Task-Oriented Active Sensing via Action Entropy Minimization

This work is licensed under a Creative Commons Attribution 4.0 International License.In active sensing, sensing actions are typically chosen to minimize the uncertainty of the state according to some information-theoretic measure such as entropy, conditional entropy, mutual information, etc. This is reasonable for applications where the goal is to obtain information. However, when the information about the state is used to perform a task, minimizing state uncertainty may not lead to sensing actions that provide the information that is most useful to the task. This is because the uncertainty in some subspace of the state space could have more impact on the performance of the task than others, and this dependence can vary at different stages of the task. One way to combine task, uncertainty, and sensing, is to model the problem as a sequential decision making problem under uncertainty. Unfortunately, the solutions to these problems are computationally expensive. This paper presents a new task-oriented active sensing scheme, where the task is taken into account in sensing action selection by choosing sensing actions that minimize the uncertainty in future task-related actions instead of state uncertainty. The proposed method is validated via simulations

Rational Value of Information Estimation for Measurement Selection

Computing value of information (VOI) is a crucial task in various aspects of decision-making under uncertainty, such as in meta-reasoning for search; in selecting measurements to make, prior to choosing a course of action; and in managing the exploration vs. exploitation tradeoff. Since such applications typically require numerous VOI computations during a single run, it is essential that VOI be computed efficiently. We examine the issue of anytime estimation of VOI, as frequently it suffices to get a crude estimate of the VOI, thus saving considerable computational resources. As a case study, we examine VOI estimation in the measurement selection problem. Empirical evaluation of the proposed scheme in this domain shows that computational resources can indeed be significantly reduced, at little cost in expected rewards achieved in the overall decision problem.Comment: 7 pages, 2 figures, presented at URPDM2010; plots fixe

Планування інноваційного виробництва на основі комплексної методики вибору раціональної альтернативи

Introduction. Innovation is one of the major factors of economic growth in modern economy on the macrolevel, and a prominent contributor to an enterprise's profit increase at microlevel. Nevertheless, innovation activity is accompanied by a high level of risk and may cause significant losses. Thus, the problem of limiting the risk by developing rational methods of decision making is relevant. Aim and tasks. The article aims at development of integrated methodology for taking a decision as to selection of rational innovative production alternative based on the usage of a group of decision making methods in dependency on conditions under which the decision is being taken. Results. The article analyses decision making process in the context of system approach and defines stages of decision making. Criteria of effective decision are described and classified. Methods of decision making are observed and classified according to the conditions of decision making. The necessary components of integrated methodology of  selection of rational innovative production alternative are defined. The formation principles and general structure of the integrated methodology of selection of rational innovative production alternative are described. Conclusions. The task of decision effectiveness assessment is complicated by simultaneous existence of number of performance goals with different suitability for formal evaluation, negative correlation between speed and accuracy of decision making, and temporal distance between decision making process and goal achievement, which requires employment of discounting methods. The above-mentioned factors determine the necessity for an integrated criterion, which includes economic efficiency indicators but is not reduced to them. Thus, integrated methodology of selection of rational innovative production alternative consists of multicriteria decision making solution, assessment of sufficient range of alternatives, allowance for uncertainty as to input information about criteria, inclusion of different types of criteria measurement, provision of possibility to use alternative information at all stages of decision making process.Вступ. Інновації є одним з основних факторів економічного зростання в сучасній економіці на макрорівні та істотним фактором збільшення прибутку підприємства на мікрорівні. Проте, інноваційна діяльність супроводжується високим рівнем ризику і може призвести до значних збитків. Таким чином, актуальною є проблема обмеження ризику шляхом розробки раціональних методів прийняття рішень. Мета і завдання. Метою статті є розробка комплексної методології прийняття рішення про вибір раціональної інноваційної виробничої альтернативи на основі використання групи методів прийняття рішень в залежності від умов прийняття рішення. Результати. У статті проаналізовано процес прийняття рішень у контексті системного підходу та визначено етапи прийняття рішень. Описано та класифіковано критерії ефективного рішення. Досліджено методи прийняття рішень та класифіковано відповідно до умов прийняття рішень. Визначено необхідні компоненти комплексної методології вибору раціональної інноваційної виробничої альтернативи. Описано принципи формування та загальну структуру комплексної методології вибору раціональної інноваційної виробничої альтернативи. Висновки. Завдання оцінки ефективності рішень ускладнюється одночасним існуванням ряду цілей ефективності з різною придатністю для формальної оцінки, негативною кореляцією між швидкістю і точністю прийняття рішень і віддаленістю у часі між процесом прийняття рішень і досягненням мети, що вимагає застосування методів дисконтування. Перераховані вище фактори визначають необхідність комплексного критерію, який включає показники економічної ефективності, але не зводиться до них. Таким чином, комплексна методологія вибору раціональної інноваційної виробничої альтернативи складається з багатокритеріального рішення для прийняття рішень, оцінки достатнього діапазону альтернатив, обліку невизначеності вхідної інформації про критерії, включення різних видів вимірювання критеріїв, забезпечення можливості використання альтернативної інформації на всіх етапах процесу прийняття рішень

Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection

Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing. Fierce competition amongst business sectors necessitates adapting modern supply chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decisionmaking relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work. Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration. Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. vi Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making

Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection

Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing. Fierce competition amongst business sectors necessitates adapting modern supply chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decisionmaking relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work. Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration. Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. vi Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making