In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The...
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In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The aim is to minimize the cycle time, robot setup costs and robot costs. The second difference is on the procedure proposed to solve the problem. In addition, a new mixed-integer linear programming model is developed. Since the problem is NP-hard, three versions of multi-objective evolution strategies (MOES) are employed. Numerical results show that the proposed hybrid MOES is more efficient. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
In spite of many studies, investigating balancing and sequencing problems in mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new mixed-Inte...
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In spite of many studies, investigating balancing and sequencing problems in mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new mixed-integer linear programming (MILP) model is developed to provide the exact solution of the problem with station-dependent assembly times. Because of NP-hardness, a Simulated Annealing (SA) is applied and compared to the Co-evolutionary Genetic Algorithm (Co-GA) from the literature. To strengthen the search process, two main hypotheses, namely simultaneous search and feasible search, are developed contrasting Co-GA. Various parameters of SA are reviewed to calibrate the algorithm by means of Taguchi design of experiments. Numerical results statistically show the efficiency and effectiveness of the proposed SA in terms of both the quality of solution and the time of achieving the best solution. Finally, the contribution of each hypothesis in this superiority is analyzed. (c) 2011 Elsevier B.V. All rights reserved.
Assessing the environmental performance of hydrogen infrastructures is essential for determining their practical viability. Previous optimization approaches for hydrogen networks have focused on optimizing a single en...
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Assessing the environmental performance of hydrogen infrastructures is essential for determining their practical viability. Previous optimization approaches for hydrogen networks have focused on optimizing a single environmental metric in conjunction with the economic performance. This approach is inadequate as it may leave relevant environmental criteria out of the analysis. We propose herein a novel framework for optimizing hydrogen supply chains (SC) according to several environmental indicators. Our method comprises two steps. In step one, we formulate a multi-objective mixed-integerlinear program (MILP) that accounts for the simultaneous minimization of the most relevant life cycle assessment (LCA) impacts. Principal Component Analysis (PCA) is next employed in the post-optimal analysis of the MILP in order to facilitate the interpretation and analysis of its solution space. We demonstrate the capabilities of this approach through its application to the design of the future (potential) hydrogen SC in Spain. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
In this paper we study the problem of replicating the performances of a stock market index, i.e. the so-called index tracking problem, and the problem of out-performing a market index, i.e. the so-called enhanced inde...
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In this paper we study the problem of replicating the performances of a stock market index, i.e. the so-called index tracking problem, and the problem of out-performing a market index, i.e. the so-called enhanced index tracking problem. We introduce mixed-integer linear programming (MILP) formulations for these two problems. Furthermore, we present a heuristic framework called Kernel Search. We analyze and evaluate the behavior of several implementations of the Kernel Search framework to the solution of the index tracking problem. We show the effectiveness and efficiency of the framework comparing the performances of these heuristics with those of a general-purpose solver. The computational experiments are carried out using benchmark and newly created instances. (C) 2011 Elsevier B.V. All rights reserved.
This paper presents a mixed-integer linear programming model for the solution of the centralized Generation Expansion Planning (GEP) problem. The GEP objective is the minimization of the total present value of investm...
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This paper presents a mixed-integer linear programming model for the solution of the centralized Generation Expansion Planning (GEP) problem. The GEP objective is the minimization of the total present value of investment, operating and unserved energy costs net the remaining value of the new units at the end of the planning horizon. Environmental considerations are modeled through the incorporation of the cost of purchasing emission allowances in the units' operating costs and the inclusion of annual renewable quota constraints and penalties. A monthly time-step is employed, allowing mid-term scheduling decisions, such as unit maintenance scheduling and reservoir management, to be taken along with investment decisions within the framework of a single long-term optimization problem. The proposed model is evaluated using a real (Greek) power system. Sensitivity analysis is performed for the illustration of the effect of demand, fuel prices and CO2 prices uncertainties on the planning decisions. (C) 2011 Elsevier B.V. All rights reserved.
A decision support tool helping the transmission system operator (TSO) dispatchers to minimize the costs for the load-frequency control is proposed in this paper. Dispatch of tertiary control reserves is done primaril...
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A decision support tool helping the transmission system operator (TSO) dispatchers to minimize the costs for the load-frequency control is proposed in this paper. Dispatch of tertiary control reserves is done primarily with an aim to ensure secure operation of the transmission system, while the costs associated with utilization of the control reserves are traditionally of less importance. The mixed-integer linear programming based optimization tool proposed in this paper suggests such activation of tertiary control reserves which minimizes the costs for the control reserves utilization and ensures secure operation of the transmission system at the same time. Through a case study comparing the control based on the decision support tool with historical control performed manually by the TSO dispatchers, it is demonstrated that the costs for the load-frequency control could be reduced. (c) 2012 Elsevier Ltd. All rights reserved.
New mixed-integer linear programming formulations are presented for the quadratic assignment problem, based on splittings of the coefficient matrices. Computational results are reported for medium-sized problem instan...
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New mixed-integer linear programming formulations are presented for the quadratic assignment problem, based on splittings of the coefficient matrices. Computational results are reported for medium-sized problem instances in the QAPLIB collection. (c) 2012 Elsevier Ltd. All rights reserved.
A stochastic programming formulation is developed for determining the optimal placement of gas detectors in petrochemical facilities. FLACS, a rigorous gas dispersion package, is used to generate hundreds of scenarios...
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A stochastic programming formulation is developed for determining the optimal placement of gas detectors in petrochemical facilities. FLACS, a rigorous gas dispersion package, is used to generate hundreds of scenarios with different leak locations and weather conditions. Three problem formulations are investigated: minimization of expected detection time, minimization of expected detection time including a coverage constraint, and a placement based on coverage alone. The extensive forms of these optimization problems are written in Pyomo and solved using CPLEX. A sampling procedure is used to find confidence intervals on the optimality gap and quantify the effectiveness of detector placements on alternate subsamples of scenarios. Results show that the additional coverage constraint significantly improves performance on alternate subsamples. Furthermore, both optimization-based approaches dramatically outperform the coverage-only approach, making a strong case for the use of rigorous dispersion simulation coupled with stochastic programming to improve the effectiveness of these safety systems. (C) 2012 Published by Elsevier Ltd.
We study a real-world complex hybrid flow-shop scheduling problem arising from a bio-process industry. There are a variety of constraints to be taken into account, in particular zero intermediate capacity and limited ...
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We study a real-world complex hybrid flow-shop scheduling problem arising from a bio-process industry. There are a variety of constraints to be taken into account, in particular zero intermediate capacity and limited waiting time between processing stages. We propose an exact solution approach for this optimization problem, based on a discrete time representation and a mixed-integer linear programming formulation. The proposed solution algorithm makes use of a new family of valid inequalities exploiting the fact that a limited waiting time is imposed on jobs between two successive production stages. The results of our computational experiments confirm that the proposed method produces good feasible schedules for industrial instances. (C) 2011 Elsevier Ltd. All rights reserved.
The Capacitated Facility Location Problem (CFLP) is among the most studied problems in the OR literature. Each customer demand has to be supplied by one or more facilities. Each facility cannot supply more than a give...
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The Capacitated Facility Location Problem (CFLP) is among the most studied problems in the OR literature. Each customer demand has to be supplied by one or more facilities. Each facility cannot supply more than a given amount of product. The goal is to minimize the total cost to open the facilities and to serve all the customers. The problem is NP-hard. The Kernel Search is a heuristic framework based on the idea of identifying subsets of variables and in solving a sequence of MILP problems, each problem restricted to one of the identified subsets of variables. In this paper we enhance the Kernel Search and apply it to the solution of the CFLP. The heuristic is tested on a very large set of benchmark instances and the computational results confirm the effectiveness of the Kernel Search framework. The optimal solution has been found for all the instances whose optimal solution is known. Most of the best known solutions have been improved for those instances whose optimal solution is still unknown.
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