Container ports have been faced under increasing development during last 10 years. In such systems, the container transportation system has the most important effect on the total system. Therefore, there is a continuous need for the optimal use of equipment and facilities in the ports. Regarding the several complicated structure and activities in container ports, this paper evaluates and compar...

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continu...

This paper deals with discrete-event simulation based on optimization of a catchment basin management. The integration of optimization techniques into modeling and simulation relies on the evolution of the studied model using decisions based on previous simulation results. Three different categories of optimization via simulationmethods can be found in the literature: rank-and-selection methods...

a simulation-based optimization approach for the purpose of finding a near-optimal answer can be efficient and effective. In the present paper, first, the mathematical model for the project activity scheduling problem has been presented with a job shop approach. Then, using the Arena 14 software, the simulation model has been designed. Consequently, a numerical example has been solved via runni...

Building performance simulation is being increasingly deployed beyond the building design phase to support efficient building operation. Specifically, the predictive feature of the simulation-assisted building systems control strategy provides distinct advantages in view of building systems with high latency and inertia. Such advantages can be exploited only if model predictions can be relied u...

Simulation optimization (SO) is the process of finding the best set of input variable values without explicitly evaluating each feasible set of these input variable values given an output criterion (Law, 2007; Fu, 1994). Input variables are called (controllable) inputs, parameter settings, values, variables, (proposed) solutions, designs, configurations, or factors (in design of experiments ter...

We review techniques for optimizing stochastic discrete-event systems via simulation. We discuss both the discrete parameter case and the continuous parameter case, but concentrate on the latter which has dominated most of the recent research in the area. For the discrete parameter case, we focus on the techniques for optimization from a finite set: multiple-comparison procedures and ranking-an...