The role of the agent's outside options in principal-agent relationships

We consider a principal-agent model of adverse selection where, in order to trade with the principal, the agent must undertake a relationship-specific investment which affects his outside option to trade, i.e. the payoff that he can obtain by trading with an alternative principal. This creates a distinction between the agent’s ex ante (before investment) and ex post (after investment) outside options to trade. We investigate the consequences of this distinction, and show that whenever an agent’s ex ante and ex post outside options differ, this may equip the principal with an additional tool for screening among different agent types, by randomizing over the probability with which trade occurs once the agent has undertaken the investment. In turn, this may enhance the efficiency of the optimal second-best contract

The SeqBin Constraint Revisited

We revisit the SEQBIN constraint [1]. This meta-constraint subsumes a number of important global constraints like CHANGE [2], SMOOTH [3] and INCREASINGNVALUE [4]. We show that the previously proposed filtering algorithm for SEQBIN has two drawbacks even under strong restrictions: it does not detect bounds disentailment and it is not idempotent. We identify the cause for these problems, and propose a new propagator that overcomes both issues. Our algorithm is based on a connection to the problem of finding a path of a given cost in a restricted n-partite graph. Our propagator enforces domain consistency in O(nd 2) and, for special cases of SEQBIN that include CHANGE,SMOOTH and INCREASINGNVALUE in O(nd) time

An Optimal Arc Consistency Algorithm for a Particular Case of Sequence Constraint

International audienceThe AtMostSeqCard constraint is the conjunction of a cardinality constraint on a sequence of n variables and of n − q + 1 constraints AtMost u on each subsequence of size q. This constraint is useful in car-sequencing and crew-rostering problems. In van Hoeve et al. (Constraints 14(2):273-292, 2009), two algorithms designed for the AmongSeq constraint were adapted to this constraint with an O(2^q n) and O(n^3) worst case time complexity, respectively. In Maher et al. (2008), another algorithm similarly adaptable to filter the AtMostSeqCard constraint with a time complexity of O(n^2) was proposed. In this paper, we introduce an algorithm for achieving arc consistency on the AtMostSeqCard constraint with an O(n) (hence optimal) worst case time complexity. Next, we show that this algorithm can be easily modified to achieve arc consistency on some extensions of this constraint. In particular, the conjunction of a set of m AtMostSeqCard constraints sharing the same scope can be filtered in O(nm). We then empirically study the efficiency of our propagator on instances of the car-sequencing and crew-rostering problems

Author manuscript, published in "Proc. First International Workshop on Search Strategies and Non-standard Objectives, (CPAIOR- SSNOW'12) (2012)" FOCUS: A Constraint for Concentrating High Costs

Abstract. Many Constraint Programming models use integer cost variables aggregated in an objective criterion. In this context, some constraints involving exclusively cost variables are often imposed. Such constraints are complementary to the objective function. They characterize the solutions which are acceptable in practice. This paper deals with the case where the set of costs is a sequence, in which high values should be concentrated in a few number of areas. Representing such a property through an search heuristic may be complex and overall not precise enough. To solve this issue, we introduce a new constraint, FOCUS(X, yc, len, k), where X is a sequence of n integer variables, yc an integer variable, and len and k are two integers. To satisfy FOCUS, the minimum number of distinct sub-sequences of consecutive variables in X, of length at most len and that involve exclusively values strictly greater than k, should be less than or equal to yc. We present two examples of problems involving FOCUS. We propose a complete filtering algorithm in O(n) time complexity.

Linking Prefixes and Suffixes for Constraints Encoded Using Automata with Accumulators

Consider a constraint on a sequence of variables functionally determining a result variable that is unchanged under reversal of the sequence. Most such constraints have a compact encoding via an automaton augmented with accumulators, but it is unknown how to maintain domain consistency efficiently for most of them. Using such an automaton for such a constraint, we derive an implied constraint between the result variables for a sequence, a prefix thereof, and the corresponding suffix. We show the usefulness of this implied constraint in constraint solving, both by local search and by propagation-based systematic search