What Automated Planning Can Do for Business Process Management

Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle

An optimal-control based integrated model of supply chain

Problems of supply chain scheduling are challenged by high complexity, combination of continuous and discrete processes, integrated production and transportation operations as well as dynamics and resulting requirements for adaptability and stability analysis. A possibility to address the above-named issues opens modern control theory and optimal program control in particular. Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of complexity, dynamics, uncertainty, and adaptivity. Supply chain schedule generation is represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. The calculation procedure is based on applying Pontryagin’s maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. With the developed model, important categories of supply chain analysis such as stability and adaptability can be taken into consideration. Besides, the dimensionality of operations research-based problems can be relieved with the help of distributing model elements between an operations research (static aspects) and a control (dynamic aspects) model. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes.supply chain, model of supply chain scheduling, optimal program control theory, Pontryagin’s maximum principle, operations research model,

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

AGILE PORTFOLIO MANAGEMENT: DESIGN GOALS AND PRINCIPLES

Digital transformation and the resulting volatile and unpredictable business environments challenge traditional enterprises to continuously fulfill and surpass customers’ expectations. They need to become agile in its organization by proactively sensing the unpredictable change and responding accordingly with speed and dexterity. While many organizations are quite advanced in realizing adaptivity at the operational level, strategic agility in general and in portfolio management in particular as linking op-erations and strategy for satisfying the customer needs is in its nascence. To identify the baseline for portfolio management for achieving agility, we derive four design goals for an effective agile portfolio management system, six design principles on how to achieve these goals and show an exemplary setup with design features. Our results are based on a research study with empirical insights from six com-panies and theoretical input from thirteen existing case studies and eight frameworks for scaling agility to the portfolio level. By deriving design principles for an agile portfolio management system, our work closes a gap in existing research, which focuses on principles for adaptive IT portfolio management processes instead of proactive enterprise systems, insights on individual portfolio practices or non-generalizable blueprints for an agile organizational setup without showing alternative approaches

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability

Internet-of-Things (IoT) envisions an intelligent infrastructure of networked smart devices offering task-specific monitoring and control services. The unique features of IoT include extreme heterogeneity, massive number of devices, and unpredictable dynamics partially due to human interaction. These call for foundational innovations in network design and management. Ideally, it should allow efficient adaptation to changing environments, and low-cost implementation scalable to massive number of devices, subject to stringent latency constraints. To this end, the overarching goal of this paper is to outline a unified framework for online learning and management policies in IoT through joint advances in communication, networking, learning, and optimization. From the network architecture vantage point, the unified framework leverages a promising fog architecture that enables smart devices to have proximity access to cloud functionalities at the network edge, along the cloud-to-things continuum. From the algorithmic perspective, key innovations target online approaches adaptive to different degrees of nonstationarity in IoT dynamics, and their scalable model-free implementation under limited feedback that motivates blind or bandit approaches. The proposed framework aspires to offer a stepping stone that leads to systematic designs and analysis of task-specific learning and management schemes for IoT, along with a host of new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive and Scalable Communication Network

Management: thesis, antithesis, synthesis

Increasingly, managers live in a world of paradox. For instance, they are told that they must manage by surrendering control and that they must stay on top by continuing to learn, thus admitting that they do not fully know what they do. Paradox is becoming increasingly pervasive in and around organizations, increasing the need for an approach to management that allows both researchers and practitioners to address these paradoxes. A synthesis is required between such contradictory forces as efficiency and effectiveness, planning and action, and structure and freedom. A dialectical view of strategy and organizations, built from four identifiable principles of simultaneity, locality, minimality and generality, enables us to build the tools to achieve such synthesis. Put together, these principles offer new perspectives for researchers to look at management phenomena and provide practitioners with a means of addressing the increasingly paradoxical world that they confront.dialectics, improvisation, paradox, synthesis

Navigating the future: Building adaptive capacity in international schools

Given the pace and complexity of change for schools globally, this study investigates how leaders of international schools are navigating the future for the organisations they lead. The research draws on two pieces of existing literature, firstly that of Adaptive Leadership Theory which has mainly evolved outside the education sector and secondly literature related to the School as a Learning Organisation (SLO) which has not specifically been defined within the international school context. This study explores how relevant and applicable these two concepts are for international schools and investigates what the relationship is between the two concepts. This study is qualitative, using eleven semi-structured interviews with educational leaders working in the international school sector. The participants within this study defined, with a strong degree of consistency, their view of schools as adaptive organisations and of adaptive leadership, identifying three overarching themes: openness, strong sense of identity and empowerment. Participants also defined a set of adaptive leadership behaviours which they viewed as essential for growing adaptive capacity in international school leaders. From the data analysed within this study, the SLO concept is relevant and applicable to an international school context. This research contributes to a gap in the knowledge base relating to adaptivity in the education context, specifically in relation to international schools. Detail is provided on the characteristics of an adaptive international school and adaptive international school leadership. The research provides confidence for the applicability of the SLO model in international schools and defines the interrelationship between this and the concept of adaptivity