In this paper sequencing situations with Just-in-Time (JiT) arrival are introduced. This new type of one-machine sequencing situations assumes that a job is available to be handled by the machine as soon as its predecessor is finished. A basic predecessor dependent set-up time is incorporated in the model. Sequencing situations with JiT arrival are first analyzed from an operations research perspective: for a subclass an algorithm is provided to obtain an optimal order. Secondly, we analyze the allocation problem of the minimal joint cost from a game theoretic perspective. A corresponding sequencing game is defined followed by an analysis of a context-specific rule that leads to core elements of this game.

We present a unifying framework for transferable utility coalitional games that are derived from a non-negative matrix in which every entry represents the value obtained by combining the corresponding row and column. We assume that every row and every column is associated with a player, and that every player is associated with at most one row and at most one column. The instances arising from this framework are called matching games, and they encompass assignment games and permutation games as two polar cases. We show that the core of a matching game is always nonempty by proving that the set of matching games coincides with the set of permutation games. Then we focus on two separate problems. First, we exploit the wide range of situations comprised in our framework to investigate the relationship between matching games with different player sets but defined by the same underlying matrix. We show that the core is not only immune to the merging of a row player and a column player, but also to the reverse manipulation, i.e., to the splitting of a player into a row player and a column player. Other common solution concepts fail to be either merging-proof or splitting-proof in general. Second, we focus on permutation games only and we analyze the set of all matrices that define permutation games with the same core. In contrast to assignment games, we show that there can be multiple matrices whose entries cannot be raised without modifying the core of the corresponding permutation game and that, for small instances, every such matrix defines an exact game.

For games with a non-empty core the Alexia value is introduced, a value which averages the lexicographic maxima of the core. It is seen that the Alexia value coincides with the Shapley value for convex games, and with the nucleolus for strongly compromise admissible games and big boss games. For simple flow games, clan games and compromise stable games an explicit expression and interpretation of the Alexia value is derived. Furthermore it is shown that the reverse Alexia value, defined by averaging the lexicographic minima of the core, coincides with the Alexia value for convex games and compromise stable games.

In this paper we present an axiomatic analysis of several ranking methods for tournaments. We find that two of them exhibit a very good behaviour with respect to the set of properties under consideration. One of them is the maximum likelihood ranking, the most common method in statistics and psychology. The other one is a new ranking method introduced in this paper: recursive Buchholz. One of the most widely studied methods in social choice, the fair bets ranking, also performs quite well, but fails to satisfy some arguably important properties.

In this paper preparation sequencing situations are introduced. This new type of one-machine sequencing situations assumes that before a job can start, some preparation depending on its predecessor is required. Preparation sequencing situations are first analyzed from an operations research perspective: optimality conditions are provided and an algorithm is provided to obtain an optimal order. Secondly, we analyze the allocation problem of the minimal joint cost from a game theoretic perspective. A corresponding preparation sequencing game is defined and the focus is on the core and nucleolus of such games.

This paper revisits the Alexia value, a recent solution concept for cooperative transferable utility games. We introduce the dual Alexia value and show that it coincides with the Alexia value for several classes of games. We demonstrate the importance of the notion of compromise stability for characterizing the Alexia value.