This paper focuses on supplier-related decisions in a newsvendor setting. We build upon the current literature by analysing the newsvendor problem with multiple unreliable and non-identical suppliers. We also incorpor...
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This paper focuses on supplier-related decisions in a newsvendor setting. We build upon the current literature by analysing the newsvendor problem with multiple unreliable and non-identical suppliers. We also incorporate both fixed ordering costs and capacity limits for supplier selection. We develop an exact algorithm to solve the problem optimally and a heuristic algorithm to solve the problem efficiently. Through structural properties of the optimal solution and a numerical study, we provide useful managerial implications regarding optimal sourcing strategies in complex supply chains. Previous literature concludes that with multiple unreliable (independent) suppliers, cost is the order qualifier and reliability is the order winner. We found that when fixed ordering costs and supply capacities exist, this insight no longer holds. We also examine the sensitivity of the sourcing decisions to supplier capacity levels, demand uncertainty, salvage value and shortage cost. Our results show that high levels of demand uncertainty lead firms to turn to a single-sourcing strategy whereas high salvage values and high shortage cost suggest multi-sourcing strategy.
The increasing integration of larger amounts of wind energy into power systems raises important operational issues, such as the balance between power generation and demand. The pumped storage hydro (PSH) units are one...
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The increasing integration of larger amounts of wind energy into power systems raises important operational issues, such as the balance between power generation and demand. The pumped storage hydro (PSH) units are one possible solution to mitigate this problem, once they can store the excess of energy in the periods of higher generation and lower demand. However, the behavior of a PSH unit may differ considerably from the expected in terms of wind power integration when it operates in a liberalized electricity market under a price-maker context. In this regard, this paper models and computes the optimal PSH weekly scheduling in a price-taker and price-maker scenarios, either when the PSH unit operates in standalone and integrated in a portfolio of other generation assets. Results show that the price-maker standalone PSH will integrate less wind power in comparison with the price-taker situation. Moreover, when the PSH unit is integrated in a portfolio with a base load power plant, the role of the price elasticity of demand may completely change the operational profile of the PSH unit. (C) 2014 Elsevier Ltd. All rights reserved.
Complex web applications are usually served by multi-tier web clusters. With the growing cost of energy, the importance of reducing power consumption in server systems is now well-known and has become a major research...
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Complex web applications are usually served by multi-tier web clusters. With the growing cost of energy, the importance of reducing power consumption in server systems is now well-known and has become a major research topic. However, most existing research focused solely on homogeneous clusters. This paper addresses the challenge of power management in Heterogeneous Multi-tier Web Clusters. We apply Generalized Benders Decomposition (GBD) to decompose the global optimization problem into small sub-problems. This algorithm achieves the optimal solution in an iterative fashion. The evaluation results show that our algorithm achieves more energy conservation than the previous work. (C) 2013 Elsevier Inc. All rights reserved.
A systematic core design method is developed to design Gd-bearing fuel assembly having two types of Gd rods, low-wt%-Gd rod and high-wt%-Gd rod. The purpose of the method is to lower the critical boron concentration (...
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A systematic core design method is developed to design Gd-bearing fuel assembly having two types of Gd rods, low-wt%-Gd rod and high-wt%-Gd rod. The purpose of the method is to lower the critical boron concentration (CBC) of a preliminary core loading pattern, and consequently to achieve more negative or less positive moderator temperature coefficient (MTC). The proposed core design method is a process of solving a non-linear programming problem stated with a system of equations. In this method, both the ratio of the number of low-wt%-Gd rod to the number of high-wt%-Gd rod (r) and the assembly average Gd wt% (w) are the solution variables of the system of equations. The target function is the amount of soluble boron concentration reduction, Delta CBC, which is correlated with the reactivity change, Delta k(FA), per Gd-bearing fuel assembly by a quadratic reactivity equation. The coefficients of the quadratic equations are calculated prior to the determination of Gd-bearing fuel assembly pattern, using the least square method. The constraints required to determine (r, w) are physically realizable Gd rods pattern, Delta k(i) close to Delta k(FA) derived from Delta CBC, etc. An objective function, min [f(Sigma(i)(Delta k(FA) - Delta k(i)))], enables a final loading pattern to reach a target CBC. This design methodology is applied to APR 1400. Total six cases with various target CBCs are investigated to validate the proposed method. CASMO-3/MASTER calculations with new design assemblies produce lower CBCs at BOC than target CBCs keeping maximum pin power below the safety limit, and thus show more negative MTC. (C) 2014 Elsevier Ltd. All rights reserved.
In this paper we study the problem of locating a new station on an existing rail corridor and a new junction on an existing road network, and connecting them with a new road segment under a budget constraint. We consi...
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In this paper we study the problem of locating a new station on an existing rail corridor and a new junction on an existing road network, and connecting them with a new road segment under a budget constraint. We consider three objective functions and the corresponding optimization problems, which are modeled by means of mixed integer non-linear programs. For small instances, the models can be solved directly by a standard solver. For large instances, an enumerative algorithm based on a discretization of the problem is proposed. Computational experiments show that the latter approach yields high quality solutions within short computing times. (C) 2014 Elsevier Ltd. All rights reserved.
This research presents a method for convexifying the non-linear constraints and the objective function for the Transmission Network Expansion Planning Problem (TNEP). The TNEP seeks to identify the best set of transmi...
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This research presents a method for convexifying the non-linear constraints and the objective function for the Transmission Network Expansion Planning Problem (TNEP). The TNEP seeks to identify the best set of transmission capacity additions to meet a future electric power demand. The TNEP is a non-convex Mixed Integer non-linear programming problem for which a variety of primal solution methods have been designed. In this paper, the TNEP is formulated as a bilinearprogramming problem subject to bilinear constraints. This allows resolving the non-linearities through convexification of the non-linear objective function and the constraints for a relaxation of the TNEP in which integrality requirements are removed. The final solution for the original TNEP problem is obtained by using a branch and bound strategy. It was found by using a two-node test case that the convexification method presented in this paper in conjunction with a brand and bound strategy identifies the optimal solution. Successfully solving a small-scale test problem through convexification presents a promising scenario to solve larger scale problems. This primal-dual method allows identifying the duality gap which is a limitation of primal methods. Further multidisciplinary research is needed to extend the method presented here to larger cases and real life networks. Copyright (c) 2013 John Wiley & Sons, Ltd.
An Economic Lot Scheduling Problem is considered under the condition that the production process may shift from an in-control state to an out-of-control state due to the deterioration of the facility's key module....
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An Economic Lot Scheduling Problem is considered under the condition that the production process may shift from an in-control state to an out-of-control state due to the deterioration of the facility's key module. We adopt the Common Cycle policy in two mathematical models depending on whether the key module is repairable or not. Several standby modules are available during a production run. For the model with non-repairable key modules, the active key module, once deteriorated, is disposed of and replaced by a new standby. For the model with repairable key modules, the active one is replaced by a standby as soon as it is deteriorated. The failing module will be restored in a repair shop and rejoin the standbys. The objective is to determine an optimal production cycle time and the economic number of standby modules in order to minimise the long-term average cost including set-up, inventory carrying, standby and defective costs. The convexity of the cost functions is revealed so that efficient algorithms can be developed accordingly to achieve optimal production-inventory policies. It is shown that these policies can be used to significantly improve the system performance.
We study the following discrete facility location game. Two players, a leader and a follower, open facilities and compete to attract clients from a given market. Each player has a budget and maximizes own market share...
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ISBN:
(纸本)9781509002016
We study the following discrete facility location game. Two players, a leader and a follower, open facilities and compete to attract clients from a given market. Each player has a budget and maximizes own market share. Each client splits own demand probabilistically over all opened facilities by the gravity rule. The goal is to find the location and design of the leader facilities to maximize his market share. We present an alternating heuristic and exact method for this game. We rewrite the problem as mixed integer linear program with exponential number of constraints. In our method, we start with small subset of constraints and iteratively enlarge it until upper and lower bounds not coincide. Computational results are discussed.
Existing decision making methodologies like the Analytic Hierarchy Process (AHP) address imprecise pairwise comparisons by modeling crisp pairwise comparisons as fuzzy sets or a single type of probability distribution...
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Existing decision making methodologies like the Analytic Hierarchy Process (AHP) address imprecise pairwise comparisons by modeling crisp pairwise comparisons as fuzzy sets or a single type of probability distribution (e.g., uniform, triangular). However, one common issue faced by decision makers (DMs) is bounded rationality. That is, DMs have limited cognitive powers in specifying their preferences over multiple pairwise comparisons. This result to crisp as well as imprecise pairwise comparisons. Furthermore, given the ultimate goal of imprecise AHP is to make the decision, computing weights for the criteria and the alternatives from the imprecise preferences is a must. Hence, these various types of pairwise comparisons must be modeled using a single probability distribution for easy computation of the weights. In this research, a beta distribution is proposed to model the varying stochastic preferences of the DM. The method-of-moments methodology is used to fit the varying stochastic preferences of the DM into beta stochastic pairwise comparisons since it can represent a wide variety of probability distributions. Additionally, a non-linear programming model is then developed that calculates weights which maximize the preferences of the DM while maintaining a level of consistency. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology. Published by Elsevier Inc.
In this paper, a new method is presented in optimization of hydrogen network. The mixed integer non-linear programming (MINLP) and non-linear programming (NLP) problems have been solved with two methods, simultaneousl...
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In this paper, a new method is presented in optimization of hydrogen network. The mixed integer non-linear programming (MINLP) and non-linear programming (NLP) problems have been solved with two methods, simultaneously. The linearization technique for non-linear programming models which proposed by McCormick (1976) and also a new method proposed by Faria and Bagajewicz (2011) have been used to solve these problems. Application of this new method is presented in global optimization of MINLP/NLP, and hydrogen network problem. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
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