MaxSAT-Based Scheduling of B2B Meetings

Bofill, Miquel; Garcia, Marc; Suy, Josep; Villaret, Mateu

doi:10.1007/978-3-319-18008-3_5

Cited by 13 publications

(18 citation statements)

References 8 publications

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“…Note that the regret heuristic cannot be applied since the objective function is not separable over the s pt branching variables. We use the 20 instances from (Bofill et al 2015): they feature from 42 to 78 participants, a few hundred meetings, and from 8 to 22 time slots to schedule them. Most of these are quite challenging for our CP model.…”

Section: Business-to-business Meeting Schedulingmentioning

confidence: 99%

Counting-Based Search for Constraint Optimization Problems

Pesant

2016

AAAI

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Branching heuristics based on counting solutions in constraints have been quite good at guiding search to solve constraint satisfaction problems. But do they perform as well for constraint optimization problems? We propose an adaptation of counting-based search for optimization, show how to modify solution density computation for some of the most frequently-occurring constraints, and empirically evaluate its performance on several benchmark problems.

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Section: Business-to-business Meeting Schedulingmentioning

confidence: 99%

Counting-Based Search for Constraint Optimization Problems

Pesant

2016

AAAI

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“…Model-and-solve approaches on a more complete formulation have been developed in recent works. Several CP, MIP and SAT based encodings have been studied by Bofill, Espasa, Garcia, Palahí, Suy, and Villaret (2014), by Pesant, Rix, and Rousseau (2015) and by Bofill, Garcia, Suy, and Villaret (2015).…”

Section: Introductionmentioning

confidence: 99%

Constraint Solving Approaches to the Business-to-Business Meeting Scheduling Problem

Bofill¹,

Coll²,

García³

et al. 2022

jair

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The Business-to-Business Meeting Scheduling problem consists of scheduling a set of meetings between given pairs of participants to an event, while taking into account participants’ availability and accommodation capacity. A crucial aspect of this problem is that breaks in participants’ schedules should be avoided as much as possible. It constitutes a challenging combinatorial problem that needs to be solved for many real world brokerage events. In this paper we present a comparative study of Constraint Programming (CP), MixedInteger Programming (MIP) and Maximum Satisfiability (MaxSAT) approaches to this problem. The CP approach relies on using global constraints and has been implemented in MiniZinc to be able to compare CP, Lazy Clause Generation and MIP as solving technologies in this setting. We also present a pure MIP encoding. Finally, an alternative viewpoint is considered under MaxSAT, showing best performance when considering some implied constraints. Experiments conducted on real world instances, as well as on crafted ones, show that the MaxSAT approach is the one with the best performance for this problem, exhibiting better solving times, sometimes even orders of magnitude smaller than CP and MIP.

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“…The paper is mainly theoretical, but it is important to highlight that MaxSAT solving has been applied to solve problems in a range of real-world domains as diverse as bioinformatics [11,22], circuit design and debugging [23], community detection in complex networks [15], diagnosis [10], FPGA routing [25], planning [26], scheduling [5] and team formation [21], among many others.…”

Section: Introductionmentioning

confidence: 99%

A Tableau Calculus for Non-clausal Maximum Satisfiability

Manyà

Soler

2019

Lecture Notes in Computer Science

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We define a non-clausal MaxSAT tableau calculus. Given a multiset of propositional formulas φ, we prove that the calculus is sound in the sense that if the minimum number of contradictions derived among the branches of a completed tableau for φ is m, then the minimum number of unsatisfied formulas in φ is m. We also prove that it is complete in the sense that if the minimum number of unsatisfied formulas in φ is m, then the minimum number of contradictions among the branches of any completed tableau for φ is m. Moreover, we describe how to extend the proposed calculus to deal with hard and weighted soft formulas.

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MaxSAT-Based Scheduling of B2B Meetings

Cited by 13 publications

References 8 publications

Counting-Based Search for Constraint Optimization Problems

Counting-Based Search for Constraint Optimization Problems

Constraint Solving Approaches to the Business-to-Business Meeting Scheduling Problem

A Tableau Calculus for Non-clausal Maximum Satisfiability

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