finally, the optimal portfolio is derived in terms of Malliavin derivatives and stochastic integrals.     

Older drivers' insight into their hazard perception ability

Even though the driving ability of older adults may decline with age, there is evidence that some individuals attempt to compensate for these declines using strategies such as restricting their driving exposure. Such compensatory mechanisms rely on drivers’ ability to evaluate their own driving performance. This paper focuses on one key aspect of driver ability that is associated with crash risk and has been found to decline with age: hazard perception. Three hundred and seven drivers, aged 65–96, completed a validated video-based hazard perception test. There was no significant relationship between hazard perception test response latencies and drivers’ ratings of their hazard perception test performance, suggesting that their ability to assess their own test performance was poor. Also, age-related declines in hazard perception latency were not reflected in drivers’ self-ratings. Nonetheless, ratings of test performance were associated with self-reported regulation of driving, as was self-rated driving ability. These findings are consistent with the proposal that, whileself-assessments of driving ability may be used by drivers to determine the degree to which they restrict their driving, the problem is that drivershave little insight into their own driving ability. This may impact on the potential road safety benefits of self-restriction of driving because drivers may not have the information needed to optimally self-restrict. Strategies for addressing this problem are discussed.     

Anticipation: learning from the past. The Russian/Soviet contributions to the science of anticipation

The focus on Russian/Soviet contributions is only an opportunity to understand the objective premises of anticipation. Since anticipation expresses a main concept characterizing human action, it is important to see whether and how it corresponds to the neuro-physiology of the human. The aim of this review is to show that anticipation is neuro-physiologically constitutive and is intertwined with all other reflective, cognitive, and coordinative functions that form an inseparable unity in the process of adaptation. The experiments described in the book draw attention to anticipation as the internal tendency of the living that cannot be ignored. The review highlights the dialectic of continuity and discontinuity in the living from the standpoint of anticipation, and the holistic conclusions of the scientific research regarding the living and the human being.     

基于实时拓扑图的发射台站网络监控管理系统

只要存在网络就必然会进行网络拓扑的管理,就一个短波发射台而言,网络设备的种类和类型繁多,路由器、交换机、服务器和防火墙等等.如果某个网络设备出了问题,有可能会导致整个网络都不能正常访问,通过实现网络拓扑图与实时状态关联,不仅将这个网络拓扑图展现出来后,同时也将各网络节点的运行状态实时展现,从而达到网络运行监控的可视性和预判性对网络运行全面监控.在设备或应用发生问题时,主动进行规划、防御和告警.     

Temporal awareness: pivotal in performance?

This paper describes an experiment where operators have to deal with various parallel asynchronous processes. The authors were interested in the level of ‘temporal awareness’ developed by the operator. By temporal awareness, one means the ability of the operator to build a representation of the situation including the recent past and the near future. The hypothesis was that this ability is linked to other elements of performance. The authors also looked at the effects of an aid aimed at supporting the construction of temporal representation. The experiment showed that this support system was largely ineffective, but that the presence of temporal awareness proves to be a good indicator of performance, both in terms of errors committed and multiple-goal optimization.     

Anticipation based on constraint processing in a multi-agent context

Anticipation is a general concept used and applied in various domains. Many studies in the field of artificial intelligence have investigated the capacity for anticipation. In this article, we focus on the use of anticipation in multi-agent coordination, particularly preventive anticipation which consists of anticipating undesirable future situations in order to avoid them. We propose to use constraint processing to formalize preventive anticipation in the context of multi-agent coordination. The resulting algorithm allows any action that may induce an undesirable future state to be detected upstream of any multi-agent coordination process. Our proposed method is instantiated in a road traffic simulation tool. For the specific question of simulating traffic at road junctions, our results show that taking anticipation into account allows globally realistic behaviors to be reproduced without provoking gridlock between the simulated vehicles.     

Modeling and optimizing of strategic and tactical production planning in the automotive industry under uncertainty

This work considers the strategic flexibility and capacity planning under uncertain demands in production networks of automobile manufacturers. We present a deterministic and a stochastic model, which extend existing approaches, especially by an anticipation scheme for tactical workforce planning. This scheme is compared to an extended formulation of the deterministic model, which incorporates workforce planning via detailed shift models. The stochastic model is efficiently solved by an accelerated decomposition approach. The solution approach is integrated into a decision support system, which calculates minimum-cost product allocations and capacity plans. Our numerical results show that, in spite of the considerably increased complexity, our approach can efficiently handle hundreds of scenarios. Finally, we present an industrial case study.     

Effect of driving experience on anticipatory look-ahead fixations in real curve driving

Anticipatory skills are a potential factor for novice drivers’ curve accidents. Behavioural data show that steering and speed regulation are affected by forward planning of the trajectory. When approaching a curve, the relevant visual information for online steering control and for planning is located at different eccentricities, creating a need to disengage the gaze from the guidance of steering to anticipatory look-ahead fixations over curves. With experience, peripheral vision can be increasingly used in the visual guidance of steering. This could leave experienced drivers more gaze time to invest on look-ahead fixations over curves, facilitating the trajectory planning.