A mixed-integer linear programming model is proposed for the selection of technology routes for fruit and vegetable crops between harvest and market. The objective is to optimize capital investment in food preservatio...
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A mixed-integer linear programming model is proposed for the selection of technology routes for fruit and vegetable crops between harvest and market. The objective is to optimize capital investment in food preservation facilities under uncertainties? based on alternative routes and a set of crop and market scenarios. A case-study illustrates the application of the model.
This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as mixed logical dynamical (MLD) systems. These are descr...
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This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as mixed logical dynamical (MLD) systems. These are described by linear dynamic equations subject to linear inequalities involving real and integer variables. MLD systems include linear hybrid systems, finite state machines, some classes of discrete event systems, constrained linear systems, and nonlinear systems which can be approximated by piecewise linear functions. A predictive control scheme is proposed which is able to stabilize MLD systems on desired reference trajectories while fulfilling operating constraints, and possibly take into account previous qualitative knowledge in the form of heuristic rules. Due to the presence of integer variables, the resulting on-line optimization procedures are solved through mixedinteger quadratic programming (MIQP), for which efficient solvers have been recently developed. Some examples and a simulation case study on a complex gas supply system are reported. (C) 1999 Elsevier Science Ltd. All rights reserved.
Recoverable product environments are becoming an increasingly important segment of the overall push in industry towards environmentally conscious manufacturing. Integral to the recoverable product environment is the r...
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Recoverable product environments are becoming an increasingly important segment of the overall push in industry towards environmentally conscious manufacturing. Integral to the recoverable product environment is the recoverable manufacturing system that focuses on recovering the product and extending its life through remanufacture or repair. Remanufacturing provides the customer with an opportunity to acquire a product that meets the original product standards at a lower price than a new product. The flow of materials and products in this environment occurs both from the customer to the remanufacturer (reverse flow), and from the remanufacturer to the customer (forward flow). Since most of the products and materials may be conserved, essentially this forms a closed-loop logistics system. We present a 0-1 mixedintegerprogramming model that simultaneously solves for the location of remanufacturing/distribution facilities, the transshipment, production, and stocking of the optimal quantities of remanufactured products and cores. We also discuss the managerial uses of the model for logistics decision-making.
This paper presents a sophisticated mixed-integer linear programming model developed to help regional decision-makers in the longterm planning of solid waste management activities. The model removes practically all th...
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This paper presents a sophisticated mixed-integer linear programming model developed to help regional decision-makers in the longterm planning of solid waste management activities. The model removes practically all the limitations of earlier integrated waste management models. All the features and capabilities of the tool are described in technical and nontechnical language. The paper includes statistics from a real-world application, and some directions for future developments.
An optimization-based algorithm is presented for scheduling hydro power systems with restricted operating zones and discharge ramping constraints. Hydro watershed scheduling problems are difficult to solve because man...
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An optimization-based algorithm is presented for scheduling hydro power systems with restricted operating zones and discharge ramping constraints. Hydro watershed scheduling problems are difficult to solve because many constraints, continuous and discrete, including hydraulic coupling of cascaded reservoirs have to be considered. Restricted or forbidden operating zones as well as minimum generation limits of hydro units result in discontinuous preferred operating regions, and hinder direct applications of efficient continuous optimization methods such as network now algorithms. Discharge ramping constraints due to navigational, environmental and recreational requirements in a hydro system add another dimension of difficulty since they couple generation or water discharge across time horizon. Integrated consideration of the above constraints is very challenging. The key idea of this paper is to use additional sets of multipliers to relax discontinuous operating region and discharge ramping constraints on individual hydro units so that a two-level optimization structure is formed. The low level consists of a continuous discharge scheduling subproblem determining the generation levels of all units in the entire watershed, and a number of pure integer scheduling subproblems determining the hydro operating states, one for each unit. The discharge subproblem is solved by a network flow algorithm, and the integer scheduling problems are solved by dynamic programming with a small number of states and well-structured transitions. The two sets of subproblems are coordinated through multipliers updated at the high level by using a modified subgradient algorithm. After the dual problem converges, a feasible hydro schedule is obtained by using the same network flow algorithm with the operating states obtained, and operating ranges modified to guarantee satisfaction of ramping constraints. Numerical testing based on the data sets of the PG&E power system shows that this method is
An optimization-based algorithm is presented for scheduling hydrothermal power systems with cascaded and head-dependent reservoirs. Within the Lagrangian relaxation framework, the hydro river catchment subproblems are...
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An optimization-based algorithm is presented for scheduling hydrothermal power systems with cascaded and head-dependent reservoirs. Within the Lagrangian relaxation framework, the hydro river catchment subproblems are difficult to solve because of the continuous reservoir dynamics and constraints, discontinuous operating regions, discrete operating states and hydraulic coupling of cascaded reservoirs. The head-dependent water-power conversion adds another dimension of difficulty since the objective functions of hydro subproblems are no longer stage-wise additive with respect to water discharge. It is difficult to solve the subproblems by relaxing the reservoir limits or the hydraulic coupling among units as in previous work A new algorithm with a novel relaxation structure is presented in this paper to solve hydro river catchment subproblems. The key idea is to use another set of multipliers to relax capacity and minimum generation constraints of individual hydro units. A river catchment subproblem can be further decomposed into two sets of subproblems: a continuous-variable optimization problem determining the generation levels of all units in the entire river catchment, and a number of pure integer problems determining the hydro commitment states, one for each unit. The continuous problem is solved by a nonlinear network flow algorithm, and the integer problems are solved by dynamic programming with a small number of states and well-structured transitions. The two sets of subproblems are coordinated through the multipliers that are updated at the intermediate dual level by using a modified subgradient algorithm. After the dual problem converges, the feasible hydro schedule is obtained by using the same network flow algorithm with operating states obtained in the dual solution and possibly adjusted by heuristics. Numerical testing based on the data sets of a practical system shows that this method is efficient and effective to deal with hydrothermal systems with ca
We present a branch-and-cut algorithm to solve capacitated network design problems. Given a capacitated network and point-to-point traffic demands, the objective is to install more capacity on the edges of the network...
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We present a branch-and-cut algorithm to solve capacitated network design problems. Given a capacitated network and point-to-point traffic demands, the objective is to install more capacity on the edges of the network and route traffic simultaneously, so that the overall cost is minimized. We study a mixed-integer programming formulation of the problem and identify some new facet defining inequalities. These inequalities, together with other known combinatorial and mixed-integer rounding inequalities. are used as cutting planer. To choose the branching variable, we use a new rule called "knapsack branching". We also report on our computational experience using real-lift data.
We present an algorithm for solving stochastic integerprogramming problems with recourse, based on a dual decomposition scheme and Lagrangian relaxation. The approach can be applied to multi-stage problems with mixed...
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We present an algorithm for solving stochastic integerprogramming problems with recourse, based on a dual decomposition scheme and Lagrangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some two-stage test problems. (C) 1999 Elsevier Science B.V. All rights reserved.
Mathematical programming is employed to obtain an optimal decision rule for project approval in capital budgeting in a nonperfect capital market. We use the framework due to Martin Weingartner to formulate the decisio...
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Mathematical programming is employed to obtain an optimal decision rule for project approval in capital budgeting in a nonperfect capital market. We use the framework due to Martin Weingartner to formulate the decision problem in a deterministic setting and derive the optimal rules for the acceptance/rejection of a single project explicitly in the two cases where the borrowing/lending rates for capital are constant and time-dependent, respectively. (C) 1999 Elsevier Science Ltd. All rights reserved.
We survey structural properties of and algorithms for stochastic integerprogramming models, mainly considering linear two-stage models with mixed-integer recourse (and their multi-stage extensions).
We survey structural properties of and algorithms for stochastic integerprogramming models, mainly considering linear two-stage models with mixed-integer recourse (and their multi-stage extensions).
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