In this paper, we study a resource allocation problem in orthogonal frequency division multiple access (OFDMA)-based Device-to-Device (D2D) communications. To end, propose multi-objective optimization (MOOP) framework, which jointly maximizes the sum rate of D2D users (DUs) and cellular (CUs) uplink communications minimizes total transmit power. The proposed formulation takes into account minim...

Many real projects complete through the realization of one and only one path of various possible network paths. Here, these networks are called alternative stochastic networks (ASNs). It is supposed that the nodes of considered network are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of t...

Multi-objective spatial optimization problems require data input that can contain uncertainties. Via the validation of constraints and computation objective values this uncertainty propagates to Pareto fronts. Here, we develop a method quantify in fronts by finding extreme lower upper bound range optimal space, i.e. interval. The is demonstrated on land use allocation problem with initial (for ...

land use planning is the process of allocating different land uses and activities to the special units of land. so we face with two problems of assigning kind of activity and location of it. by considering the role of industries in development, employment and environment, we consider industrial and especially intensive energy industries planning as a multi objective optimization problem. in thi...

Introduction: To meet ever-increasing demands for health-care services, it is necessary to determine optimal locations for new health-care facilities. Method: A multi-objective model based on the genetic algorithm (GA) has been applied to evaluate site suitability for new clinics in part of Tehran urban areas. A multi-objective GA has been combined with a single GA to solve the location-allocat...

this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive...

this paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequence-dependent setup times that minimizes the weighted mean completion time and the weighted mean tardiness time. for solving this multi-objective model, we develop a fuzzy multi-objective linear programming (fmolp) model. in this problem, a proposed fmolp method is applied with respect to the o...

Ocean sunfish Mola mola are a seasonally common inhabitant of southern Californian waters, and comprise the largest bycatch component (29% of total catch) of the California drift gillnet fishery for swordfish. We used temperature and depth-sensing acoustic transmitters to quantify the fine-scale movement patterns of ocean sunfish near Santa Catalina Island, California. Eight ocean sunfish were ...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...