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

Ferda Can Çetinkaya,Hale Akkocaoğlu Çatmakaş,Pınar Yeloğlu

doi:10.5267/j.ijiec.2021.3.001

Ferda Can Çetinkaya, Hale Akkocaoğlu Çatmakaş + Show 1 more

Open Access

https://doi.org/10.5267/j.ijiec.2021.3.001

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Abstract

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.

Highlights

Most of the existing research on classical scheduling problems, unlike the customer order scheduling (COS) problem, assumes that a single customer orders various products, or there are multiple customer orders, each of which consists of only a single product
Our results demonstrate that the job-based processing approach does not optimally solve large-size problems; this approach provides the best integer solutions, which are still better than the solutions obtained for the problems solved by the orderbased processing approach
This study considers a customer order scheduling problem in a single machine to find a schedule with a sequence of jobs and the sequence of customer orders in each job when the job-based processing approach is used to minimize the customer orders’ total completion time

Summary

Introduction

Most of the existing research on classical scheduling problems, unlike the customer order scheduling (COS) problem, assumes that a single customer orders various products (jobs), or there are multiple customer orders, each of which consists of only a single product. Each order is a collection of several products processed in a job lot consisting of many customer orders demanding the same product. In such a system, an order is shipped as a group to the customer, at the completion time of that order’s last job (Liu, 2009). In the order-based processing, which is the most frequently used in previous COS studies in the literature, all various products in a customer order form an order lot (group), and all products in this order are processed successively without being intermingled with other customer orders’ products (Yang, 2011). In order-based processing, the customer orders’ sequence and the processing sequence of the products in each customer order lot need to be simultaneously determined. While order-based processing aims to manage customer orders on the shop floor job-based processing aims to reduce the negative effect of job setups, especially when the setup times required before processing the products are significantly longer

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