Quantity-Contingent Auctions and Allocation of Airport Slots

2020 ◽  
Vol 54 (4) ◽  
pp. 858-881 ◽  
Author(s):  
Michael O. Ball ◽  
Alexander S. Estes ◽  
Mark Hansen ◽  
Yulin Liu
Keyword(s):  
Integer Programming ◽  
Market Power ◽  
Road Network ◽  
Programming Model ◽  
Continuous Model ◽  
Winner Determination Problem ◽  
Single Product ◽  
Winner Determination ◽  
Multiple Units ◽  
Airport Slots

In this paper, we define and investigate quantity-contingent auctions. Such auctions can be used when there exist multiple units of a single product and the value of a set of units depends on the total quantity sold. For example, a road network or airport will become congested as the number of users increase so that a permit for use becomes more valuable as the total number allocated decreases. A quantity-contingent auction determines both the number of items sold and an allocation of items to bidders. Because such auctions could be used by bidders to gain excessive market power, we impose constraints limiting market power. We focus on auctions that allocate airport arrival and departure slots. We propose a continuous model and an integer programming model for the associated winner determination problem. Using these models, we perform computational experiments that lend insights into the properties of the quantity-contingent auction.

Biased Random-Key Genetic Algorithms for the Winner Determination Problem in Combinatorial Auctions

2015 ◽  
Vol 23 (2) ◽  
pp. 279-307 ◽  
Author(s):  
Carlos Eduardo de Andrade ◽  
Rodrigo Franco Toso ◽  
Mauricio G. C. Resende ◽  
Flávio Keidi Miyazawa
Keyword(s):  
Genetic Algorithms ◽  
Linear Programming ◽  
Large Scale ◽  
Programming Model ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Winner Determination Problem ◽  
Winner Determination ◽  
Linear Integer Programming ◽  
Linear Programming Relaxations

In this paper we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

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.

EXPRESS: Investigating the Effects of Excise Taxes, Public Usage Restrictions, and Anti-Smoking Ads across Cigarette Brands

2021 ◽  
pp. 002224292199456
Author(s):  
Yanwen Wang ◽  
Michael Lewis ◽  
Vishal Singh
Keyword(s):  
Market Power ◽  
Market Share ◽  
Brand Choice ◽  
Continuous Model ◽  
Marketing Strategies ◽  
Brand Strength ◽  
Excise Taxes ◽  
Cigarette Tax ◽  
Pass Through ◽  
The Impact

The prevalence of strong brands such as Coca-Cola, McDonald’s, Budweiser, and Marlboro in “vice” categories has important implications for regulators and consumers. While researchers in multiple disciplines have studied the effectiveness of anti-tobacco counter-marketing strategies, little attention has been given to how brand strength may moderate the efficacy of tactics such as excise taxes, usage restrictions, and educational advertising campaigns. In this research, we use a multiple discrete-continuous model to study the impact of anti-smoking techniques on smokers’ choices of brands and quantities. Our results suggest that while cigarette excise taxes decrease smoking rates, these taxes also result in a shift in market share towards stronger brands. Market leaders may be less affected by tax policies because their market power allows strong brands such as Marlboro to absorb rather than pass through increased taxes. In contrast, smoke-free restrictions cause a shift away from stronger brands. In terms of anti-smoking advertising we find minimal effects on brand choice and consumption. The findings highlight the importance of considering brand asymmetries when designing a policy portfolio cigarette tax hikes, smoke-free restrictions, and anti-smoking advertising campaigns.

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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