14,505 research outputs found
Production/maintenance cooperative scheduling using multi-agents and fuzzy logic
Within companies, production is directly concerned with the manufacturing schedule, but other services like sales, maintenance, purchasing or workforce management should also have an influence on this schedule. These services often have together a hierarchical relationship, i.e. the leading function (most of the time sales or production) generates constraints defining the framework within which the other functions have to satisfy their own objectives. We show how the multi-agent paradigm, often used in scheduling for its ability to distribute decision-making, can also provide a framework for making several functions cooperate in the schedule performance. Production and maintenance have been chosen as an example: having common resources (the machines), their activities are actually often conflicting. We show how to use a fuzzy logic in order to model the temporal degrees of freedom of the two functions, and show that this approach may allow one to obtain a schedule that provides a better compromise between the satisfaction of the respective objectives of the two functions
Automating decision making to help establish norm-based regulations
Norms have been extensively proposed as coordination mechanisms for both
agent and human societies. Nevertheless, choosing the norms to regulate a
society is by no means straightforward. The reasons are twofold. First, the
norms to choose from may not be independent (i.e, they can be related to each
other). Second, different preference criteria may be applied when choosing the
norms to enact. This paper advances the state of the art by modeling a series
of decision-making problems that regulation authorities confront when choosing
the policies to establish. In order to do so, we first identify three different
norm relationships -namely, generalisation, exclusivity, and substitutability-
and we then consider norm representation power, cost, and associated moral
values as alternative preference criteria. Thereafter, we show that the
decision-making problems faced by policy makers can be encoded as linear
programs, and hence solved with the aid of state-of-the-art solvers
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