1139. Population-based search algorithms for an integrated scheduling problem in the pharmaceutical two-stage supply chain
Invited abstract in session MB-49: Integrated lot-sizing problems, stream Lot Sizing, Lot Scheduling and Production Planning.
Monday, 10:30-12:00Room: M1 (building: 101)
Authors (first author is the speaker)
| 1. | Byung Soo Kim
|
| Industrial & Management Engineering, Incheon National University | |
| 2. | Seung Jae Lee
|
| Industrial & Management Engineering, Incheon National University |
Abstract
This paper addresses an integrated scheduling problem in the pharmaceutical two-stage supply chain. The problem is composed of multiple pharmaceutical orders, multiple unrelated factories, and one distribution center. Each factory uses a distinct permutation flow shop line consisting of hybrid batch/continuous processes and considers sequence-dependent change-over time. The distribution center picks up the products by truck shipment. The objective function is to minimize the makespan. Lot sizing, assigning, and production and truck shipment sequencing processes are the main decisions for the addressed problem. A mixed integer linear program is developed, and two types of population-based search algorithms are proposed to effectively and efficiently find the near-optimal solutions for the large-sized instances. In the small-sized experiments, the performances of the algorithms are verified by the absolute comparison with the mixed integer linear program. In the large-sized experiments, the performances of the algorithms are evaluated by the relative comparison.
Keywords
- Supply Chain Management
- Scheduling
- Metaheuristics
Status: accepted
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