Bidding for Customer Orders in TAC SCM

2006 ◽  
pp. 143-157 ◽  
Author(s):  
David Pardoe ◽  
Peter Stone
Keyword(s):  
Customer Orders

The Impact of Committing to Customer Orders in Online Retail

2020 ◽  
Author(s):  
Gonçalo Figueira ◽  
Willem van Jaarsveld ◽  
Pedro Amorim ◽  
Jan C. Fransoo
Keyword(s):  
Online Retail ◽  
The Impact ◽  
Customer Orders

A Decision-Making Framework for Inventory Positioning in an Omnichannel Business Environment

2019 ◽  
Vol 12 (1) ◽  
pp. 81-94 ◽  
Author(s):  
Albert Wee Kwan Tan ◽  
David Gligor
Keyword(s):  
Decision Making ◽  
Business Model ◽  
Business Environment ◽  
Shopping Experience ◽  
Decision Making Framework ◽  
Customer Orders

Omnichannel is an evolving business model that has been gaining increased popularity among retailers. This business model allows firms to use a variety of channels to interact with their customers and fulfill their orders. Customers can order online and pick up later in the store, or they can choose to have the products delivered from a nearby store. Due to the complexity of fulfilling customer orders via omnichannel models, positioning inventory is a key challenge in supporting this type of business model. This article presents a framework for assisting companies in deciding under what condition to centralize or decentralize their inventory to fulfill customer orders without disrupting the shopping experience.

scholarly journals Optimization of production allocation and transportation of customer orders for a leading forest products company

2008 ◽  
Vol 48 (7-8) ◽  
pp. 1158-1169 ◽  
Author(s):  
Mehmet Aydinel ◽  
Taraneh Sowlati ◽  
Ximena Cerda ◽  
Eric Cope ◽  
Mats Gerschman
Keyword(s):  
Forest Products ◽  
Production Allocation ◽  
Customer Orders

scholarly journals Customer order scheduling with job-based processing on a single-machine to minimize the total completion time

2021 ◽  
Vol 12 (3) ◽  
pp. 273-292 ◽  
Author(s):  
Ferda Can Çetinkaya ◽  
Pınar Yeloğlu ◽  
Hale Akkocaoğlu Çatmakaş
Keyword(s):  
Completion Time ◽  
Numerical Control ◽  
Total Completion Time ◽  
Mixed Integer ◽  
Order Scheduling ◽  
Customer Order ◽  
Processing Approach ◽  
Problem Instances ◽  
Customer Order Scheduling ◽  
Customer Orders

This study considers a customer order scheduling (COS) problem in which each customer requests a variety of products (jobs) processed on a single flexible machine, such as the computer numerical control (CNC) machine. A sequence-independent setup for the machine is needed before processing each product. All products in a customer order are delivered to the customer when they are processed. The product ordered by a customer and completed as the last product in the order defines the customer order’s completion time. We aim to find the optimal schedule of the customer orders and the products to minimize the customer orders’ total completion time. We have studied this customer order scheduling problem with a job-based processing approach in which the same products from different customer orders form a product lot and are processed successively without being intermingled with other products. We have developed two mixed-integer linear programming models capable of solving the small and medium-sized problem instances optimally and a heuristic algorithm for large-sized problem instances. Our empirical study results show that our proposed tabu search algorithm provides optimal or near-optimal solutions in a very short time. We have also compared the job-based and order-based processing approaches for both setup and no-setup cases and observed that the job-based processing approach yields better results when jobs have setup times.

scholarly journals Mathematical models for a batch scheduling problem to minimize earliness and tardiness

2018 ◽  
Vol 11 (3) ◽  
pp. 390 ◽  
Author(s):  
Basar Ogun ◽  
Çigdem Alabas-Uslu
Keyword(s):  
Mathematical Models ◽  
Real World ◽  
Lean Manufacturing ◽  
Programming Model ◽  
Computational Study ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Earliness And Tardiness ◽  
Customer Orders

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented.Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems.Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.

Representation Learning for Predicting Customer Orders

2021 ◽  
Author(s):  
Tongwen Wu ◽  
Yu Yang ◽  
Yanzhi Li ◽  
Huiqiang Mao ◽  
Liming Li ◽  
...  
Keyword(s):  
Representation Learning ◽  
Customer Orders
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