An LNS-based relax-and-restore matheuristic for integrated yard and manpower group planning in automotive terminals

Ziqiao Mei; Feng Chen; Ziqiao Mei; Feng Chen

doi:10.3934/jimo.2026179

Journal of Industrial and Management Optimization

2026, Volume 22, Issue 10: 5194-5226. doi: 10.3934/jimo.2026179

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Research article

An LNS-based relax-and-restore matheuristic for integrated yard and manpower group planning in automotive terminals

Ziqiao Mei ¹,
Feng Chen ^{2
,
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1.
Department of Management Science & Engineering, Antai College of Economics & Management, Shanghai Jiao Tong University, 200030, Shanghai, China
2.
Sino-US Global Logistics Institute, Antai College of Economics & Management, Shanghai Jiao Tong University, 200030, Shanghai, China

Received: 01 July 2026 Revised: 14 September 2026 Accepted: 15 September 2026 Published: 20 September 2026
90C11, 90C59, 90C27, 90B06, 90B35

This paper investigates a joint yard allocation and manpower group configuration and assignment problem in automotive roll-on/roll-off (RO-RO) terminals. Unlike existing yard allocation studies, this paper explicitly models manpower as standardized groups, each consisting of a fixed number of drivers transported together by a minibus between vessels and yard sections. Each order is associated with one vessel but can be allocated to multiple yard sections. The problem must determine the minimum required number of groups of each size as well as how to assign these groups to each order–section pair. We formulate the problem as an integer linear programming model to minimize the total manpower cost. To solve large-scale instances, we develop a large neighbourhood search-based relax-and-restore matheuristic (LNS-M) in which each encoded order sequence is evaluated through a three-stage relax-and-restore framework. The first stage constructs rough yard-operation plans, the second stage evaluates these plans with a partially relaxed manpower group configuration and assignment model, and the third stage conditionally restores integer feasibility for promising candidates. The main challenge introduced by group configuration is that extending the operation interval of an order–section pair can reduce the number of manpower groups assigned to this pair, but it may increase overlaps among several order–section pairs and create a higher peak driver demand. To address this challenge, we design a peak-aware scoring mechanism to determine the start and completion times of each pair. Extensive numerical experiments demonstrate the effectiveness of the proposed method and validate the contributions of the peak-aware scoring mechanism and the matheuristic framework. Compared with a rule-based heuristic, LNS-M reduces the average manpower cost by 21.35%.
- RO-RO terminal,
- yard allocation,
- group configuration,
- manpower assignment,
- matheuristic
Citation: Ziqiao Mei, Feng Chen. An LNS-based relax-and-restore matheuristic for integrated yard and manpower group planning in automotive terminals[J]. Journal of Industrial and Management Optimization, 2026, 22(10): 5194-5226. doi: 10.3934/jimo.2026179

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Abstract

This paper investigates a joint yard allocation and manpower group configuration and assignment problem in automotive roll-on/roll-off (RO-RO) terminals. Unlike existing yard allocation studies, this paper explicitly models manpower as standardized groups, each consisting of a fixed number of drivers transported together by a minibus between vessels and yard sections. Each order is associated with one vessel but can be allocated to multiple yard sections. The problem must determine the minimum required number of groups of each size as well as how to assign these groups to each order–section pair. We formulate the problem as an integer linear programming model to minimize the total manpower cost. To solve large-scale instances, we develop a large neighbourhood search-based relax-and-restore matheuristic (LNS-M) in which each encoded order sequence is evaluated through a three-stage relax-and-restore framework. The first stage constructs rough yard-operation plans, the second stage evaluates these plans with a partially relaxed manpower group configuration and assignment model, and the third stage conditionally restores integer feasibility for promising candidates. The main challenge introduced by group configuration is that extending the operation interval of an order–section pair can reduce the number of manpower groups assigned to this pair, but it may increase overlaps among several order–section pairs and create a higher peak driver demand. To address this challenge, we design a peak-aware scoring mechanism to determine the start and completion times of each pair. Extensive numerical experiments demonstrate the effectiveness of the proposed method and validate the contributions of the peak-aware scoring mechanism and the matheuristic framework. Compared with a rule-based heuristic, LNS-M reduces the average manpower cost by 21.35%.

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