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Data Envelopment Analysis (DEA) is a nonparametric methodology for estimating technical efficiency of a set of Decision Making Units (DMUs) from a dataset of inputs and outputs. This paper is devoted to computational aspects of DEA models under the application of the Principle of Least Action. This principle guarantees that the efficient closest targets are determined as benchmarks for each assessed...
It is tempting to reuse simulation replications taken during a simulation optimization search as input to a ranking-and-selection procedure, especially when generating replications is computationally expensive. Yet when a search identifies new systems based on the observed performance of explored systems, the resulting search replications are conditionally dependent given the sequence of returned...
We present a Bayesian sequential decision-making formulation of the information filtering problem, in which an algorithm presents items (news articles, scientific papers, tweets) arriving in a stream, and learns relevance from user feedback on presented items. We model user preferences using a Bayesian linear model, similar in spirit to a Bayesian linear bandit. We compute a computational upper bound...
This article studies a two-unit system with failure interactions. The system is subject to two types of shocks (I and II). A type I shock, removed by a minimal repair, causes a minor failure of unit A and type II shock causes a complete system failure that calls for a corrective replacement. Each unit A minor failure also results in a random amount of damage to unit B and such a damage to unit B can...
Operating Vehicle Sharing systems means periodically performing some relocation process, in order to avoid stations becoming either empty or overfilled. We first propose here a static Vehicle Sharing Rebalancing (VSR) framework which unifies preemption and non preemption. Next we present and test a decomposition algorithmic scheme which decomposes our problem into a simple minimum cost assignment...
A transmission topology control (TC) framework for production cost reduction based on a shift factor (SF) representation of line flows is proposed. The framework can model topology changes endogenously while maintaining linearity in the overall Mixed Integer Linear Programming (MILP) formulation of the problem. In large power systems it is standard practice to optimize operations considering few but...
Transportation engineering is one of the most popular area of Operations Research in which fractional programming is used. In this study, we present two algorithms to find initial basic feasible solution of a linear fractional transportation problem. Also we present a methodology to find optimal solution of the stated problem. Using simulation experiments on large number of examples we compare the...
There has been an increasing number of companies moving towards cloud computing due to its economic model based on the so-called pay-as-you-go. The cloud is known as a dynamic and scalable environment. These characteristics make the management of this environment a complex task. Using autonomic management potentially helps to solve the complexity of managing large number of provisioned cloud resources...
With the development of the economy and the expansion of market capacity, companies that launching new types of the services need to conduct enterprise location in the newly developed market to serve the customers. In order to maximize the profit, companies should balance the rent and the customer flow volume, as well as service income and customers' waiting cost, which means that the companies should...
This paper considers a two-stage robotic flow shop scheduling problem. The objective is to minimize the makespan. The problem consists of two dedicated machines at the first stage and one common machine at the second stage. Each job is defined by two operations processed on the two-stages in series. Depending on its type, each job is executed on a dedicated machine at the first stage, then it is transported,...
This study focuses on the single-cycle stock replenishment strategies of perishable merchandise with price reduction, in which the stock shortage is permissible. It proposes a new Economic Order Quantity (EOQ) model, and conducts one numerical example to show the effectiveness of the new EOQ model. Finally, it provides some potential issues for future research.
In this study, a computerized nurse scheduling model is developed. The model is approached through a binary integer programming. It is adapted to ICU in university educational hospital, New Kasr El-Eni in Cairo to improve the current manual-made schedules. The developed model accounts both for hospital objectives and nurses' preferences seniority.
Agent-based modeling is a paradigm that simulates the simultaneous operations and interactions of multiple agents, in an attempt to re-create and predict the appearance of complex phenomena. Its key advantages are that a) it provides the most natural way to model real-world systems and b) it has much more modeling power than traditional mathematical methods such as differential equations as the latter...
The method of non-overlapping batch means is the standard for constructing a confidence interval for the mean of a steady-state simulation output. In “Batch Size Effects in the Analysis of Simulation Output,” published in Operations Research in 1982, Schmeiser recast the problem of selecting a batch size by examining the marginal benefit of attaining the largest number of batches (smallest batch size)...
Shisen-Sho or Four Rivers is a game with perfect information where the objective is to remove all tiles from the board. In this work we present two mixed integer programming models for solving Shisen-Sho game, as well as techniques to improve the formulations proposed. The first mathematical model considers the classical problem of finding a sequence of moves to remove all tiles from the board, while...
An optimization model of integrated forward/reverse logistics network for manufacturer of jiont operations is proposed under uncertain environment, the model can solve location selection of distribution center, recycling center and recycling processing center, and flow allocation between facilities. Then a steps for solving the model was given by transforming the model to certain model. Since such...
Consider the problem of selecting the best simulated system with high probability, from a finite and huge set of alternative systems. The best system might be the one that has the maximum or minimum performance measure. In this paper, we present a sequential method that uses the Ordinal Optimization procedure to select randomly a subset that overlaps with the set of the actual best m% systems with...
Data envelopment analysis (DEA) is a mathematical programming method in Operations Research that can be used to distinguish between efficient and inefficient decision making units (DMUs). However, the conventional DEA models do not have the ability to rank the efficient DMUs. The super-efficiency models in DEA are used for ranking the efficient DMUs. This paper proposes a non-radial super-efficiency...
There has been enormous interest about Covering Location Problem (CLP) among both academicians and practitioners around the world. Applications of CLP range from locating fire stations to telecommunications. This paper deals with a special case of CLP where travel times are fuzzy variables. In addition, it has been assumed that the variable cost of locating facilities is a function of the distance...
Methods of obtaining the distribution functions of errors and the parameters of products after operations of the measurable monitoring. Taken into an account errors of measurements. We discuss the possibility of constructing approximate models, which significantly reduces the complexity of computing.
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