In the refinery industry, especially in large-scale modern refineries, production scheduling modeling is an essential tool in the operation and management. By scheduling systems, better economic performance can be ach...
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In the refinery industry, especially in large-scale modern refineries, production scheduling modeling is an essential tool in the operation and management. By scheduling systems, better economic performance can be achieved. In order to implement the scheduling schemes, the influence of control systems has to be considered in scheduling models. This paper presents a novel refinery scheduling model where several controllable and realizable operation modes for production units are established based on unitwide predictive control. Furthermore, operational transitions resulting from switching operation modes of production units are taken into account to reflect the dynamic nature of production. A novel mixed integer linear programming (MILP) discrete-time model is developed, and computational tests show the efficiency of the proposed model.
This paper deals with the problem of scheduling additional train unit (TU) services in a double parallel rail transit line, and a mixedintegerprogramming (MIP) model is formulated for integration strategies of new t...
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This paper deals with the problem of scheduling additional train unit (TU) services in a double parallel rail transit line, and a mixedintegerprogramming (MIP) model is formulated for integration strategies of new trains connected by TUs with the objective of obtaining higher frequencies in some special sections and special time periods due to mass passenger volumes. We took timetable scheduling and TUs scheduling as an integrated optimization model with two objectives: minimizing travel times of additional trains and minimizing shifts of initial trains. We illustrated our model using computational experiments drawn from the real rail transit line 16 in Shanghai and reached results which show that rail transit agencies can obtain a reasonable new timetable for different managerial goals in a matter of seconds, so the model is well suited to be used in daily operations.
District heating is an efficient way of providing heat to urban areas. The use of storage tanks integrated with district heating network would permit to increase the annual utilization of base load equipment, avoiding...
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District heating is an efficient way of providing heat to urban areas. The use of storage tanks integrated with district heating network would permit to increase the annual utilization of base load equipment, avoiding over estimation of the size of backup equipment, and balancing the energy demand fluctuation during day and night. In the present work a multi-objective optimization model for sizing and operation optimization of district heating systems with heat storage tanks is presented. The model includes process design and energy integration techniques for optimizing the temperature intervals, the volume and the operation strategy of thermal storage tanks. The proposed model is demonstrated by means of two test cases. Results show that the efficiency, environmental impacts and total costs of an urban system can be improved after integrating the thermal storage by 4.7%, 5% and 2% respectively. (C) 2013 Elsevier Ltd. All rights reserved.
This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the prese...
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This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.
Motivated by drawing route sketches, we consider the d-regular path schematization problem. For this problem we are given an embedded path P (e.g., a route in a road network) and a positive integer d. The goal is to f...
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Motivated by drawing route sketches, we consider the d-regular path schematization problem. For this problem we are given an embedded path P (e.g., a route in a road network) and a positive integer d. The goal is to find a d-schematized embedding of P in which the orthogonal order of all vertices in the input is preserved and in which every edge has a direction that is an integer multiple of (90/d)(o). We show that deciding whether a path can be d-schematized is NP-complete for any positive integer d. Despite the NP-hardness of the problem we still want to be able to generate route sketches and thus need to solve the d-regular path schematization problem. We explore two different algorithmic approaches, both of which consider two additional quality constraints: We require that every edge is drawn with a user-specified minimum length and we want to maximize the number of edges that are drawn with their preferred direction. The first algorithmic approach restricts the input paths to be axis-monotone. We show that there exists a polynomial-time algorithm that solves the d-regular path schematization problem for this restricted class of embedded paths. We extend this approach by a heuristic such that it can handle arbitrary simple paths. However, for the second step we cannot guarantee that the orthogonal order of the input embedding is maintained. The second approach is a formulation of the d-regular path schematization problem as a mixedintegerlinear program. Finally, we give an experimental evaluation which shows that both approaches generate reasonable route sketches for real-world data. (C) 2013 Elsevier B.V. All rights reserved.
This paper studies the problem of scheduling open shops with no intermediate buffer, called no-wait open shops under makespan minimization. No-wait scheduling problems arise in many realistic production environments s...
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This paper studies the problem of scheduling open shops with no intermediate buffer, called no-wait open shops under makespan minimization. No-wait scheduling problems arise in many realistic production environments such as hot metal rolling, the plastic molding, chemical and pharmaceutical, food processing and several other industries. To tackle such problems, we first develop three different mathematical models, mixedintegerlinear programs, by which we can solve the problem to optimality. Besides the models, we propose novel metaheuristics based on genetic and variable neighborhood search algorithms to solve the large-sized problems in an acceptable computational time. The key point in any scheduling solver is the procedure of encoding and decoding schemes. In this paper, we propose a simple yet effective tailor-made procedure of encoding and decoding schemes for no-wait open shop problems. The operators of the proposed metaheuristics are designed so as to consider the specific encoding scheme of the problem. To evaluate the performance of models and metaheuristics, we conduct two computational experiments. The first includes small-sized instances by which we compare the mathematical models and assess general performance of the proposed metaheuristics. In the second experiment, we further evaluate the potential of metaheuristics on solving some benchmarks in the literature of pure open shops. The results show that the models and metaheuristics are effective to deal with the no-wait open shop problems. (C) 2014 Elsevier B.V. All rights reserved.
This paper proposes a solution methodology for the production scheduling of batch plants. The methodology is defined by an integrated approach that simultaneously considers the representation of the scheduling problem...
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This paper proposes a solution methodology for the production scheduling of batch plants. The methodology is defined by an integrated approach that simultaneously considers the representation of the scheduling problem, the optimization model, and the decision-making process. A problem representation and a mixedintegerlinear programing (MILP) model are developed and applied to solve a real world scheduling problem from the chemical-pharmaceutical industry. The main advantage of this approach is that it includes a general process representation that can be used across several departments of the company. Moreover, we also discuss development and implementation challenges of optimization methods for the process industry, and we provide some guidelines to mitigate existing problematic issues in this domain.
As studies on municipal solid waste management increased in recent years, many new mathematical models and approaches with a focus on determining the best treatment and disposal scenario were developed and applied. In...
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As studies on municipal solid waste management increased in recent years, many new mathematical models and approaches with a focus on determining the best treatment and disposal scenario were developed and applied. In this study, a mixed integer linear programming model was developed to be used as a facilitative tool for the cost minimisation of municipal solid waste management practices. Since municipal solid waste mass is a mixed composition of various types of waste components with different physical and chemical properties, the model was designed to include all the suitable treatment and disposal methods for these different waste components. The method alternatives with multiple waste inputs, such as aerobic biological treatment and the thermal processes, were divided into a number of inputs to remove their non-linear structures. This way, linearprogramming could be used, and the linear cost function could be minimised over a set of linear constraints with integer variables. The model was applied to the city of Kocaeli, which will require a new waste management application in the future, beginning from 2015. The results obtained for different haul distance constraints in the study area were presented and assessed. The results showed that all the information required for a comprehensive management task could be modelled by a linear optimisation model with a divided processes approach easily.
In order to improve the robustness of a railway system in station areas, this paper introduces an iterative approach to successively optimize the train routing through station areas and to enhance this solution by app...
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In order to improve the robustness of a railway system in station areas, this paper introduces an iterative approach to successively optimize the train routing through station areas and to enhance this solution by applying some changes to the timetable in a tabu search environment. We present our vision on robustness and describe how this vision can be used in practice. By introducing the spread of the trains in the objective function for, the route choice and timetabling module, we improve the robustness of a railway system. Using a discrete event simulation model, the performance of our algorithms is evaluated based on a case study for the Brussels' area. The computational results indicate an average improvement in robustness of 6.2% together with a decrease in delay propagation of about 25%. Furthermore, the effect of some measures like changing the train offer to further increase the robustness is evaluated and compared. (C) 2013 Elsevier B.V. All rights reserved.
Setup operations are significant in some production environments. It is mandatory that their production plans consider some features, as setup state conservation across periods through setup carryover and crossover. T...
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Setup operations are significant in some production environments. It is mandatory that their production plans consider some features, as setup state conservation across periods through setup carryover and crossover. The modelling of setup crossover allows more flexible decisions and is essential for problems with long setup times. This paper proposes two models for the capacitated lot-sizing problem with backlogging and setup carryover and crossover. The first is in line with other models from the literature, whereas the second considers a disaggregated setup variable, which tracks the starting and completion times of the setup operation. This innovative approach permits a more compact formulation. Computational results show that the proposed models have outperformed other state-of-the-art formulation.
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