30 research outputs found
On Profit-Maximizing Pricing for the Highway and Tollbooth Problems
In the \emph{tollbooth problem}, we are given a tree \bT=(V,E) with
edges, and a set of customers, each of whom is interested in purchasing a
path on the tree. Each customer has a fixed budget, and the objective is to
price the edges of \bT such that the total revenue made by selling the paths
to the customers that can afford them is maximized. An important special case
of this problem, known as the \emph{highway problem}, is when \bT is
restricted to be a line.
For the tollbooth problem, we present a randomized -approximation,
improving on the current best -approximation. We also study a
special case of the tollbooth problem, when all the paths that customers are
interested in purchasing go towards a fixed root of \bT. In this case, we
present an algorithm that returns a -approximation, for any
, and runs in quasi-polynomial time. On the other hand, we rule
out the existence of an FPTAS by showing that even for the line case, the
problem is strongly NP-hard. Finally, we show that in the \emph{coupon model},
when we allow some items to be priced below zero to improve the overall profit,
the problem becomes even APX-hard
On the Complexity of the Highway Pricing Problem
The highway pricing problem asks for prices to be determined for segments of a single highway such as to maximize the revenue obtainable from a given set of customers with known valuations. The problem is (weakly) NP-hard and a recent quasi-PTAS suggests that a PTAS might be in reach. Yet, so far it has resisted any attempt for constant-factor approximation algorithms. We relate the tractability of the problem to structural properties of customers' valuations. We show that the problem becomes NP-hard as soon as the average valuations of customers are not homogeneous, even under further restrictions such as monotonicity. Moreover, we derive an efficient approximation algorithm, parameterized along the inhomogeneity of customers' valuations. Finally, we discuss extensions of our results that go beyond the highway pricing problem.\u
Price Strategy Implementation
Consider a situation in which a company sells several different items to a set of customers. However, the company is not satisfied with the current pricing strategy and wishes to implement new prices for the items. Implementing these new prices in one single step mightnot be desirable, for example, because of the change in contract prices for the customers. Therefore, the company changes the prices gradually, such that the prices charged to a subset of the customers, the target market, do not differ too much from one period to the next. We propose a polynomial time algorithm to implement the new prices in the minimum number of time periods needed, given that the prices charged to the customers in the target market increase by at most a factor 1 + δ, for predetermined δ > 0. Furthermore, we address the problem to maximize the revenue when also a maximum number of time periods is predetermined. For this problem, we describe a dynamic program if the numberof possible prices is limited, and a local search algorithm if all prices are allowed. Also, we present the integer program that models this problem. Finally, we apply the obtained algorithms in a practical study.operations research and management science;
Progress on pricing with peering
This paper examines a simple model of how a
provider ISP charges customer ISPs by assuming the provider
ISP wants to maximize its revenue when customer ISPs have
the possibility of setting up peering connections. It is shown that
finding the optimal pricing is NP-complete, and APX-complete.
Customers can respond to price in many ways, including throttling
traffic as well as peering. An algorithm is studied which
obtains a 1/4 approximation for a wide range of customer
responses
Stackelberg Network Pricing Games
We study a multi-player one-round game termed Stackelberg Network Pricing
Game, in which a leader can set prices for a subset of priceable edges in a
graph. The other edges have a fixed cost. Based on the leader's decision one or
more followers optimize a polynomial-time solvable combinatorial minimization
problem and choose a minimum cost solution satisfying their requirements based
on the fixed costs and the leader's prices. The leader receives as revenue the
total amount of prices paid by the followers for priceable edges in their
solutions, and the problem is to find revenue maximizing prices. Our model
extends several known pricing problems, including single-minded and unit-demand
pricing, as well as Stackelberg pricing for certain follower problems like
shortest path or minimum spanning tree. Our first main result is a tight
analysis of a single-price algorithm for the single follower game, which
provides a -approximation for any . This can
be extended to provide a -approximation for the
general problem and followers. The latter result is essentially best
possible, as the problem is shown to be hard to approximate within
\mathcal{O(\log^\epsilon k + \log^\epsilon m). If followers have demands, the
single-price algorithm provides a -approximation, and the
problem is hard to approximate within \mathcal{O(m^\epsilon) for some
. Our second main result is a polynomial time algorithm for
revenue maximization in the special case of Stackelberg bipartite vertex cover,
which is based on non-trivial max-flow and LP-duality techniques. Our results
can be extended to provide constant-factor approximations for any constant
number of followers
On the Complexity of the Highway Pricing Problem
The highway pricing problem asks for prices to be determined for segments of a single highway such as to maximize the revenue obtainable from a given set of customers with known valuations. The problem is (weakly) NP-hard and a recent quasi-PTAS suggests that a PTAS might be in reach. Yet, so far it has resisted any attempt for constant-factor approximation algorithms. We relate the tractability of the problem to structural properties of customers'' valuations. We show that the problem becomes NP-hard as soon as the average valuations of customers are not homogeneous, even under further restrictions such as monotonicity. Moreover, we derive an efficient approximation algorithm, parameterized along the inhomogeneity of customers'' valuations. Finally, we discuss extensions of our results that go beyond the highway pricing problem.operations research and management science;
Optimal Bundle Pricing with Monotonicity Constraint
We consider the problem to price (digital) items in order to maximize the revenue obtainable from a set of bidders. We suggest a natural monotonicity constraint on bundle prices, show that the problem remains NP-hard, and we derive a PTAS. We also discuss a special case, the highway pricing problem.operations research and management science;
Optimal Bundle Pricing for Homogeneous Items
We consider a revenue maximization problem where we are selling a set of m items, each of which available in a certain quantity (possibly unlimited) to a set of n bidders. Bidders are single minded, that is, each bidder requests exactly one subset, or bundle of items. Each bidder has a valuation for the requested bundle that we assume to be known to the seller. The task is to find an envy-free pricing such as to maximize the revenue of the seller. We derive several complexity results and algorithms for several variants of this pricing problem. In fact, the settings that we consider address problems where the different items are `homogeneous'' in some sense. First, we introduce the notion of affne price functions that can be used to model situations much more general than the usual combinatorial pricing model that is mostly addressed in the literature. We derive fixed-parameter polynomial time algorithms as well as inapproximability results. Second, we consider the special case of combinatorial pricing, and introduce a monotonicity constraint that can also be seen as `global'' envy-freeness condition. We show that the problem remains strongly NP-hard, and we derive a PTAS - thus breaking the inapproximability barrier known for the general case. As a special case, we finally address the notorious highway pricing problem under the global envy-freeness condition.operations research and management science;