Abstract The “somewhat vague, intuitive” notion from computability theory of an effective procedure (method) or algorithm can be fairly precisely defined even if it is not sufficiently formal and precise to belong mathematics proper (in a narrow sense)—and (as many have asserted) for that reason the Church–Turing thesis unprovable. It proved logically class procedures decidable, i.e., there no ...

In this paper, we generalize the Ski-Rental Problem to the Bahncard Problem which is an online problem of practical relevance for all travelers. The Bahncard is a railway pass of the Deutsche Bundes-bahn (the German railway company) which entitles its holder to a 50% price reduction on nearly all train tickets. It costs 240 DM, and it is valid for 12 months. For the common traveler, the decisio...

Most of data in a multi-attribute decision making (MADM) problem are unstable and changeable, then sensitivity analysis after problem solving can effectively contribute to making accurate decisions. This paper provides a new method for sensitivity analysis of MADM problems so that by using it and changing the weights of attributes, one can determine changes in the final results of a decision ma...

Background The concept of decision space holds appeal as an approach to disaggregating the elements that may influence decision-making in decentralized systems. This narrative review aims to explore the functioning of decision space and the factors that influence decision space.   Methods A narrative review of the literature was conducted with searches of online databases and academic journals ...

in this paper, we investigate a decision support system (dss) for the resolution of real-life vehicle routing and scheduling problem (vrsp). scheduling the deliveries from a regional distribution centre (rdc) to large stores of a major fmcg retailer includes every possible vehicle routing complexity. usual constraints that are seen are: size of the vehicle and the length of the driving day, loa...

We address the problem that different users have different lexical knowledge about problem domains, so that automated dialogue systems need to adapt their generation choices online to the users’ domain knowledge as it encounters them. We approach this problem using policy learning in Markov Decision Processes (MDP). In contrast to related work we propose a new statistical user model which incor...

In this paper we introduce a discrete version of the online traveling salesman problem (DOLTSP). We represent the metric space using a weighted graph, where the server is allowed to modify its route only at the vertices. This limitation directly affects the capacity of the server to react and increases the risk related to each decision. We prove lower bounds on the performance of deterministic ...

In online shopping scenarios, it can be difficult for consumers to process the vast amounts of information available and to make satisfactory buying decisions. Interactive decision aids are a potential solution to this problem. However, decision aids that filter a very large set of alternatives based on initial preferences may eliminate potentially valuable alternatives early in the decision pr...