EURO 2024 Copenhagen
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2618. An adaptive VNS optimization algorithm for order acceptance with scheduling problem in additive manufacturing

Invited abstract in session WC-26: Topics in scheduling (Contributed), stream Combinatorial Optimization.

Wednesday, 12:30-14:00
Room: 012 (building: 208)

Authors (first author is the speaker)

1. Teng Cao
Management and Economics Department, Tianjin University

Abstract

We studied the order acceptance and scheduling problem on a single machine in additive manufacturing(AM) environment, considering a group of part orders with different sizes, profits, arrival date, due date, and delivery deadlines to be decided,manufactured and scheduled on an single AM machine. In our research, the AM machine is modeled as a batch processing Machine, processing part orders in batch sequences.Part orders are either accepted and assigned to a batch or rejected, the accepted orders are subject to dual constraints of time window and processing space.The goal is to maximize total net revenue considering orders revenue,processing costs, and penalties for delayed delivery and order rejection.

In this talk, we :
1.develop an Adaptive Variable Neighborhood Search Algorithm (AVNSA) to obtain a high-quality order acceptance list and part processing sequence which satisfies all technical constraints.
2.present a heuristics methods for initialization.
3.propose 9 kinds of move operators for neighborhood search and 2 kinds of backtracking mechanism to prevent the algorithm from getting stuck in local optima
4.make the comparisons between the proposed AVNSA and several methods in previous research in 135 randomly generated instances.

The preliminary experimental results illustrates that,within shorter CPU time,the AVNSA is capable to obtain better solutions with higher net revenue,fill rate and less delay.



Keywords

Status: accepted

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