A major risk for many existing and planned wood-based bioenergy facilities is the uncertainty regarding future feedstock supply. Many bioenergy projects use waste generated from primary sectors such as lumber, and, th...
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A major risk for many existing and planned wood-based bioenergy facilities is the uncertainty regarding future feedstock supply. Many bioenergy projects use waste generated from primary sectors such as lumber, and, therefore, carry the inherent risk of supply fluctuations if these industries change. To assess the long-term viability of a wood-based bioenergy facility, it is necessary to understand how biomass feedstock fluctuates with other sectors and at what cost supply can be made available. We address these issues by constructing a positive mathematical programming (PMP) model of the Alberta forest sector that focuses on optimizing fibre transfer routes. Through the use of PMP, we derive a marginal cost function for harvesting and hauling fibre to each processing facility. The results indicate that woody residual supply is quite sensitive to market conditions in the primary sector. For the most part, to support bioenergy expansion, feedstock will need to be sourced from the forest, as very few surplus mill residues are available even at high lumber prices. However, we estimate the marginal cost of delivering harvesting residues to be significant, which suggests that policy support will be needed for further bioenergy development.
This paper presents a novel mathematical programming approach for the static stability analysis of structures with uncertainties within the framework of FEM. The considered uncertain parameters are material properties...
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This paper presents a novel mathematical programming approach for the static stability analysis of structures with uncertainties within the framework of FEM. The considered uncertain parameters are material properties, geometry of element cross section, and loading conditions, all of which are described by an interval model. The proposed method formulates the two cases of interest, namely, worst and best buckling load calculation, into a pair of mathematical programming problems. Two straightforward advantages are exhibited by such formulations. The first advantage is that the proposed formulation can overcome the interference on the sharpness of bounds of the buckling load due to the interval dependence issue. The second benefit is that the information of uncertain parameters causing the extremities of buckling load can always be retrieved as by-products of the uncertain stability analysis. Some numerical examples are presented to illustrate the capability of the proposed method on various structures and the sharpness of the bounds of the buckling load factors. The efficiency and effectiveness of the proposed method are also demonstrated through comparison with the classical Monte Carlo simulation method. Copyright (c) 2014 John Wiley & Sons, Ltd.
Tandem queueing models play an important role in many real world systems such as computer systems, production lines, and service systems. This paper proposes a procedure to construct the membership functions of the pe...
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Tandem queueing models play an important role in many real world systems such as computer systems, production lines, and service systems. This paper proposes a procedure to construct the membership functions of the performance measures in tandem queueing systems, in that the arrival rate and service rates are fuzzy numbers. The basic idea is to transform a fuzzy tandem queue to a family of crisp tandem queues by applying the alpha-cut approach. Then on the basis of alpha-cut representation and the extension principle, a pair of mathematical programs is formulated to describe this family of crisp tandem queues, via which the membership functions of the performance measures are derived. Two numerical examples arc solved successfully to demonstrate the validity of the proposed approach. Since the performance measures are expressed by membership functions rather than by crisp values, the fuzziness of input information is completely conserved. Thus the proposed approach for fuzzy systems can represent the system more accurately, and more information is provided for designing queueing systems. The successful extension of tandem queues to fuzzy environments permits tandem queueing models to have wider applications.
Two different methods for finding the optimal cable profile of tapered low-voltage multibranched distributors are presented. One method is for tapering between nodes assuming a change in cable size can occur anywhere ...
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Two different methods for finding the optimal cable profile of tapered low-voltage multibranched distributors are presented. One method is for tapering between nodes assuming a change in cable size can occur anywhere within a branch, the other is for tapering at nodes where a change in cable size is allowed only from branch to branch. Both can be embedded in a general procedure for designing distribution networks. Also, both cater for interconnectors, existing branches and the cost of losses.
The problem of tuning of stabilizers in multimachine power systems has been formulated both as a quadratic and a linear programming problem. The objective is to shift the lightly damped poles associated to the system ...
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The problem of tuning of stabilizers in multimachine power systems has been formulated both as a quadratic and a linear programming problem. The objective is to shift the lightly damped poles associated to the system mechanical modes. The structure of the transfer function of the stabilizers has been chosen a priori, being the optimization performed with respect to its free coefficients. A usual phase lead characteristic has been included in the constraints. Numerical results are presented for a three-machine power system. (C) 1997 Elsevier Science Ltd.
This work presents a mathematical programming model for the optimal decision making on the supply chain of lithium and lithium compounds in a macroscopic system. The model considers the exploitation of the economicall...
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This work presents a mathematical programming model for the optimal decision making on the supply chain of lithium and lithium compounds in a macroscopic system. The model considers the exploitation of the economically feasible natural sources;it also considers the processing and purification stages as well as the transportation costs needed to satisfy the demand of the several lithium applications, such as Li-ion batteries. Given the significance of circular economy, a discussion on the remanufacturing and recycling of the battery components is also included. Currently, there is no exploitation and production of lithium in Mexico;however, since Mexico is the 7th vehicle manufacturer in the world, information from the potential Lithium deposits in Mexico and its corresponding demands are used to explore the potential and the techno-economic decision making required within such a supply chain.
A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While...
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A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.
Most of the research on cellular manufacturing focuses on cell formation, the initial step of setting up a cellular manufacturing system. Numerous methods exist for organizing efficient manufacturing cells for existin...
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Most of the research on cellular manufacturing focuses on cell formation, the initial step of setting up a cellular manufacturing system. Numerous methods exist for organizing efficient manufacturing cells for existing equipment and parts. However, when cell redesign is not possible or desired, opportunities still exist for further optimization and cost savings with the existing cell formation. Exceptional elements (EEs) in cellular manufacturing are bottleneck machines and exceptional parts that span two or more manufacturing cells. This paper develops a mathematical programming model that retains the original cell formation, which is assumed to be optimal in the long term, and minimizes total costs of a cellular manufacturing system with exceptional elements through (1) intercellular transfer, (2) machine duplication, and (3) subcontracting while taking machine capacities into account to avoid capacity violations. (C) 2014 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
The nonlinear fractional programming problem is considered. The functions involved in the objective function and constraints are assumed to be invex and differentiable. It is shown that the ratio of invex functions is...
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The nonlinear fractional programming problem is considered. The functions involved in the objective function and constraints are assumed to be invex and differentiable. It is shown that the ratio of invex functions is invex. Sufficient optimality and duality theorems art: presented for an invex fractional programming problem. (C) 1997 Academic Press.
In this article, we propose a new solution scheme for modeling elastoplastic problems with stress wave propagation in dissipative media. The scheme is founded on a generalized Hellinger-Reissner (HR) variational princ...
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In this article, we propose a new solution scheme for modeling elastoplastic problems with stress wave propagation in dissipative media. The scheme is founded on a generalized Hellinger-Reissner (HR) variational principle. The principle renders the discretized boundary-value problem into an equivalent second-order cone programming (SOCP) problem that can be resolved in mathematical programming using the advanced optimization algorithm-the interior point method. In such a way, the developed method not only inherits admirable features of the SOCP-based finite element method in solving elastoplastic problems but also enables the enforcement of absorbing layers (i.e., Caughey absorbing layer), which is essential in modeling stress wave propagation problems, to absorb wave energy. The proposed scheme is validated via the comparison between analytical and numerical results for seismic wave propagation in dissipative media. Its application to elastoplastic dynamic problems with stress wave propagation is also illustrated to demonstrate its efficiency.
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