0360-8352/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.cie.2008.07.022 * Corresponding author. Tel./fax: +86 24 83680169 E-mail addresses: [email protected] (L. Tang In this paper, we consider two new types of the two-machine flowshop scheduling problems where a batching machine is followed by a single machine. The first type is that normal jobs with transportation between machin...

The Online Order Batching Problem with Multiple Pickers (OOBPMP) consists of optimizing the operations related to picking process orders in a warehouse, when policy follows an order batching strategy. In this case, variant well-known considers existence multiple workers warehouse and online arrival orders. We study three different objective functions for problem: minimizing completion time, dif...

Bangladesh is one of the largest exporters of jute which is commonly processed with mineral Jute Batching Oil (JBO). JBO-processed jute products (especially food grade packaging item) have poor acceptability worldwide mainly due to their unpleasant odor, texture and the possible presence of carcinogenic compounds Foreign market has demanded replacement of mineral JBO and it is high time not to ...

Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements the basic Gauss-Newton algorithm tackle convergence guarantees or leverage sparsity underlying problem structure for computational speedup. With success deep learning methods leveraging large datasets, stochastic optimization received recently lot attention. Our work...

this paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. we assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. in this paper, we present an artificial imm...

We develop adaptive replicated designs for Gaussian process metamodels of stochastic experiments. Adaptive batching is a natural extension sequential design heuristics with the benefit replication growing as response features are learned, inputs concentrate, and metamodeling overhead rises. Motivated by problem learning level set mean simulator response, we five novel schemes: Multi-Level Batch...