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A collaborative supply chain seeks to coordinate its members to produce and distribute products along the chain for minimum overall costs to satisfy customer demand. An integrated multi-period, multi-product and multi-stage supply chain model is developed. A collaborative supply chain grid (CSCG) system gathers necessary information on operations and resources from members of the supply chain. It then guides the members on ordering decisions for a minimum overall cost, while continuously re-directing them as new data becomes available. An actual CSCG system has been implemented in a collaborative auto industry with diverse and dynamic membership, yielding an approximately 26% reduction in... 

Wireless Sensor Networks are composed of small, low cost, resource-constrained computing nodes equipped with low power wireless transceivers. In this paper, we study and model the time and energy cost of Kerberos protocol by using timed automata in WSN. We model check the protocol using UPPAAL. We show that considering time in the analysis of security protocols yield more confident results  

Recently, for zero ordering cost a new ordering policy named (1, T), in which the time interval between two consecutive orders and the value of the order size are both constant, have been developed for nonperishable products. In this paper, the (1, T) policy is developed for perishable products. Using an analogy among this inventory model, a queueing model with impatient customers, and a finite dam model, the long-run average total cost function of the inventory system is derived. It is observed that the total cost rate is independent from the lead time as is for nonperishable products. Since analyzing the convexity of the model is extremely complicated, a proposition is proved to define a... 

Time-cost trade-off problems (TCT) are well-known in project management contents. This approach normally applied for scheduling of a project especially where the project should be completed under pre-determined deadline. This paper aims to extend time-cost trade-off (TCT) problems in order to provide a well-organized mechanism for both scheduling and rescheduling processes of a project. The proposed mechanism includes project scheduling which concerns with the TCT problem, monitoring of project performance during execution phase using earned value management (EVM), and also predicting project future performance through statistical modeling. Once the predicted values of project performance... 

Nowadays, analyzing large amount of data is of paramount importance for many companies. Big data and business intelligence applications are facilitated by the MapReduce programming model while, at infrastructural layer, cloud computing provides flexible and cost effective solutions for allocating on demand large clusters. Capacity allocation in such systems is a key challenge to providing performance for MapReduce jobs and minimize cloud resource cost. The contribution of this paper is twofold: (i) we formulate a linear programming model able to minimize cloud resources cost and job rejection penalties for the execution of jobs of multiple classes with (soft) deadline guarantees, (ii) we... 

A cooperative supply chain seeks to coordinate its members to produce and distribute products along the chain, for minimum overall costs to satisfy customer demand. An integrated multi-period, multiple product and multiple stage supply chain is formulated using a flow networks framework. A Cooperative Supply Chain Optimizer (CSCO), as a central software entity taking advantage of Grid technology, connects and gathers necessary operational information from members of the corporate supply chain. The CSCO then guides supply chain members on ordering decisions, for a minimum overall cost of the entire supply chain, while continuously re-directing the members as new data becomes available. The... 

This research proposes a new method for optimisation of a power generation system based on exergy fuel cost and external social cost of air pollution. A thermodynamic model is provided to estimate the outlet mass flow rates of CO2, CO, NO and NO2 for a gas turbine based on maximising the first and second law efficiencies and minimising the objective function. Results show that inclusion of the external social cost of air pollution increases the optimum excess air ratio if temperature constraint due to metallurgical consideration is disregarded. Otherwise external social cost of air pollution is independent of optimised conditions  

We consider the design of an optimal natural-gas network. Our proposed network contains two echelons, Town Broad Stations (TBSs), and consumers (demand zones). Here, our aim is a two-stage cost minimization. We first determine locations of the TBS so that the location-allocation cost is minimized. Then, we show how to distribute the flow of gas among the TBS minimizing the flow cost by using Minimum Spanning Tree (MST). A case study in Mazandaran Gas Company in Iran is made to assess the validity and effectiveness of our proposed model  

This research deals with a model with better efficiency for selection of portfolio making use of cardinal constraints, which are explained in previous sections. Such a method, which is a combination of fuzzy models and MCDM considering the constraints intended by investors, has not been used in previous models. We have considered transactions cost, because they are among factors important for an investor, and their being ignored in a portfolio selection method will result in inefficient portfolio. Sector value constraint is among other constraints considered here. Such a constraint aims to raise investment rate in sectors with higher values. Cardinal constraints (number of shares existing in... 

In this work, steady state and dynamic performances of quaternary distillation column sequences designed based on steady state and dynamic cost functions have been investigated. To quantify the dynamic performance, product losses due to disturbances have been considered in the objective function. In addition, variations of operating costs such as utilities have been considered in the objective function. To separate a quaternary mixture into four products, 22 configurations have been used. It has been observed that the feed composition, disturbance frequency and magnitude affect the dynamic behavior strongly. To decrease the optimization computational load, a scheme that provides a suboptimal... 

A holding or a multi-business corporate seeks to coordinate its supply for minimum overall costs. A Corporate Supply Optimizer (CSO), as a central entity taking advantage, of the notion of flow networks, gathers necessary operational information from members of the corporate supply chain. The CSO then guides supply chain members on ordering decisions for a minimum overall cost for the entire supply chain. Its computational engine models the entire supply chain with multiple members in four stages to satisfy customer demand. The CSO seeks a solution with minimum total costs, unlike noncooperative supply chains where individual members compete, to optimize, their local costs. The existing... 

In this paper, Bat Algorithm is proposed to solve the Optimal Power Flow (OPF) problem. The approach employs a Meta heuristic optimization algorithm called bat optimization algorithm to determine the optimal settings of control variables of OPF problem. The performance of proposed method examined on the IEEE 9, 14, 30 and 57-buses test systems with fuel cost minimization as the objective function. The numerical results are compared to those of Particle Swarm Optimization (PSO), Harmony Search (HS) and Cuckoo algorithms. Simulation results obtained from the proposed approach demonstrate that this method provide effective and robust high-quality answer for the OPF problem. © 2016 IEEE  

A redundancy allocation problem consists of the selection of a number of redundancies to be allocated in each subsystem of a series-parallel configuration to maximize system reliability, while minimizing overall system cost. Most existing studies either ignore system cost or assume deterministic component reliabilities. However, the selection of a network system design requires the estimation of its reliability and cost. Therefore, the uncertainty associated with such estimates must be considered in the decision process. In this study, an efficient method based on the loss function approach is proposed to solve the redundancy allocation problem. This approach not only optimizes the overall... 

Home energy management (HEM) schemes persuade residential customers to actively participate in price-based demand response (DR) programs. In these price-based HEM methods, a controller schedules the energy consumption of household's controllable appliances in response to electricity price signals, considering various customer preferences. Although numerous methods have been recently proposed for HEM application, prioritizing the operation of controllable appliances from the customer's viewpoint in price-based HEM has not been addressed, which is the focus of the present paper. To do this, the value of lost load (VOLL) of each appliance is defined to indicate the operational priority of that... 

This paper deals with a two-echelon inventory system consisting of onesupplier and N retailers. Each retailer faces an independent Poisson demand withthe same rate and applies a new ordering policy called one-for-one- periodordering policy for its inventory control. In this ordering policy the ordersize is equal to one and the time interval between any two consecutive ordersforms a common fixed cycle. Thus, the supplier faces a deterministic demand andadopts a deterministic inventory policy. At each cycle he orders a batch of sizeN to his own supplier. Upon receipt of each batch he sends 1 unit of theproduct to each retailer with a transportation cost. In this paper, for theabove system we... 

Three-dimensional thermo-hydrodynamic analysis of gas turbine combustion chambers is of great importance in the power generation industry to achieve higher efficiency and reduced emissions. However, it is prohibitive to use a comprehensive full-detailed mechanism in their simulation algorithms because of the huge CPU time and memory space requirements. Many reduction approaches are available in the literature to remedy this problem. Here a new approach is presented to reduce large detailed or skeletal mechanisms of oxidation of hydrocarbon fuels to a low-cost skeletal mechanism. The method involves an integrated procedure including a Sensitivity Analysis (SA) and a procedure of Gradual... 

This study presents a framework that utilizes Bayesian regression to create probabilistic cost models for retrofit actions. Performance improvement is the key parameter introduced in the proposed framework. The incorporation of this novel feature facilitates the characterization of retrofit cost as a continuous function of the desired performance improvement. Accounting for the performance gained from retrofit enables the use of the models in determining the optimal level of retrofit. Furthermore, accounting for the model uncertainty facilitates the use of the models in risk and reliability analyses. The proposed framework is applied to create seismic retrofit cost models for masonry school... 

Nowadays, we live in a Big Data world and many sectors of our economy are guided by data-driven decision processes. Big Data and Business Intelligence applications are facilitated by the MapReduce programming model, while, at infrastructural layer, cloud computing provides flexible and cost-effective solutions to provide on-demand large clusters. Capacity allocation in such systems, meant as the problem of providing computational power to support concurrent MapReduce applications in a cost-effective fashion, represents a challenge of paramount importance. In this paper we lay the foundation for a solution implementing admission control and capacity allocation for MapReduce jobs with a priori... 

Cost optimization for workflow scheduling while meeting deadline is one of the fundamental problems in utility computing. In this paper, a two-phase cost-efficient scheduling algorithm called critical chain is presented. The proposed algorithm uses the concept of slack time in both phases. The first phase is deadline distribution over all tasks existing in the workflow which is done considering critical path properties of workflow graphs. Critical chain uses slack time to iteratively select most critical sequence of tasks and then assigns sub-deadlines to those tasks. In the second phase named mapping step, it tries to allocate a server to each task considering task's sub-deadline. In the... 

We propose a novel way of spreading data over multiple servers in Content Delivery Networks. Such approach provides a framework to explore trade-off between three key parameters of a content delivery network; namely, delay, storage size and communication cost. After presenting proper models for such trade-off, fundamental limits and lower and upper bounds on parameters of interest are provided for basic one-and two-dimensional spatial server arrangements. The observation that both delay and storage size can be reduced at the expense of moderate communication cost can be of great importance in a number of practical scenarios of interest. © 2018 IEEE