Free trial or no free trial: Optimal software product design with network effects

A common business strategy to promote product adoption in software industry is to provide a free trial version with limited functionalities of the commercial product to increase the installed user base. The increase of user base will lead to higher value of the software because of positive network effects. However, offering a free trial version may cannibalize some demand of the commercial software. This paper examines the tradeoff between network effects and the cannibalization effect, and aims to uncover the conditions under which firms should introduce the free trial product. We find that when network intensity is strong, it is more profitable for a software monopoly to offer free trial than to segment the market with two versions of different qualities. In addition, this paper solves the joint decision problem of finding the optimal quality for the firm’s free trial software and the optimal price of its commercial product.     

A Polynomial Time Approximation Scheme for the Grade of Service Steiner Minimum Tree Problem

In this paper, we present the design of a Polynomial Time Approximation Scheme (PTAS) for the Grade of Service Steiner Minimum Tree (GOSST) problem, which is known to be NP-Complete. Previous research has focused on geometric analyses and different approximation algorithms have been designed. We propose a PTAS that provides a polynomial time, near-optimal solution with performance ratio 1+. The GOSST problem has some important applications. In network design, a fundamental issue for the physical construction of a network structure is the interconnection of many communication sites with the best choice of the connecting lines and the best allocation of the transmission capacities over these lines. Good solutions should provide paths with enough communication capacities between any two sites, with the least network construction costs. Also, the GOSST problem has applications in transportation, for road constructions and some potential uses in CAD in terms of interconnecting the elements on a plane to provide enough flux between any two elements.     

A combinatorial interior point method for network flow problems

For solving minimum cost flow problems, we develop a combinatorial interior point method based on a variant of the algorithm of Karmarkar, described in Gonzaga [3, 4]. Gonzaga proposes search directions generated by projecting certain directions onto the nullspace ofA. By the special combinatorial structure of networks any projection onto the nullspace ofA can be interpreted as a flow in the incremental graph ofG. In particular, to evaluate the new search direction, it is sufficient to choose a negative circuit subject to costs on the arcs depending on the current solution. That approach results in an O(mn ² L) algorithm wherem denotes the number of vertices,n denotes the number of arcs, andL denotes the total length of the input data.     

贷款分配方法的数学模型及其解法

为了解决三角债问题，银行给出一笔贷款，应该如何分配这笔贷款，使清理的债务达到最大。本文建立这个问题的数学模型，并且给出一个解法。     

Kinematic Analysis of Robotic Bevel-Gear Trains: An Application of Network Model Approach

The network model approach for rigid and multi-rigid body systems developed recently [1,2] can also be used conveniently in formulating system equations or equations of motion of three-dimensional mechanical systems of interconnected rigid bodies. In this article, this method is further elaborated for establishing only the kinematics of spatial robotic bevel-gear trains. However the dynamic analysis of such systems using the same method is also possible and will be taken up in a future publication.     

Scheduling in network flow shops

We consider the general problem of static scheduling of a set of jobs in a network flow shop. In network flow shops, the scheduler not only has to sequence and schedule but also must concurrently determine the process routing of the jobs through the shop. In this paper, we establish the computational complexity of this new class of scheduling problem and propose a general purpose heuristic procedure. The performance of the heuristic is analyzed when makespan, cycle time and average flow time are the desired objectives.This research has been supported by the UCLA Academic Senate Grant #95.     

The network approach to calculation of characteristic time constants of the flat two-layer superconducting cable

The matrix method was used to investigate the process of current decay in the samples of flat two-layer superconducting cables. The discrete spectrum of eigen-frequencies has been obtained. Each of these frequencies determines the rate of decay of the correspondent eigen-current. Despite of the increasing of the number of eigen-frequencies with the enlargement of the sample dimensions the spectrum remains finite, as the maximum and minimum frequencies tend to finite limits. An analysis made for the lowest eigen-frequencies showed the corresponding eigen-currents to be slowly decaying long current loops. Within the range of high frequencies the sinusoidal distribution of eigen-currents in the rows of the cable was observed.     

Detecting embedded pure network structures in LP problems

Recently, linear programming problems with special structures have assumed growing importance in mathematical programming. It is well known that exploiting network structures within linear programs can lead to considerable improvement of the computational solution of large-scale linear programming problems. A linear program is said to contain an embedded network structure provided that some subset of its constraints can be interpreted as specifying conservation of flow. If a column of the constraint matrix has at most two non-zeros, then it leads to embedded generalized network structure and if these non-zeros are unit elements and of opposite signs, then it leads to embedded pure network structure. In this paper, we are concerned with algorithms for detecting embedded pure network structures within linear programs. The network extraction methods are presented in two groups. The first group covers deletion and addition based algorithms and the second group covers GUB based algorithms. We have extended the GUB based algorithm appearing in the second group by introducing Markowitz merit count approach for exploiting matrix non zeros. A set of well known test problems has been used to carry out computational experiments which show that our extensions to the GUB based algorithms give better results than the algorithms reported earlier.     

Computational aspects of two-segment separable programming

Recursive separable programming algorithms based on local, two-segment approximations are described for the solution of separable convex programs. Details are also given for the computation of lower bounds on the optimal value by both a primal and a dual approach, and these approaches are compared. Computational comparisons of the methods are provided for a variety of test problems, including a water supply application (with more than 600 constraints and more than 900 variables) and an econometric modelling problem (with more than 200 variables). Research supported by National Science Foundation Grants MCS74-20584 A02 and MCS-7901066.