In recent years stock exchange has become one of the most attractive and growing businesses in respect of investment and profitability. But applying a scientific approach in this field is really troublesome because of variety and complexity of decision making factors in the field. This paper tries to deliver a new solution for portfolio selection based on multi criteria decision making literatu...

This article proposes the concept of digital heuristics to model and explain political communication strategies in complex environment hybrid media systems. Insights from recent psychological research on heuristic decision-making are combined with literature current structural context features online order make case for a heuristics-oriented approach strategies. I argue that despite growing imp...

We present a state-of-the-art survey of parallel meta-heuristic strategies, developments, and results. We discuss general design and implementation principles that apply to most metaheuristic classes and instantiate these principles for neighborhood and population-based metaheuristics. We also identify a number of trends and promising research directions.

To handle a large amount of unlabeled data, batch active learning (BAL) queries humans for the labels most valuable data points at every round. Most current BAL strategies are based on human-designed heuristics, such as uncertainty sampling or mutual information maximization. However, there exists disagreement between these heuristics and ultimate goal BAL, i.e., optimizing model's final perfor...

Nowadays, one of the major goals of the distribution environment is to reduce lead times and inventories. Cross-docking is a logistics technique which removes the storage and picking up the functions of a warehouse. The term cross-docking refers to moving products directly from incoming to outgoing trailers with little or no storage in between. According to the recent related papers, the truck ...

As exact algorithms are unfeasible to solve real optimization problems, due their computational complexity, meta-heuristics usually used them. However, choosing a meta-heuristic particular problem is non-trivial task, and often requires time-consuming trial error process. Hyper-heuristics, which heuristics choose heuristics, have been proposed as means both simplify improve algorithm selection ...

In previous work, we developed a single Evolutionary Algorithm (EA) to solve random instances of the Anshel-Anshel-Goldfeld (AAG) key exchange protocol over polycyclic groups. The EA consisted six simple heuristics which manipulated strings. present work extends this by exploring use hyper-heuristics in group-theoretic cryptology for first time. Hyper-heuristics are way generate new algorithms ...

In this paper, a set of heuristics for evaluating the usability of mobile map applications is introduced. We developed the heuristics by exploring the present generic heuristics and then forming new theory-based heuristics. Usability specialists tested the heuristics by evaluating the usability of a mobile map application with both generic and domain-specific heuristics. As a result, more usabi...

in this paper the conditional location problem is discussed. conditional location problems have a wide range of applications in location science. a new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are compared to those of the previous studies. this algorithm produces much better results than the previous formulations.