Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Developing a simulated annealing algorithm for the cutting stock problem
Computers and Industrial Engineering
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Heuristic and Metaheuristic Approaches for a Class of Two-Dimensional Bin Packing Problems
INFORMS Journal on Computing
Efficient scheduling of Internet banner advertisements
ACM Transactions on Internet Technology (TOIT)
Performance bounds of algorithms for scheduling advertisements on a web page
Journal of Scheduling
Approximating the Advertisement Placement Problem
Journal of Scheduling
Scheduling Banner Advertisements on the Web
INFORMS Journal on Computing
Scheduling Web Advertisements: A Note on the Minspace Problem
Journal of Scheduling
Heuristic approaches for the two- and three-dimensional knapsack packing problem
Computers and Operations Research
An Exact Algorithm for Higher-Dimensional Orthogonal Packing
Operations Research
Allocation of Multiple Advertisement on Limited Space: Heuristic Approach
FMN '09 Proceedings of the 2nd International Workshop on Future Multimedia Networking
Single Pattern Generating Heuristics for Pixel Advertisements
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
An improved web system for pixel advertising
EC-Web'06 Proceedings of the 7th international conference on E-Commerce and Web Technologies
On the two-dimensional Knapsack Problem
Operations Research Letters
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The problem addressed in this paper is the allocation of multiple advertisements on a Web banner, in order to maximize the revenue of the allocated advertisements. It is essentially a two-dimensional, single, orthogonal, knapsack problem, applied to pixel advertisement. As this problem is known to be NP-hard, and due to the temporal constraints that Web applications need to fulfill, we propose several heuristic algorithms for generating allocation patterns. The heuristic algorithms presented in this paper are the left justified algorithm, the orthogonal algorithm, the GRASP constructive algorithm, and the greedy stripping algorithm. We set out an experimental design using standard banner sizes, and primary and secondary sorting criteria for the set of advertisements. We run two simulations, the first simulation compares the heuristics with an optimal solution found using brute force search, and the second simulation compares the heuristic algorithms to gain a better insight into their performance. Finding a suitable pattern generating algorithm is a trade-off between effectiveness and efficiency. Results indicate that allocating advertisements with the orthogonal algorithm is the most effective. In contrast, allocating advertisements using the greedy stripping algorithm is the most efficient. Furthermore, the best settings per algorithm for each banner size are given.