Mass Vaccine Administration under Supply Uncertainty

The insurgence of COVID-19 requires fast mass vaccination, hampered by scarce availability and uncertain supply of vaccine doses and a tight schedule for boosters. In this paper, we analyze planning strategies for the vaccination campaign to vaccinate as many people as possible while meeting the booster schedule. We compare a conservative strategy and q-days-ahead strategies against the clairvoyant strategy. The conservative strategy achieves the best trade-off between utilization and compliance with the booster schedule. Q-days-ahead strategies with q < 7 provide a larger utilization but run out of stock in over 30% of days

Non-identical parallel machines batch processing problem with release dates, due dates and variable maintenance activity to minimize total tardiness

[EN] Combination of job scheduling and maintenance activity has been widely investigated in the literature. We consider a non-identical parallel machines batch processing (BP) problem with release dates, due dates and variable maintenance activity to minimize total tardiness. An original mixed integer linear programming (MILP) model is formulated to provide an optimal solution. As the problem under investigation is known to be strongly NP-hard, two meta-heuristic approaches based on Simulated Annealing (SA) and Variable Neighborhood Search (VNS) are developed. A constructive heuristic method (H) is proposed to generate initial feasible solutions for the SA and VNS. In order to evaluate the results of the proposed solution approaches, a set of instances were randomly generated. Moreover, we compare the performance of our proposed approaches against four meta heuristic algorithms adopted from the literature. The obtained results indicate that the proposed solution methods have a competitive behaviour and they outperform the other meta-heuristics in most instances. Although in all cases, H + SA is the most performing algorithm compared to the others.Beldar, P.; Moghtader, M.; Giret Boggino, AS.; Ansaripoord, AH. (2022). Non-identical parallel machines batch processing problem with release dates, due dates and variable maintenance activity to minimize total tardiness. Computers & Industrial Engineering. 168:1-28. https://doi.org/10.1016/j.cie.2022.10813512816

Effective Strategies to Improve Project Planning in the Banking Industry

Poor project planning can negatively affect the profitability of information technology (IT) projects. IT project managers in the banking industry who fail to improve project planning can observe a decrease in profitability. Grounded in the structuration theory, the purpose of this qualitative single case study was to explore effective strategies IT project managers use to improve project planning in the banking industry. Participants were four IT project managers in Abidjan-Ivory Coast who successfully used strategies to improve project planning in the banking industry. Data were collected from semistructured interviews and company documents relevant to IT project planning and analyzed using Yin’s five-step process. Five themes emerged: effective communication, effective risk management plan, scope management plan, schedule management plan, and cost management plan. A key recommendation for IT project managers is to use project management information systems and project reporting to share information with the project stakeholders. The implications for positive social change include the potential to sustain financial and economic development in the community through the successful implementation of IT projects

Robust single machine scheduling with a flexible maintenance activity

In this paper, we address a problem arising in a manufacturing environment concerning the joint scheduling of multiple jobs and a maintenance activity on a single machine. Such activity must be processed within a given time window and its non-deterministic duration takes values in a given interval. We seek job schedules which are robust to any possible changes in the maintenance activity duration. We consider makespan and total completion time objectives under four different robustness criteria. We discuss a few properties and the complexity of finding robust schedules for the resulting eight problem scenarios. For the case of total completion time objective and maximum absolute regret criterion, we design and test exact and heuristic algorithms. The results of an extensive computational campaign, performed for assessing the performance of the proposed solution approaches, are reported

Robust single machine scheduling with a flexible maintenance activity

In this paper, we address a problem arising in a manufacturing environment concerning the joint scheduling of multiple jobs and a maintenance activity on a single machine. Such activity must be processed within a given time window and its non-deterministic duration takes values in a given interval.We seek job schedules which are robust to any possible changes in the maintenance activity duration. We consider makespan and total completion time objectives under four different robustness criteria. We discuss a few properties and the complexity of finding robust schedules for the resulting eight problem scenarios.For the case of total completion time objective and maximum absolute regret criterion, we design and test exact and heuristic algorithms. The results of an extensive computational campaign, performed for assessing the performance of the proposed solution approaches, are reported. (C) 2019 Elsevier Ltd. All rights reserved