augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...

the set covering problem (scp) is a well-known combinatorial optimization problem. this paper investigates development of a local branching approach for the scp. this solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the mixed integer programming solver. the algorithm parameters are tuned by design of experiments approach. the proposed method is te...

today, online social networks are very popular due to the possibility of creating relationships between people all over the world. these social networks with possibilities such as friend recommendation generally use local features derived from social graph structure. for friend recommendation, there are different algorithms with local and global approaches. in this paper, we proposed an algorit...

A combinatorial auction is an auction where the bidders have the choice to bid on bundles of items. The WDP in combinatorial auctions is the problem of finding winning bids that maximize the auctioneer’s revenue under the constraint that each item can be allocated to at most one bidder. The WDP is known as an NP-hard problem with practical applications like electronic commerce, production manag...

In this work, we extend the existing local fractional Sumudu decomposition method to solve the nonlinear local fractional partial differential equations. Then, we apply this new algorithm to resolve the nonlinear local fractional gas dynamics equation and nonlinear local fractional Klein-Gordon equation, so we get the desired non-differentiable exact solutions. The steps to solve the examples a...

there is a need to analyze and map rainfall erosivity to assess soil erosion at the regional scale. the objectives of this study were to develop a regional model to estimate seasonal erosivity from seasonal rainfall data and to study temporal and spatial distribution of rainfall erosivity for the gorganrood drainage basin in the northeast of iran. six gauging stations with a high temporal resol...

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, rand...

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...

there is a need to analyze and map rainfall erosivity to assess soil erosion at the regional scale. the objectives of this study were to develop a regional model to estimate seasonal erosivity from seasonal rainfall data and to study temporal and spatial distribution of rainfall erosivity for the gorganrood drainage basin in the northeast of iran. six gauging stations with a high temporal reso...