scholarly journals Personnel rostering: models and algorithms for scheduling, rescheduling and ensuring robustness

2020 ◽  
Author(s):  
Toni I. Wickert ◽  
Luciana S. Buriol ◽  
Greet Vanden Berghe ◽  
Pieter Smet
Keyword(s):  
Integer Programming ◽  
Real World ◽  
Programming Model ◽  
State Of The Art ◽  
Porto Alegre ◽  
Computation Techniques ◽  
Integer Programming Model ◽  
The Past ◽  
Model Based ◽  
World Demand

Personnel rostering is the process of assigning employees to shifts while respecting a set of constraints. Despite progress in recent decades concerning computation techniques, a considerable number of organizations continue to organize their rosters manually. This thesis seeks to bridge the gap between academia and practice by (i) introducing an integer programming model based on a real-world demand and a matheuristic to quickly generate results, (ii) producing state-of-the-art results for cyclic rostering problems using instances available in the literature, (iii) designing new rerostering strategies for repairing disruptions in multi-skilled rostering scenarios, and (iv) introducing a metric for quantifying and enforcing robustness in rosters. Besides the scientific contributions resulted from the thesis, this work is also relevant in practice. Since April of 2019, Hospital de Clínicas de Porto Alegre employs this PhD's outcome, named ProScheduleSolver to compute its physicians' rosters. The automation takes a few minutes, as opposed to multiple hours in the past, and results in 24,7\% less overtime for the physicians.

scholarly journals Optimization of Classification Track Assignment Considering Block Sequence at Train Marshaling Yard

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yingqun Zhang ◽  
Rui Song ◽  
Shiwei He ◽  
Haodong Li ◽  
Xiaole Guo
Keyword(s):  
Integer Programming ◽  
Numerical Experiment ◽  
Real World ◽  
Programming Model ◽  
Block Sequence ◽  
Operational Process ◽  
Integer Programming Model ◽  
The Real ◽  
Reasonable Amount ◽  
Number Of Factors

An operational process at train marshaling yard is considered in this study. The inbound trains are decoupled and disassembled into individual railcars, which are then moved to a series of classification tracks, forming outbound trains after being assembled and coupled. We focus on the allocation plan of the classification tracks. Given are the disassembling and assembling sequence, the railcars connection plan, and a number of classification tracks. Output is the assignment of the railcars to the classification tracks. An integer programming model is proposed, aimed at reducing the number of coupling operations, as well as the number of dirty tracks which is related to the rehumping operation, and the order of the railcars on the outbound train must satisfy the block sequence. Tabu algorithm is designed to solve the problem, and the model is also tested by CPLEX in comparison. A numerical experiment based on a real-world case is analyzed, and the result can be reached within a reasonable amount of time. We also discussed a number of factors that may affect the track assignment and gave suggestions for the real-world case.

scholarly journals Reshuffle minimisation to improve storage yard operations efficiency

2021 ◽  
Vol 15 ◽  
pp. 174830262199401
Author(s):  
Hammed Bisira ◽  
Abdellah Salhi
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Heuristic Approach ◽  
Container Terminals ◽  
Exact Method ◽  
Computational Results ◽  
Binary Integer Programming ◽  
Integer Programming Model ◽  
Compatibility Test ◽  
Storage Area

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.

scholarly journals Allocating Students to Industry Placements Using Integer Programming and Ant Colony Optimisation

Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 219
Author(s):  
Dhananjay Thiruvady ◽  
Kerri Morgan ◽  
Susan Bedingfield ◽  
Asef Nazari
Keyword(s):  
Integer Programming ◽  
Gender Equity ◽  
Programming Model ◽  
Original Data ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Integer Programming Model ◽  
Problem Instances ◽  
Work Integrated Learning ◽  
Time Required

The increasing demand for work-ready students has heightened the need for universities to provide work integrated learning programs to enhance and reinforce students’ learning experiences. Students benefit most when placements meet their academic requirements and graduate aspirations. Businesses and community partners are more engaged when they are allocated students that meet their industry requirements. In this paper, both an integer programming model and an ant colony optimisation heuristic are proposed, with the aim of automating the allocation of students to industry placements. The emphasis is on maximising student engagement and industry partner satisfaction. As part of the objectives, these methods incorporate diversity in industry sectors for students undertaking multiple placements, gender equity across placement providers, and the provision for partners to rank student selections. The experimental analysis is in two parts: (a) we investigate how the integer programming model performs against manual allocations and (b) the scalability of the IP model is examined. The results show that the IP model easily outperforms the previous manual allocations. Additionally, an artificial dataset is generated which has similar properties to the original data but also includes greater numbers of students and placements to test the scalability of the algorithms. The results show that integer programming is the best option for problem instances consisting of less than 3000 students. When the problem becomes larger, significantly increasing the time required for an IP solution, ant colony optimisation provides a useful alternative as it is always able to find good feasible solutions within short time-frames.

Research on the Freight Station Layout

2013 ◽  
Vol 380-384 ◽  
pp. 4506-4510
Author(s):  
Miao Du ◽  
Yong Qin ◽  
Zi Yang Wang ◽  
Zhong Xin Zhao ◽  
Hong Fei Yu ◽  
...  
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Rapid Expansion ◽  
Mixed Integer ◽  
Railway Stations ◽  
Integer Programming Model ◽  
Rail Freight ◽  
Mixed Integer Programming Model ◽  
Train Operation

At present, there are many problems existing in railway stations, such as excessive numbers and over-crowded layout, which seriously affect the scale benefit generation and rapid expansion of rail freight capacity. Aimed at these problems, a Mixed Integer programming model is proposed. Taking Lanzhou train operation depot for example, applying lingo software, the layout of freight station is obtained.

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