The aim of the paper is to present sequential methods for a pseudoconvex optimization problem whose objective function is the sum of a linear and a linear fractional function and the feasible region is a polyhedron, not necessarily compact. Since the sum of a linear and a linear fractional function is not in general pseudoconvex, we first derive conditions characterizing its pseudoconvexity on ...

Quadratic elements place stringent requirements on a surface mesh smoother. One of the biggest challenges is that a good linear element may become invalid when mid-side nodes are introduced. To help alleviate this problem, a new objective function for optimization-based smoothing is proposed for triangular and quadrilateral elements, linear or quadratic. Unlike the current popular approaches, t...

In this paper, we develop an intuitionistic fuzzy optimization approach using non-linear membership and non-membership function for optimizing multi objective structural model. In this optimum design formulation, the objective functions are the weight of the truss and the deflection of loaded joint; the design variables are the crosssections of the truss members; the constraints are the stresse...

Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model considers minimization of supply chain costs while the second objective function minimizes CO...

Abstract Linear proportional solenoid (LPS) is widely applied in different linear motion control systems as the electromagnetic actuator since its high reliability and low cost. LPS difficult to optimize by changing a single variable due amounts of structural design parameters, each parameter has nonlinear relationship with static force. This paper aims improve LPS’s push force response perform...

Inverse optimization perturbs objective function to make an initial feasible solution optimal with respect to perturbed objective function while minimizing cost of perturbation. We extend inverse optimization to two-stage stochastic linear programs. Since the resulting model grows with number of scenarios, we present two decomposition approaches for solving these problems.

In this paper, we present a general framework for designing approximation schemes for combinatorial optimization problems in which the objective function is a combination of more than one function. Examples of such problems include those in which the objective function is a product or ratio of two linear functions, parallel machine scheduling problems with the makespan objective, robust version...

Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors, and other human environments. Human society has social norms that people mutually accept; obeying these is an essential signal someone participating socially with respect to the rest of population. For be compatible humans, it crucial for obey norms. In prior work, we demonstrated a Socially-Aware Naviga...

1. Abstract While various multiobjective optimization methods based on metaheuristic techniques have been proposed, these methods still encounter difficulties when handling many variables, or numerous objectives and constraints. This paper proposes a new aggregative gradient-based multiobjective optimization method for obtaining a Pareto-optimal solution set. In this method, the objective funct...