Mobility offer allocations in corporate settings

IF 2.6 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI:10.1016/j.ejco.2021.100010
Sebastian Knopp, Benjamin Biesinger, Matthias Prandtstetter
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引用次数: 3

Abstract

Corporate mobility is often based on a fixed assignment of vehicles to employees. Relaxing this fixation and including alternatives such as public transportation or taxis for business and private trips could increase fleet utilization and foster the use of battery electric vehicles. We introduce the mobility offer allocation problemas the core concept of a flexible booking system for corporate mobility. The problem is equivalent to interval scheduling on dedicated unrelated parallel machines. We show that the problem is NP-hard to approximate within any factor. We describe problem specific conflict graphs for representing and exploring the structure of feasible solutions. A characterization of all maximum cliques in these conflict graphs reveals symmetries which allow to formulate stronger integer linear programming models. We also present an adaptive large neighborhood search based approach which makes use of conflict graphs as well. In a computational study, the approaches are evaluated. It was found that greedy heuristics perform best if very tight run-time requirements are given, a solver for the integer linear programming model performs best on small and medium instances, and the adaptive large neighborhood search performs best on large instances.

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移动提供分配在企业设置
企业流动性通常是基于员工的固定车辆分配。放松这种固定状态,为商务和私人旅行提供公共交通或出租车等替代方案,可以提高车队利用率,促进电池电动汽车的使用。我们介绍了一个灵活的企业移动预订系统的核心概念的流动性提供分配问题。这个问题相当于在专用的不相关并行机器上的间隔调度。我们证明了这个问题在任何因素范围内都是np困难的。我们描述了特定问题的冲突图,以表示和探索可行解决方案的结构。这些冲突图中所有最大团的特征揭示了允许制定更强的整数线性规划模型的对称性。我们还提出了一种基于冲突图的自适应大邻域搜索方法。在计算研究中,对这些方法进行了评估。结果表明,在给定非常严格的运行时间要求时,贪婪启发式算法的性能最好;整数线性规划模型的求解器在中小型实例上的性能最好;自适应大邻域搜索在大型实例上的性能最好。
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来源期刊
EURO Journal on Computational Optimization
EURO Journal on Computational Optimization OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
3.50
自引率
0.00%
发文量
28
审稿时长
60 days
期刊介绍: The aim of this journal is to contribute to the many areas in which Operations Research and Computer Science are tightly connected with each other. More precisely, the common element in all contributions to this journal is the use of computers for the solution of optimization problems. Both methodological contributions and innovative applications are considered, but validation through convincing computational experiments is desirable. The journal publishes three types of articles (i) research articles, (ii) tutorials, and (iii) surveys. A research article presents original methodological contributions. A tutorial provides an introduction to an advanced topic designed to ease the use of the relevant methodology. A survey provides a wide overview of a given subject by summarizing and organizing research results.
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