Traditional heuristic search algorithms use the ranking of states that a heuristic function provides to guide the search. In this paper—with the objective of improving suboptimality and runtime of search algorithms when only weak heuristics are available—we present Stratified Tree Search (STS), a suboptimal heuristic search algorithm that uses a heuristic to partition the state space to guide t...

This paper aims to find the efficient state of hybrid electric vehicle (HEV) by simultaneous optimization of the control strategy and the power train. The power transmission employed in this vehicle is a power-split continuously variable transmission (CVT) which uses several fixed ratio mechanisms. After describing this transmission, the rules of electric assist control strategy are introduced....

We consider the problem of how to design resource allocation policies that both provide good performance at predicted environmental conditions and are robust against changes or misprediction of the environmental conditions. We evaluate various common threshold-based allocation policies within a simple model, where there is a clear tradeoff between the (conflicting) goals of good performance and...

Supervised alternative clusterings is the problem of finding a set of clusterings which are of high quality and different from a given negative clustering. The task is therefore a clear multi-objective optimization problem. Optimizing two conflicting objectives at the same time requires dealing with tradeoffs. Most approaches in the literature optimize these objectives sequentially (one objecti...

Multi-objective optimization (MO) is a highly demanding research topic because many realworld optimization problems consist of contradictory criteria or objectives. Considering these competing objectives concurrently, a multi-objective optimization problem (MOP) can be formulated as finding the best possible solutions that satisfy these objectives under different tradeoff situations. A family o...