This work presents a method for optimum design of structures, where the design variables can he considered as Continuous or discrete. The variables are chosen as sizing variables as well as coordinates of joints. The main idea is to reduce the number of structural analyses and the overal cost of optimization. In each design cycle, first the structural response quantities such as forces, displac...

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimiza...

time-dependent vehicle routing problem is one of the most applicable but least-studied variants of routing and scheduling problems. in this paper, a novel mathematical formulation of time-dependent vehicle routing problems with heterogeneous fleet, hard time widows and multiple depots, is proposed. to deal with the traffic congestions, we also considered that the vehicles are not forced to come...

Different methods are available for simultaneous optimization of cross-section, topology and geometry of truss structures. Since the search space for this problem is very large, the probability of falling in local optimum is considerably high. On the other hand, different types of design variables (continuous and discrete) lead to some difficulties in the process of optimization. In this articl...

a real-time optimization (rto) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. furthermore, the objective function is penalized by a fuzzified form of the key process constraints. to enable using conventional optimization techniques, the resulting fuzzy optimization problem is then re...

In this paper, the novel Distributed Bayesian (D-Bay) algorithm is presented for solving multi-agent problems within Continuous Constraint Optimization Problem (C-DCOP) framework. This framework extends classical DCOP towards utility functions with continuous domains. D-Bay solves a C-DCOP by utilizing optimization adaptive sampling of variables. We theoretically show that converges to global o...

We give explicit solutions for utility optimization problems in the presence of Knightian uncertainty in continuous time. We solve the robust optimization problem explicitly both when the investor’s utility is of CRRA and of CARA type. We show that our problem formulation allows us to apply Sion’s min max theorem and to solve the dual problem explicitly. Mathematics Subject Classification: 91B2...