Analysis of an inventory system with emergency ordering option at the time of supply disruption

This paper studies a continuous-review stochastic inventory problem for a firm facing random demand and random supply disruptions. The supplier experiences operational (on) and disrupted (off) periods with exponentially distributed durations. The firm adopts an order-up-to level policy during the on period and additionally can release an emergency order based on the inventory level just before disruption. This inventory policy is described by a continuous-time Markov chain model. We analyze the model for two different lead time scenarios and suggest solution approaches yielding the optimal policy parameters. In a numerical study, we explore the value of exercising such a policy and show that an emergency ordering opportunity at the disruption time brings substantial cost savings in cases with high lost sales cost, long off period, and low percentage of supplier’s availability.

Leadership Disruption: Time to Reimagine Leadership Talent

Rapid changes in the global orbit, whether these are demographics, politics, pandemics or even technology shifts, all have considerable implications for leaders. The current world context is disrupting leadership practices because they are no longer meeting the needs of organizations and are forcing the reimagining of the talent needed to lead in this volatile era. The purpose of this article is to first identify the major drivers of the disruption. Secondly, to examine leadership through Humanocracy termed by Hamel and Zanini [1]. Third, there is a conversation around being able to adapt to the speed of change through a process of hyper-learning, that transitions to hyper-leading [2, 3]. Finally, as all great writing connects to theories, this article will include IQ, EQ, CQ, and LQ and their relevancy to leading through disruption.

TEACHER’S LEADERSHIP COMPETENCY IN MANAGING ONLINE INSTRUCTION DURING THE PANDEMIC DISRUPTION IN INDONESIA

Since COVID-19 shocked the world, all business activities experienced an enormous impact, including in the field of education. UNESCO advised the world to ease the pandemic's impact on world education continuity with distance learning policies to overcome this disruption. Since then, pandemic affected countries experienced difficulties implementing that distance learning to respond to the policy. In this regard, this paper was carried out to identify additional instructional leadership competencies for teachers in managing learning in a pandemic. Evidence from the study of education shows that learning in disruption time is closely related to teachers' management in innovating such high technological virtual learning. To find answers, we conducted preliminary readings of the relevant literature. Next, we analyzed that information qualitatively by exploring what teacher instruction management is applicable during the pandemic. Then, we found that additional teaching leadership competencies can be adopted to support students learning in virtual approaches such as reflective opportunities, increasing truth among teachers and students, keeping curiosity habits, building productive communication, initiative habit, and more listening to understand others. Those additional teaching leadership competencies are useful to any party interested in supporting students learning in the pandemic disruption.

Study of event-driven and periodic rescheduling on a single machine with unexpected disruptions

This paper studies the rescheduling problem of a single machine facing unexpected disruptions in order to determine which parameters can help reducing the negative impacts of these disruptions on schedule performance. A Genetic Algorithm (GA) is used to generate the initial schedule and the updated ones according to a reactive strategy. The performance of event-driven rescheduling and periodic rescheduling policies are compared in terms of total tardiness and total cost of rescheduling. Other factors that may affect rescheduling such as disruption time, disruption duration and number of disruptions are investigated. The sensitivity of results to both due date tightness and cost factor variation is tested. The results showed that the timing of the occurrence of disruption as related to scheduling horizon has a major effect on determining the best rescheduling policy. Event-driven policy is superior to other policies for short infrequent disruptions. It was found that the periodic policy is more appropriate for long and frequent disruptions.

Optimal Order Policies for Dual-Sourcing Supply Chains under Random Supply Disruption

In this paper, we investigate inventory and order strategies of a two-echelon supply chain, which is composed of two unreliable suppliers that are subject to random disruption. We develop the gross weighted profit benchmark model and the service level constrained model of the supply chain, respectively. We derive the retailer’s optimal order quantity and analyze the retailer’ optimal order policy and also obtain the analytical closed-form solutions. In addition, some numerical examples are provided to illustrate the effect of disruption time, disruption probability and fill rate on the optimal decisions and expected profit.

Power Cable with Two Joints Experimental Analysis for Defect Assessments

<span>Time domain reflectometry (TDR) is an easy technique that provides quick response which is ideal for power utility companies to conduct cable diagnostics on-site. Electricity disruption due to power cable failure is a major challenge for power utility companies due to the long length of cable installed with joints. The long time taken to diagnose the defect along the cable before electricity can be restored has not only jeopardized the reputation of power utility companies but also brings losses to the economy. Hence, this study conducts experimental analysis on cable with two joints with the application of TDR technique to reduce the electricity disruption time. This research is divided into two stages where stage 1 conducts experiments on cable with one degraded section while stage 2 looks into cable with two degraded sections. The TDR reflection characteristics are studied from stage 1 experiments and applied to stage 2 experiments to verify the consistency of the TDR reflection characteristics. The cable conditions of stage 2 experiments are predicted using the reflection characteristics from stage 1 observations and are then validated by comparing these predictions with the actual cable configuration. Results obtained from these experiments have proven that the TDR reflection characteristics are consistent and accurate which can be used to sectionalize the degraded cable section. Detail findings of all experiments conducted with the TDR application are discussed in part three of this paper.</span>