Наредни састанак Семинара биће одржан онлајн у уторак, 12.априла 2022, са почетком у 14.15 часова.

Предавач: Julia Memar, School of Mathematical and Physical Sciences, University of Technology, Sydney

Наслов предавања: LAGRANGIAN RELAXATION AND DECOMPOSITION-BASED ALGORITHMS FOR FLOW SHOPS WITH JOB-DEPENDENT BUFFER REQUIREMENTS

Апстракт: The flow shop problems with storage (a buffer) have been extensively studied in the literature on scheduling, but most of these publications consider flow shops with an intermediate buffer between stages and assume that this buffer limits only the number of jobs that have completed one operation and are waiting for the commencement of the next one. In contrast, in the flow shop models, considered in this talk, the storage requirement varies from job to job and each job seizes the required storage space during its processing on the machines as well as during its waiting time between the operations. This also differentiates these models from the resource-constrained scheduling that assumes that the additional resource is consumed by a job only during its processing on the machines, but it is released between the operations. Although the practical significance of the flow shops with job-dependent storage requirements was acknowledged as early as in 2007, the active research in this field of scheduling theory was triggered by the publications in 2008 and 2013 that were concerned with controlling the lag during a multimedia presentation of media objects, where each object has a loading time and playtime.

Since then, various publications have appeared with results concerning complexity, integer programming formulations, branch and bound algorithms and heuristics for the flow shops with job-dependent storage requirements. In this seminar, I will talk about Lagrangian relaxation and decomposition approach to such models and my results in this area so far: I will present several Lagrangian relaxation and decomposition-based heuristics that are developed for NP-hard flow-shop problems with job-dependent storage and the results of computational experiments.

Напомена: Због тренутне епидемиолошке ситуације, предавања се могу пратити искључиво на даљину преко линка:
https://miteam.mi.sanu.ac.rs/asset/YoqHWKALRkRTbK9So

За активно учешће на Семинару неопходна је регистрација преко линка:
https://miteam.mi.sanu.ac.rs/asset/xzGqvSp7aWbg8WpYX