Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It uses Bayesian methods to sample the objective efficiently using an acquisition function which incorporates the posterior...

Background: The construction of metro lines is a high-risk project. Using a budget-based model for the safety units of metro construction projects can help safety managers to spend optimal budget allocation. The purpose of this study was to plan a budget model based on safety unit performance in an under construction metro station for better budget allocation using robust optimization. Methods...

One of the problems that sometimes occur in gas allocation optimization is instability phenomenon. This phenomenon reduces the oil production and damages downhole and surface facilities. Different works have studied the stability and suggested some solutions to override it, but most of them (such as making the well intelligent) are very expensive and thus they are not applicable to many cases. ...

This paper proposes Market-based Iterative Risk Allocation (MIRA), a new market-based decentralized optimization algorithm for multiagent systems under stochastic uncertainty, with a focus on problems with continuous action and state space. In large coordination problems, from power grid management to multi-vehicle missions, multiple agents act collectively in order to maximize the performance ...

In this paper, we consider the problem of pricing for optimal resource allocation service using Engineering Optimization with Particle Swarm algorithm that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. We formulate our generalized optimization algorithm based on the notion of a “profit center” with an arbitrar...

We present a novel datapath allocation method. Key features of this method are its exibility to handle accurate modeling of datapath units, use of direct objective functions, and the simultaneous optimization of all objective functions. The proposed method consists of a new binding model construction scheme and an optimization technique based on simulated annealing. Two new datapath allocation ...

Container handling problems at container terminals are NP-hard problems. This paper presents an approach using discrete-event simulation modeling to optimize solution for storage space allocation problem, taking into account all various interrelated container terminal handling activities. The proposed approach is applied on a real case study data of container terminal at Alexandria port. The co...

Large costs arise at a seaport container terminal from the duration of the unloading of vessels and from the time a vessel is waiting to be unloaded. The optimal allocation of vessels to berth space (Berth Allocation Problem) becomes more and more important as its solution is also input to further terminal decision problems. We compare solutions for a realistic data Berth Allocation Problem fou...

A class of multicarrier systems was deened in 1] to study the eeect of the method of bandwidth allocation on coherent multiuser system performance over fading channels. In this paper, we extend our previous work to a military environment, where the system experiences some type of hostile jamming in addition to additive white Gaussian noise (AWGN). Using a novel closed form result for the error ...

Mutual cooperation in Multi-Agent Systems is an important means to implement complex applications. The static task allocation is one of the key issues in agent cooperation mechanism. The latency of the network infrastructure, dynamic topology and node heterogeneity are important features of the agent system, and they bring new challenges to the static task allocation in multi-agent environment....