Online Facility Assignments on Polygons

TL;DR

The findings have many practical implications because large networks of facilities are best partitioned into smaller and geometrically simple pieces to guarantee good overall performance.

Abstract

We study the online facility assignment problem on regular polygons, where all sides are of equal length. The influence of specific geometric settings has remained mostly unexplored, even though classical online facility assignment problems have mainly dealt with linear and general metric spaces. We fill this gap by considering the following four basic geometric settings: equilateral triangles, rectangles, regular $n$-polygons, and circles. The facilities are situated at fixed positions on the boundary, and customers appear sequentially on the boundary. A customer needs to be assigned immediately without any information about future customer arrivals. We study a natural greedy algorithm. First, we study an equilateral triangle with three facilities at its corners; customers can appear anywhere on the boundary. We then analyze regular $n$-sided polygons, obtaining a competitive ratio of $2n-1$, showing that the algorithm performance degrades linearly with the number of corner points for polygons. For the circular configuration, the competitive ratio is $2n-1$ when the distance between two adjacent facilities is the same. And the competitive ratios are $n^2-n+1$ and $2^n - 1$ for varying distances linearly and exponentially respectively. Each facility has a fixed capacity proportional to the geometric configuration, and customers appear only along the boundary edges. Our results also show that simpler geometric configurations have more efficient performance bounds and that spacing facilities uniformly apart prevent worst-case scenarios. The findings have many practical implications because large networks of facilities are best partitioned into smaller and geometrically simple pieces to guarantee good overall performance.

Figures (11)

• Figure 1: 1(a) Triangular Approach for the best case, 1(b)Triangular Approach Assignment Concept (capacity is two). The dotted line and solid line indicate the optimal and greedy algorithms, respectively.
• Figure 2: Clockwise and Anticlockwise Movement.
• Figure 3: Illustrating Case 1 of triangular approach.
• Figure 4: Exploring the Correlation Between cost (of greedy algorithm) and Ratio
• Figure 5: Illustrating Case 2 of the triangular approach.

Theorems & Definitions (16)

• lemma thmcounterlemma
• proof
• theorem thmcountertheorem
• proof
• theorem thmcountertheorem
• proof
• lemma thmcounterlemma
• proof
• theorem thmcountertheorem
• proof