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Distribute the Selfish Ambitions 143
Figure 3: Various approaches in solving benchmark problem with bi-criteria objectives
and, each of which is required for executing an activity. The capacity of each resource type is the summed
resource capacity in each instance. Projects are released sequentially, in a pace of every 5 time units.
Figure 4: Various approaches in solving AGH problem with bi-criteria objectives
Experimental results in Figure 3 show that i) in all solution methods, the higher resource levelling value
goes (cf. x-axis), the less total delay (cf. y-axis: equivalent as mean project flow times in representing
time-based objective) will be suffered; ii) Non-cooperative online multiagent heuristic approach provides
a schedule that is of comparable quality of centralized heuristic methods. iii) Moreover, by letting selfinterested
agents behave cooperative, given the same total delay, we can have lower resource levelling value.
Therefore, the overall schedule made by cooperative agent scheduling heuristic is significantly improved: it
is comparable with the best heuristic methods.
Experiments for airport specialized instances
An instance of AGH multi-project scheduling problem has the features that all projects have similar network
structure and similar activity set. In order to build an AGH multi-project scheduling problem instance, we
simulate a multi-project set by cloning a single-project instance in PSPLib. We conduct the experiments
with 30 identical projects created out of the project instance J301 1, each project represents an aircraft
turnaround, and aircraft are released every 5 time units. As in the benchmark problem experiments, five