In this paper, a systematic approach is presented for optimal design of tunnel support lining using two-dimensional finite element analysis models of soil-structure interaction developed in ABAQUS software and the Modified Colliding Bodies Optimization (MCBO) algorithm implemented in MATLAB environment. This approach is then employed to study the influence of variable geometrical and geo-mechan...

The energy efficiency of future networks is becoming a significant and urgent issue, calling for greener network designs. At the same time, rapid development of wireless networks shows a trend of increasing complexity in network structure and resource space, leading to that optimizing the energy efficiency of such networks requires a joint solution over multi-dimensional resource space. However...

This work develops a novel two-stage fuzzy optimization method for solving the multiproduct multi-period (MPMP) production planning problem, in which the market demands and some of the inventory costs are assumed to be uncertainty and characterized by fuzzy variables with known possibility distributions. Some basic properties about the MPMP production planning problem are discussed. Since the f...

In the probabilistic two-dimensional Bin Packing problem (2D-PBPP), one is asked to pack a random number of rectangular items, without overlap and any rotation, into the minimum number of identical square bins. In this paper we consider the re-optimization procedure used for solving probabilistic combinatorial optimization problems and an approximation of this strategy: the redistribution strat...

In this paper, an interesting and easy method to solve the multi-dimensional  knapsack problem is presented. Although it belongs to the combinatorial optimization, but the proposed method belongs to the decision making field in mathematics. In order to, initially efficiency values for every item is calculated then items are ranked by using Multiple Criteria Decision Making (MCDA).  Finally, ite...

In this paper, a new simplified version of the Bayesian Approach to coordinate global optimization (BAcoor) is compared with the well-known algorithms. BAcoor is a method of multi-dimensional optimization by applying a sequence of one-dimensional global optimizers starting from the best points obtained by previous one-dimensional optimization. The globality of one-dimension search is controlled...

The number of heuristic optimization algorithms has exploded over the last decade with new methods being proposed constantly. A recent overview of existing heuristic methods has listed over 130 algorithms. The majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claiming to be superior to other methods in terms of ...