Establishing and Improving Service Process in a Subcontractors Organization

Tutkimus tuli ajankohtaiseksi kohdeyrityksen kehittäessä toimintaansa asiakaslähtöisemmäksi ja kilpailukykyisemmäksi. Kohdeyrityksen toimiessa muun muassa palveluntuottajana IT - lähitukipalveluiden monipuolisessa ja kilpaillussa ympäristössä, on sen pystyttävä tarjoamaan nykyisille asiakkailleen kilpailukykyisiä ja laadukkaita palveluja ja toisaalta pyrittävä jatkuvasti laajentamaan asiakaskuntaansa sekä tarjoamaan markkinoille uusia palveluratkaisuja. Tutkimuksen tavoitteena on prosessijohtamisen teoriaan pohjautuvien mallien ja työkalujen avulla kehittää kohdeyrityksen toimintaa ja näin edesauttaa kohdeyritystä menestymään markkinoilla. Yrityksen toimintaa päätettiin tarkastella nimenomaan prosessijohtamisen kautta, koska prosessijohtamista pidettiin tehokkaana keinona lisätä kilpailukykyä ja jota soveltamalla voidaan tehostaa omaa toimintaa ja parantaa ennen kaikkea asiakaslähtöisyyttä. Nykyisellään kohdeyrityksen palveluprosessi on melko heikosti dokumentoitu ja tarkemmat kuvaukset nykyisistä toimintamalleista puuttuvat. Esimerkiksi yrityksen solmiessa uusia asiakkuuksia, ei ole käytössä virallista mallia, miten ja missä järjestyksessä eri toiminnoista sovitaan asiakkaan kanssa. Tutkimuksessa tehtyjä havaintoja, päätelmiä ja malleja onkin tarkoitus käyttää jatkossa muun muassa helpottamaan ja nopeuttamaan uusien asiakkuuksien sovittamista kohdeyrityksen palveluprosessiin. Tutkimuksessa käsiteltävä aihealue on kokonaisuudessaan melko laaja ja pääpaino tässä tutkimuksessa on aikataulullisista syistä teoriatasolla. Tutkimuksessa luodut mallit arvioidaan yhdessä liiketoimintaryhmän johtajan kanssa, mutta mallien laajamittaisesta käytäntöön viennistä päätetään pidemmällä aikataululla. /Kir1

Lower bounds: from circuits to QBF proof systems

A general and long-standing belief in the proof complexity community asserts that there is a close connection between progress in lower bounds for Boolean circuits and progress in proof size lower bounds for strong propositional proof systems. Although there are famous examples where a transfer from ideas and techniques from circuit complexity to proof complexity has been effective, a formal connection between the two areas has never been established so far. Here we provide such a formal relation between lower bounds for circuit classes and lower bounds for Frege systems for quantified Boolean formulas (QBF). Starting from a propositional proof system P we exhibit a general method how to obtain a QBF proof system P+∀red{P}, which is inspired by the transition from resolution to Q-resolution. For us the most important case is a new and natural hierarchy of QBF Frege systems C-Frege+∀red that parallels the well-studied propositional hierarchy of C-Frege systems, where lines in proofs are restricted to belong to a circuit class C. Building on earlier work for resolution [Beyersdorff, Chew and Janota, 2015a] we establish a lower bound technique via strategy extraction that transfers arbitrary lower bounds for the circuit class C to lower bounds in C-Frege+∀red. By using the full spectrum of state-of-the-art circuit lower bounds, our new lower bound method leads to very strong lower bounds for QBF \FREGE systems: 1. exponential lower bounds and separations for the QBF proof system ACo[p]-Frege+∀red for all primes p; 2. an exponential separation of ACo[p]-Frege+∀red from TCo/d-Frege+∀red; 3. an exponential separation of the hierarchy of constant-depth systems ACo/d-Frege+∀red by formulas of depth independent of d. In the propositional case, all these results correspond to major open problems

Constraints and AI Planning

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the authorâ s and shouldnâ t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.Tackling real-world problems often requires to take various types of constraints into account. Such constraint types range from simple numerical comparators to complex resources. This article describes how planning techniques can be integrated with general constraint-solving frameworks, like SAT, IP and CP. In many cases, the complete planning problem can be cast in these frameworks

Planning graphs and propositional clause-learning

The planning graph of Blum and Furst is one of the frequently used tools in planning. It is a data structure which can be visualized as a bipartite graph with state variables and actions as nodes and which approximates (upper bound) the set of reachable states with a given number of sets of simultaneous actions. We show that the contents of planning graphs follow from two more general notions: extended clause learning restricted to 2-literal clauses and the representation of parallel plans consisting of STRIPS actions in the classical propositional logic. This is the first time planning graphs have been given an explanation in terms of the inference methods used in SAT solvers. The work helps in bridging the gap between specialized algorithms devised for planning and general-purpose algorithms for automated reasoning

Scheduling with Contingent Resources and Tasks

Finding optimal schedules for the most commonly considered classes of scheduling problems is NP-complete. Best algorithms scale up to very large scheduling problems when optimality is not required and good solution quality suffices. These problems have perfect information in the sense that the resource availability, set of tasks, task duration, and other important facts, are fully known at the time of constructing a schedule. However, the assumption of perfect information is rarely satisfied, and real-world scheduling faces several forms of uncertainty, most notably with respect to durations and availability of resources. The effective handling of uncertainty is a major issue in applying scheduling in new areas. In this work, we investigate the properties of a number of classes of problems of contingent scheduling, in which assignments of resources to tasks depend on resource availability and other facts that are only known fully during execution, and hence the off-line construction of one fixed schedule is insufficient. We show that contingent scheduling in most general cases is most likely outside the complexity class NP, and resides, depending on the assumptions, in PSPACE, Sigma-p-2 or Pi-p-2. The results prove that standard constraint-satisfaction and SAT frameworks are in general not straightforwardly applicable to contingent scheduling