Industrial Organization Commons^™

Competition For Innovation, Herbert J. Hovenkamp

All Faculty Scholarship

Both antitrust and IP law are limited and imperfect instruments for regulating innovation. The problems include high information costs and lack of sufficient knowledge, special interest capture, and the jury trial system, to name a few. More fundamentally, antitrust law and intellectual property law have looked at markets in very different ways. Further, over the last three decades antitrust law has undergone a reformation process that has made it extremely self conscious about its goals. While the need for such reform is at least as apparent in patent and copyright law, very little true reform has actually occurred.

Antitrust has …

Distributive Justice And Consumer Welfare In Antitrust, Herbert J. Hovenkamp

All Faculty Scholarship

The dominant view of antitrust policy in the United States is that it is intended to promote some version of economic welfare. More specifically, antitrust promotes allocative efficiency by ensuring that markets are as competitive as they can practicably be, and that firms do not face unreasonable roadblocks to attaining productive efficiency, which refers to both cost minimization and innovation.

The distribution concern that has dominated debates over United States antitrust policy over the last several decades is whether antitrust should adopt a “consumer welfare” principle rather than a more general neoclassical “total welfare” principle. In The Antitrust Paradox Robert …

The Innovation Commons, Herbert J. Hovenkamp

All Faculty Scholarship

This book of CASES AND MATERIALS ON INNOVATION AND COMPETITION POLICY is intended for educational use. The book is free for all to use subject to an open source license agreement. It differs from IP/antitrust casebooks in that it considers numerous sources of competition policy in addition to antitrust, including those that emanate from the intellectual property laws themselves, and also related issues such as the relationship between market structure and innovation, the competitive consequences of regulatory rules governing technology competition such as net neutrality and interconnection, misuse, the first sale doctrine, and the Digital Millennium Copyright Act (DMCA). Chapters …

Voice Without Say: Why Capital-Managed Firms Aren’T (Genuinely) Participatory, Justin Schwartz

Justin Schwartz

Why are most capitalist enterprises of any size organized as authoritarian bureaucracies rather than incorporating genuine employee participation that would give the workers real authority? Even firms with employee participation programs leave virtually all decision-making power in the hands of management. The standard answer is that hierarchy is more economically efficient than any sort of genuine participation, so that participatory firms would be less productive and lose out to more traditional competitors. This answer is indefensible. After surveying the history, legal status, and varieties of employee participation, I examine and reject as question-begging the argument that the rarity of genuine …

Defense, U.S. Department Of, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Provides an overview of U.S. Department of Defense activities in the western U.S. including the military's increasing emphasis on Asia-Pacific strategic trends and developments.

Federal Energy Regulatory Commission, U.S., Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Provides a historical overview and contemporary analysis of the energy policymaking role played by the Energy Department's Federal Energy Regulatory Commission (FERC). FERC responsibilities include regulating the prices and interstate transmission of electricity, natural gas, and oil. Its responsibilities also include reviewing proposals to build and locate natural gas terminals, interstate natural gas pipelines, licensing hydropower projects, and regulating relevant mergers and securities acquisitions in these areas.

Working Regions: Reconnecting Innovation And Production In The Knowledge Economy, Jennifer Clark

Jennifer Clark

Adding Injustice To Injury - Health Perceptions, Plurality, And Power In The Ongoing Bhopal Disaster, Ruth Markwardt

Independent Study Project (ISP) Collection

Standards of health, human rights, and development are typically defined and dictated by policymakers instead of the populations directly affected by so-called development efforts. This paper seeks to contextualize global development efforts by highlighting specific local realities among the community of Bhopal Disaster survivors in Madhya Pradesh, India. As the site of the world’s largest industrial disaster, a disaster which is not over but ongoing, Bhopal represents an important population to highlight as the disaster continues. The Political Ecology of Health model was used to highlight political and environmental influences on community health. Within Political Ecology, this study takes a …

A Partial Instantiation Based First Order Theorem Prover, Vijay Chandru, John N. Hooker, Anjul Shrivastava, Gabriela Rago

John Hooker

Satisfiability algorithms for propositional logic have improved enormously in recent years. This increases the attractiveness of satisfiability methods for first order logic that reduce the problem to a series of ground-level satisfiability problems. Partial Instantiation for first order satisfiability differs radically from standard resolution based methods. Two approaches to partial instantiation based first order theorem provers have been studied by R. Jeroslow and by Plaisted and Zhu. Hooker and Rago have described improvements of Jeroslow's approach by a) extending it to logic with functions b) accelerating it through use of satisfiers as introduced by Gallo and Rago, and c) simplifying …

Predicting Cause-Effect Relationships From Incomplete Discrete Observations, E Boros, P. L. Hammer, John N. Hooker

John Hooker

This paper addresses a prediction problem occurring frequently in practice. The problem consists in predicting the value of a function on the basis of discrete observational data that are incomplete in two senses. Only certain arguments of the function are observed, and the function value is observed only for certain combinations of values of these arguments. The problem is considered under a monotonicity condition that is natural in many applications. Applications to tax auditing, medicine, and real estate valuation are discussed. In particular, a special class of problems is identified for which the best monotone prediction can be found in …

Partial Instantiation Methods For Inference In First-Order Logic, John N. Hooker, G. Rago, V. Chandru, A. Shrivastava

John Hooker

Satisfiability algorithms for propositional logic have improved enormously in recently years. This improvement increases the attractiveness of satisfiability methods for first-order logic that reduce the problem to a series of ground-level satisfiability problems. R. Jeroslow introduced a partial instantiation method of this kind that differs radically from the standard resolution-based methods. This paper lays the theoretical groundwork for an extension of his method that is general enough and efficient enough for general logic programming with indefinite clauses. In particular we improve Jeroslow's approach by (1) extending it to logic with functions, (2) accelerating it through the use of satisfiers, as …

Boolean Regression, E. Boros, P. L. Hammer, John N. Hooker

John Hooker

We take a regression-based approach to the problem of induction, which is the problem of inferring general rules from specific instances. Whereas traditional regression analysis fits a numerical formula to data, we fit a logical formula to boolean data. We can, for instance, construct an expert system for fitting rules to an expert's observed behavior. A regression-based approach has the advantage of providing tests of statistical significance as well as other tools of regression analysis. Our approach can be extended to nonboolean discrete data, and we argue that it is better suited to rule construction than logit and other types …

A Relaxation Of The Cumulative Constraint, John N. Hooker, Hong Yan

John Hooker

Hybrid methods that combine constraint programming with mathematical programming make essential use of continuous relaxations for global constraints. We state a relaxation for the cumulative constraint. In particular we identify facet-defining inequalities for problems in which some jobs have the same duration, release time, and resource consumption rate. We also identify a much larger class of valid inequalities that exist in all problems.

A Hybrid Method For Planning And Scheduling, John N. Hooker

John Hooker

We combine mixed integer linear programming (MILP) and constraint programming (CP) to solve planning and scheduling problems. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. Tasks assigned to a facility may run in parallel subject to resource constraints (cumulative scheduling). We solve minimum cost problems, as well as minimum makespan problems in which all tasks have the same release date and deadline. We obtain computational speedups of several orders of magnitude relative to the state of the art in both MILP and CP.

Optimization Methods In Logic, John N. Hooker

John Hooker

Optimization can make at least two contributions to boolean logic. Its solution methods can address inference and satisfiability problems, and its style of analysis can reveal tractable classes of boolean problems that might otherwise have gone unnoticed.

Optimality Conditions For Distributive Justice, John N. Hooker

John Hooker

This paper uses optimization theory to address a fundamental question of ethics: how to divide resources justly among individuals, groups, or organizations. It formulates utilitarian and Rawlsian criteria for distributive justice as optimization problems. The formulations recognize that some recipients are more productive than others, so that an inequitable distribution may create greater overall utility. Conditions are derived under which a distribution of resources is utility maximizing, and under which it achieves a lexicographic maximum, which we take as formulating the difference principle of John Rawls. It is found that utility maximization requires at least as much inequality as results …

Inference-Based Sensitivity Analysis For Mixed Integer/Linear Programming, M. W. Dawande, John N. Hooker

John Hooker

A new method of sensitivity analysis for mixed integer/linear programming (MILP) is derived from the idea of inference duality. The inference dual of an optimization problem asks how the optimal value can be deduced from the constraints. In MILP, a deduction based on the resolution method oftheorem proving can be obtained from the branch-and-cut tree that solves the primal problem. One can then investigate which perturbations ofthe problem leave this proof intact. On this basis it is shown that, in a minimization problem, any perturbation that satisfies a certain system of linear inequalities will reduce the optimal value no more …

Mathematical Programming Methods For Reasoning Under Uncertainty, John N. Hooker

John Hooker

We survey three applications of mathematical programming to reasoning under uncertainty: a) an application of linear programming to probabilistic logic, b) an application of nonlinear programming to Bayesian logic, a combination of Bayesian inference with probabilistic logic and c) an application of integer programming to Dempster-Shafer theory, which is a method of combining evidence from diffierent sources

A Cross-Cultural View Of Corruption, John N. Hooker

John Hooker

The world is shrinking, but its cultures remain worlds apart, as do its ethical norms. The West views bribery, kickbacks, cronyism and nepotism as unethical, but they are standard practice in many parts of the world. This poses a familiar dilemma for business firms that operate globally: should they engage in what they see as corrupt behavior in order to do business? The position defended here is that firms should always resist corruption, but at the same time understand it from a broader perspective: as behavior that undermines a cultural system. Behavior that is acceptable in one country may be …

A Generalized Dilworth's Theorem, With Application To Routing And Scheduling, John N. Hooker, N R. Natraj

John Hooker

Dilworth's theorem states a duality relation between minimum chain decompositions of a directed, acyclic graph and maximum antichains. We generalize the theorem to apply when the chains of the decomposition are required to contain the chains of an initial decomposition. We show that duality obtains precisely when an associated undirected graph is perfect. We apply this result to a vehicle routing and scheduling problem with time windows. Here each chain of the initial decomposition contains nodes that correspond to the pickup, delivery and possibly intermediate stops associated with a piece of cargo.

Solving The Capacitated Local Access Network Design Problem, F. Sibel Salman, R. Ravi, John N. Hooker

John Hooker

We propose an exact solution method for a routing and capacity installation problem in networks. Given an input graph, the problem is to route traffic from a set of source nodes to a sink node and to install transmission facilities on the edges of the graph to accommodate the flow at minimum cost. We give a branch-and-bound algorithm that solves relaxations obtained by approximating the noncontinuous cost function by its lower convex envelope. The approximations are refined by branching on the flow ranges on selected edges. Our computational experiments indicate that this method is effective in solving moderate-size problems and …

Logical Inference And Polyhedral Projection, John N. Hooker

John Hooker

We explore connections between polyhedral projection and inference in propositional logic. We formulate the problem of drawing all inferences that contain a restricted set of atoms (i.e., all inferences that pertain to a given question) as a logical projection problem. We show that polyhedral projection partially solves this problem and in particular derives precisely those inferences that can be obtained by a certain form of unit resolution. We prove that this unit resolution algorithm is exponential in the number of atoms in the restricted set but is polynomial in the problem size when this number of fixed. We also survey …

A Search-Infer-And-Relax Framework For Integrating Solution Methods, John N. Hooker

John Hooker

We present an algorithmic framework for integrating solution methods that is based on search, inference, and relaxation and their interactions. We show that the following are special cases: branch and cut, CP domain splitting with propagation, popular global optimization methods, DPL methods for SAT with conflict clauses, Benders decomposition and other nogood-based methods, partial-order dynamic backtracking, various local search metaheuristics, and GRASPs (greedy randomized adaptive search procedures). The framework allows elements of different solution methods to be combined at will, resulting in a variety of integrated methods. These include continuous relaxations for global constraints, the linking of integer and constraint …

Planning And Scheduling To Minimize Tardiness, John N. Hooker

John Hooker

We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. We consider two objectives: minimizing the number of late tasks, and minimizing total tardiness. Our main theoretical contribution is a relaxation of the cumulative scheduling subproblem, which is critical to performance. We obtain substantial computational speedups relative to the state of the art in both MILP and CP. We also obtain much better solutions for problems that cannot be solved to optimality.

Inference Duality As A Basis For Sensitivity Analysis, John N. Hooker

John Hooker

The constraint programming community has recently begun to address certain types of optimization problems. These problems tend to be discrete or to have discrete elements. Although sensitivity analysis is well developed for continuous problems, progress in this area for discrete problems has been limited. This paper proposes a general approach to sensitivity analysis that applies to both continuous and discrete problems. In the continuous case, particularly in linear programming, sensitivity analysis can be obtained by solving a dual problem. One way to broaden this result is to generalize the classical idea of a dual to that of an ldquoinference dual,rdquo …

Planning And Scheduling By Logic-Based Benders Decomposition, John N. Hooker

John Hooker

We combine mixed-integer linear programming (MILP) and constraint programming (CP) to solve an important class of planning and scheduling problems. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. Tasks assigned to a facility may run in parallel subject to resource constraints (cumulative scheduling). We solve problems in which the objective is to minimize cost, makespan, or total tardiness. We obtain significant computational speedups, of several orders of magnitude for the first two objectives, relative to the state of the art in both MILP and CP. We also obtain …

On Integrating Constraint Propagation And Linear Programming For Combinatorial Optimization, John N. Hooker, Greger Ottosson, Erlendur S. Thorsteinsson, Hak-Jin Kim

John Hooker

Linear programming and constraint propagation are complementary techniques with the potential for integration to benefit the solution of combinatorial optimization problems.

A Declarative Modeling Framework That Integrates Solution Methods, John N. Hooker, Hak-Jin Kim, G. Ottosson

John Hooker

Constraint programming offers modeling features and solution methods that are unavailable in mathematical programming but are often flexible and efficient for scheduling and other combinatorial problems. Yet mathematical programming is well suited to declarative modeling languages and is more efficient for some important problem classes. This raises this issue as to whether the two approaches can be combined in a declarative modeling framework. This paper proposes a general declarative modeling system in which the conditional structure of the constraints shows how to integrate any "checker" and any special-purpose "solver". In particular this integrates constraint programming and optimization methods, because the …

An Integrated Method For Planning And Scheduling To Minimize Tardiness, John N. Hooker

John Hooker

We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. We consider two objectives: minimizing the number of late tasks, and minimizing total tardiness. Our main theoretical contribution is a relaxation of the cumulative scheduling subproblem, which is critical to performance. We obtain substantial computational speedups relative to the state of the art in both MILP and CP. We also obtain much better solutions for problems that cannot be solved to optimality.

Cultural Differences In Business Communication, John N. Hooker

John Hooker

There is no better arena for observing a culture in action than business. Cultures tend to reveal themselves in situations where much is as stake, because it is here that their resources are most needed. Marriage, family obligations, and such stressful experiences as illness and the death of a loved one bring out much of what is distinctive and fundamental in a culture. The same is true of business, because economic survival is at stake. Business practices are shaped by deeply-held cultural attitudes toward work, power, trust, wealth—and communication.