In this study, we propose a mixed integer nonlinear programming (MINLP) model for superstructure based optimization of biodiesel production from microalgal biomass. The proposed superstructure includes a number of maj...
详细信息
In this study, we propose a mixed integer nonlinear programming (MINLP) model for superstructure based optimization of biodiesel production from microalgal biomass. The proposed superstructure includes a number of major processing steps for the production of biodiesel from microalgal biomass, such as the harvesting of microalgal biomass, pretreatments including drying and cell disruption of harvested biomass, lipid extraction, transesterification, and post-transesterfication purification. The proposed model is used to find the optimal processing pathway among the large number of potential pathways that exist for the production of biodiesel from microalgae. The proposed methodology is tested by implementing on a specific case with different choices of objective functions. The MINLP model is implemented and solved in GAMS using a database built in Excel. The results from the optimization are analyzed and their significances are discussed. (C) 2013 Elsevier Ltd. All rights reserved.
Recently, parallel computing environments have become significantly popular. In order to obtain the benefit of using parallel computing environments, we have to deploy our programs for these effectively. This paper fo...
详细信息
Recently, parallel computing environments have become significantly popular. In order to obtain the benefit of using parallel computing environments, we have to deploy our programs for these effectively. This paper focuses on a parallelization of SCIP (Solving Constraint integer Programs), which is a mixed-integer linear programming solver and constraint integerprogramming framework available in source code. There is a parallel extension of SCIP named ParaSCIP, which parallelizes SCIP on massively parallel distributed memory computing environments. This paper describes FiberSCIP, which is yet another parallel extension of SCIP to utilize multi-threaded parallel computation on shared memory computing environments, and has the following contributions: First, we present the basic concept of having two parallel extensions, and the relationship between them and the parallelization framework provided by UG (Ubiquity Generator), including an implementation of deterministic parallelization. Second, we discuss the difficulties in achieving a good performance that utilizes all resources on an actual computing environment, and the difficulties of performance evaluation of the parallel solvers. Third, we present away to evaluate the performance of new algorithms and parameter settings of the parallel extensions. Finally, we demonstrate the current performance of FiberSCIP for solving mixed-integer linear programs (MIPs) and mixed-integernonlinear programs (MINLPs) in parallel.
The emphasis in this paper is on investigating a new generation scheduling algorithm for the interconnected power systems. In general, the generation scheduling problem formulated as a mixedintegernonlinear programm...
详细信息
The emphasis in this paper is on investigating a new generation scheduling algorithm for the interconnected power systems. In general, the generation scheduling problem formulated as a mixed integer nonlinear programming (MINLP) can be efficiently computed by the generalized Benders decomposition (GBD) technique which decouples an original problem into the master problem and subproblems to allow remarkably fast and accurate solutions of very large problems. In order to ferret out efficient inter-temporal optimal power flow subproblems, we will propose a regional decomposition framework based on auxiliary problem principle (APP). Obviously, this scheme can find the most economic dispatch (ED) schedule under the power transactions for a multi-utility system without the exchange of each utility's own private information and major disruption to existing ED or optimal power flow (OPF) constructed by individual utilities. (C) 2010 Elsevier Ltd. All rights reserved.
Motivated by stochastic 0-1 integerprogramming problems with an expected utility objective, we study the mixed-integernonlinear set: where N is a positive integer, is a concave function, are nonnegative vectors, d i...
详细信息
Motivated by stochastic 0-1 integerprogramming problems with an expected utility objective, we study the mixed-integernonlinear set: where N is a positive integer, is a concave function, are nonnegative vectors, d is a real number and B is a positive real number. We propose a family of inequalities for the convex hull of P by exploiting submodularity of the function over and the knapsack constraint . Computational effectiveness of the proposed inequalities within a branch-and-cut framework is illustrated using instances of an expected utility capital budgeting problem.
In this paper, we address the Continuous Multifacility Monotone Ordered Median Problem. The goal of this problem is to locate p facilities in Rd minimizing a monotone ordered weighted median function of the distances ...
详细信息
In this paper, we address the Continuous Multifacility Monotone Ordered Median Problem. The goal of this problem is to locate p facilities in Rd minimizing a monotone ordered weighted median function of the distances between given demand points and its closest facility. We propose a new branch-and -price procedure for this problem, and three families of matheuristics based on: solving heuristically the pricer problem, aggregating the demand points, and discretizing the decision space. We give detailed discussions of the validity of the exact formulations and also specify the implementation details of all the solution procedures. Besides, we assess their performances in an extensive computational experience that shows the superiority of the branch-and-price approach over the compact formulation in medium-sized instances. To handle larger instances it is advisable to resort to the matheuristics that also report rather good results.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )
We present an algorithm to solve multistage stochastic convex problems, whose objective function and constraints are nonlinear. It is based on the twin-node-family concept involved in the Branch-and-Fix Coordination m...
详细信息
We present an algorithm to solve multistage stochastic convex problems, whose objective function and constraints are nonlinear. It is based on the twin-node-family concept involved in the Branch-and-Fix Coordination method. These problems have 0-1 mixed-integer and continuous variables in all the stages. The non-anticipativity constraints are satisfied by means of the twin-node family strategy. In this work to solve each nonlinear convex subproblem at each node we propose the solution of sequences of quadratic subproblems. Due to the convexity of the constraints we can approximate them by means of outer approximations. These methods have been implemented in C++ with the help of CPLEX 12.1, which only solves the quadratic approximations. The test problems have been randomly generated by using a C++ code developed by this author. Numerical experiments have been performed and its efficiency has been compared with that of a well-known code. Key words: stochastic programming, convex programming, branch and fix coordination, mixed integer nonlinear programming, quadratic programming, outer approximation.
The paper addresses the problem of locating sensors with a circular field of view so that it given line segment is under full Surveillance, which is termed as the disc covering problem on a line. The cost of each sens...
详细信息
The paper addresses the problem of locating sensors with a circular field of view so that it given line segment is under full Surveillance, which is termed as the disc covering problem on a line. The cost of each sensor includes a fixed component f, and a variable component that is a convex function of the diameter of the field-of-view area. When only one type of sensor or, in general. one type of disc, is available, then a simple polynomial algorithm solves the problem. When (here are different types of sensors, the problem becomes hard. A branch-and-bound algorithm as well as an efficient heuristic are developed for the special case in which the variable cost component of each sensor is proportional to the square of the measure of the field-of-view area. The heuristic very often obtains the optimal solution as shown in extensive computational testing.
If a mathematical program has many symmetric optima, solving it via Branch-and-Bound techniques often yields search trees of disproportionate sizes;thus, finding and exploiting symmetries is an important task. We prop...
详细信息
If a mathematical program has many symmetric optima, solving it via Branch-and-Bound techniques often yields search trees of disproportionate sizes;thus, finding and exploiting symmetries is an important task. We propose a method for automatically finding the formulation group of any given mixed-integernonlinear Program, and for reformulating the problem by means of static symmetry breaking constraints. The reformulated problem-which is likely to have fewer symmetric optima-can then be solved via standard Branch-and-Bound codes such as CPLEX (for linear programs) and Couenne (for nonlinear programs). Our computational results include formulation group tables for the MIPLib3, MIPLib2003, GlobalLib and MINLPLib instance libraries and solution tables for some instances in the aforementioned libraries.
This study is devoted to developing a platoon-based cooperative lane-change control (PB-CLC). It coordinates the trajectories of a CAV platoon under a platoon-centered platooning control to accommodate the CAV lane-ch...
详细信息
This study is devoted to developing a platoon-based cooperative lane-change control (PB-CLC). It coordinates the trajectories of a CAV platoon under a platoon-centered platooning control to accommodate the CAV lane-change requests from its adjacent lane, aiming to reduce the negative traffic impacts on the platoon resulting from lane-change maneuvers, on the premise of ensuring CAVs' safety and mobility. Mathematically, the PB-CLC control is established using a hybrid model predictive control (MPC) system. The hybrid MPC system involves an MPC-based mixed integer nonlinear programming optimizer (MINLP-MPC) for optimal lane-change decisions, which considers multiple objectives such as traffic smoothness, driving comfort and lane-change response promptness subject to vehicle dynamics and safety constraints. To ensure the feasible lane-change, this study investigates and provides a lower bound of the lane-change time window by analyzing the MINLP-MPC model feasibility. Apart from the optimal lane-change decision consideration, the hybrid MPC system is well designed to ensure the control continuity and smoothness. In particular, the hybrid MPC system control feasibility and stability are proved to enable the platoon's back-and-forth state switchings between car-following and lane-change accommodation states. Next, we developed a machine learning aided distributed branch and bound algorithm (ML-DBB) to solve the MINLP-MPC model within a control sampling time interval (< 1 second). Specifically, built upon computer simulation and the c-LHS sampling technique, supervised machine learning models are developed offline to predict a reduced solution space of the integer variables, which is further integrated into the distributed branch and bound method to solve the MINLP-MPC model efficiently online. Extensive numerical experiments validate the effectiveness and applicability of the ML-DBB algorithm and the PB-CLC control.
This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors with in the structure of the network, as opposed to the end-of-p...
详细信息
This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors with in the structure of the network, as opposed to the end-of-pipe use of such interceptors. The model is based on are cycle and reuse scheme that simultaneously satisfies process and environmental constraints. The properties considered in this work are composition, toxicity, theoretical oxygen demand, pH, density and viscosity. The property mixing rules included in the model give rise to bilinear terms for the property operators, and a global optimization algorithm is used for the solution of the model. The model minimizes the total annual cost of the network, which includes the fresh sources cost and the annualized property treatment system and the piping costs. Three examples are included to show the applicability and advantages of the proposed model. (C) 2010 Elsevier Ltd. All rights reserved.
暂无评论