An invigilator is a person who supervises students during examinations in educational systems. Assigning invigilators to exams is an important phase in the exam scheduling process. The problem has its own constraints and a multi-objective structure. Hardly any mathematical models have been used in the past. Mostly, heuristic approaches are used to assign invigilators to exams. The Analytic Netw...

Multi-objective optimization is a class of problems with solutions that can be evaluated along two or more incomparable or conflicting objectives. These types of problems differ from standard optimization problems in that the end result is not a single “best solution” but rather a set of alternatives, where for each member of the set, no other solution is completely better (the Pareto set). Mul...

We introduce a new multi-objective optimization (MOO) methodology based the splitting technique for rare-event simulation. The method generalizes the elite set selection of the traditional splitting framework, and uses both local and global sampling to sample in the decision space. In addition, an ε-dominance method is employed to maintain good solutions. The algorithm was compared with state-o...

In this paper, application of a multi-objective evolutionary algorithms is explored for solving multi-objective placement, packing, or layout problems. Placement problems are optimization problems concerned with finding an optimal arrangement of multiple items in a large containing region while satisfying prescribed requirements and constraints. This study is applied to the configuration design...

in this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. two objective functions, real power loss and energy not supplied index (ens), were utilized. multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

In present study, a three-step multi-objective optimization algorithm of cyclone separators is catered for the design objectives. First, the pressure drop (Dp) and collection efficiency (h) in a set of cyclone separators are numerically evaluated. Secondly, two meta models based on the evolved Group Method of Data Handling (GMDH) type neural networks are regarded to model the Dp and h as the re...

Problems dealing with the design and the operations of gas transmission networks are challenging. The difficulty mainly arises from the simultaneous modeling of gas transmission laws and of the investment costs. The combination of the two yields a nonlinear non-convex optimization problem. To obviate this shortcoming, we propose a new formulation as a multi-objective problem, with two objective...

We model document summarization as a nonlinear 0-1 programming problem where an objective function is defined as Heronian mean of the objective functions enforcing the coverage and diversity. The proposed model implemented on a multi-document summarization task. Experiments on DUC2001 and DUC2002 datasets showed that the proposed model outperforms the other summarization methods. Index Terms – ...