This paper presents a novel strategy for speeding up the classical Benders decomposition for large-scale mixed integer linear programming problems. The proposed method is particularly useful when the optimality cut is...
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This paper presents a novel strategy for speeding up the classical Benders decomposition for large-scale mixed integer linear programming problems. The proposed method is particularly useful when the optimality cut is difficult to obtain. A ratio of distances from a feasible point to an infeasible point and a feasibility cut is used as a metric to determine the tightest constraint for the region located by the feasible point, thus improving the convergence rate. Application of the proposed approach to a multi-product batch plant scheduling problem shows substantial improvement both in the computational time and the number of iterations. (C) 2012 Elsevier Ltd. All rights reserved.
This paper presents a mixed-integerlinearprogramming (MILP) super-structure model for the optimal design of distributed energy generation systems that satisfy the heating and power demand at the level of a small nei...
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This paper presents a mixed-integerlinearprogramming (MILP) super-structure model for the optimal design of distributed energy generation systems that satisfy the heating and power demand at the level of a small neighborhood. The objective is the optimal selection of the system components among several candidate technologies (micro combined heat and power units, photovoltaic arrays, boilers, central power grid), including the optimal design of a heating pipeline network, that allows heat exchange among the different nodes. The objective function to be minimised contains the annualised overall investment cost and the annual operating cost of the system. We show that besides the usual energy balance and unit operations constraints, additional equations must be included in the model to guarantee correctness of the produced heating pipeline designs. A special instance of the problem where a single centralised combined heat and power unit is installed in the neighborhood is also considered. The efficiency of the proposed model is evaluated through illustrating examples. (C) 2012 Elsevier Ltd. All rights reserved.
We consider a biodiesel production company that collects waste vegetable oil from source points that generate waste in large amounts. The company uses the collected waste as raw material for biodiesel production. The ...
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We consider a biodiesel production company that collects waste vegetable oil from source points that generate waste in large amounts. The company uses the collected waste as raw material for biodiesel production. The manager of this company needs to decide which of the present source points to include in the collection program, which of them to visit on each day, which periodic routing schedule to repeat over an infinite horizon and how many vehicles to operate such that the total collection, inventory and purchasing costs are minimized while the production requirements and operational constraints are met. For this selective and periodic inventory routing problem, we propose two different formulations, compare them and apply the better performing one on a real-world problem with 36 scenarios. We generate lower bounds using a partial linear relaxation model, and observe that the solutions obtained through our model are within 3.28% of optimality on the average. Several insights regarding the customer selection, routing and purchasing decisions are acquired with sensitivity analysis.
Video surveillance systems are becoming increasingly important for crime investigation and deterrence, and the number of cameras installed in public space is increasing. However, many cameras installed at fixed positi...
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Video surveillance systems are becoming increasingly important for crime investigation and deterrence, and the number of cameras installed in public space is increasing. However, many cameras installed at fixed positions are required to observe a wide and complex area. In order to efficiently observe such a wide area at lower cost, mobile robots are an attractive option. In this paper, we propose a method for determining the traveling route of a mobile surveillance camera. Our method is based on mixed integer linear programming and obtains an optimum traveling route such that a camera with a certain visual angle and visual distance can observe the entire region at the shortest intervals. Through our experiments, we apply this method to several artificially generated data and data for a real university campus and demonstrate that effective patrol courses for specified mobile surveillance cameras can be generated.
A mixed integer linear programming (MILP) model is proposed in this paper that targets the optimal production scheduling in a single yogurt production line. The model takes into account all the standard constraints en...
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A mixed integer linear programming (MILP) model is proposed in this paper that targets the optimal production scheduling in a single yogurt production line. The model takes into account all the standard constraints encountered in production scheduling (material balances, inventory limitations, machinery capacity, labor shifts and manpower restrictions). Furthermore, it considers special features that characterize yogurt production, which are limitations in production sequencing mainly due to different fat contents and flavors of various products and sequence-dependent setup times and costs. The objective function that is minimized considers all major sources of variable cost that depend on the production schedule, i.e. changeover cost, inventory cost and labor cost. The model is applied to a yogurt production line of a major dairy industry and the results are presented and discussed. (c) 2006 Elsevier Ltd. All rights reserved.
This paper addresses the midterm preventive maintenance outage scheduling problem of thermal generating units which is becoming increasingly important due to the aging of power generation fleet. In this context, a nov...
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This paper addresses the midterm preventive maintenance outage scheduling problem of thermal generating units which is becoming increasingly important due to the aging of power generation fleet. In this context, a novel midterm preventive maintenance outage scheduler is proposed based on decision tree and mixedintegerlinear formation which explicitly considers the thermal units aging momentum in terms of failure rate. This allows the system operators to determine the thermal units' maintenance outage window based on the cost/benefit analysis of preventive maintenance tasks while optimizing the time interval between consecutive maintenance tasks. Additionally, the division of the year-long midterm horizon into several time blocks in the proposed model provides a unique opportunity for parallel processing and computational saving. The proposed approach is tested on the IEEE Reliability Test System (IEEE-RTS). The results presented reveal the accuracy and efficiency of the proposed approach.
This paper deals with two major issues for industries: the product design and the supply chain design. These problems are usually solved separately, but in recent years, approaches were proposed to tackle these two pr...
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This paper deals with two major issues for industries: the product design and the supply chain design. These problems are usually solved separately, but in recent years, approaches were proposed to tackle these two problems together. In this paper, we investigate more precisely the links between the standardization of products or components, and the design of the supply chain. First, we show on a little example that there is a great interest to consider simultaneously these two decisions, and that solving these interdependent problems separately could result in a suboptimal, or even a bad, decision. Then, on a simplified problem issued from an industrial case study, we outline the impact of standardization choices on the structure of the supply chain and the gain that can be obtained from solving the problem as a unique compound optimization model. To illustrate the solutions of the problem, we propose graphics in order to visualize, in function of quantities and/or transportation costs, the hest decision for the product standardization and for the supply chain design. Graphics also permit to anticipate the impacts of a variation of either quantities or transportation costs, from a specific situation. Such graphics they could be used in a decision aid tool to help companies in their choices. Finally, we show that costs and supply chain structure are highly impacted. (C) 2010 Elsevier B.V. All rights reserved.
In the automotive industry, a manufacturer must perform several hundreds of tests on prototypes of a vehicle before starting its mass production. Tests must be allocated to suitable prototypes and ordered to satisfy t...
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In the automotive industry, a manufacturer must perform several hundreds of tests on prototypes of a vehicle before starting its mass production. Tests must be allocated to suitable prototypes and ordered to satisfy temporal constraints and various kinds of test dependencies. The manufacturer aims to minimize the number of prototypes required. We present improvements of constraint programming (CP) and hybrid approaches to effectively solve random instances from an existing benchmark. CP mostly achieves better solutions than the previous heuristic technique and genetic algorithm. We also provide customized search schemes to enhance the performance of general search algorithms. The hybrid approach applies mixed integer linear programming (MILP) to solve the planning part and CP to find the complete schedule. We consider several logical principles such that the MILP model can accurately estimate the prototype demand, while its size particularly for large instances does not exceed memory capacity. Moreover, the robustness is alleviated when we allow CP to partially change the allocation obtained from the MILP model. The hybrid method can contribute to optimal solutions in some instances.
Crane is widely used to move a heavy object from one place to another not only in manufacturing industry but also service industry. As an important resource in the train oilcan repairing, crane scheduling affects dire...
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Crane is widely used to move a heavy object from one place to another not only in manufacturing industry but also service industry. As an important resource in the train oilcan repairing, crane scheduling affects directly the productivity of the systems. In this paper, we study cyclic single crane scheduling problem with two parallel train oilcan repairing lines, where jobs are loaded into the line at one end and unloaded at the other end. The processing time at each workstation must be within a given range. There is no buffer between these stations. A crane is used to move jobs between the workstations in two parallel lines. The objective is to schedule the moves to minimize the production cycle. We proposed a time way diagram for two parallel lines and developed a mixed integer linear programming model. Then we extended the model to the scheduling problem with multi-station to eliminate the bottleneck in lines. Examples are given to demonstrate the effectiveness of the model. (C) 2011 Elsevier Ltd. All rights reserved.
This paper examines a preprocessing technique for a mixed integer linear programming (MILP) formulation of the Transmission-Constrained Unit Commitment problem (TC-UC). Incorporating transmission constraints into the ...
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This paper examines a preprocessing technique for a mixed integer linear programming (MILP) formulation of the Transmission-Constrained Unit Commitment problem (TC-UC). Incorporating transmission constraints into the Unit Commitment problem can significantly increase the size and difficulty of the problem. By examining the structure of the transmission network, variables that have no impact on the quality of the overall solution can be identified and removed. This preprocessing can reduce the time needed to solve the linearprogramming relaxation of the MILP, and as a result, the MILP itself. Illinois's transmission network was used to test the benefit of the proposed technique. Preprocessing was able to remove 30% of the buses in the transmission network. This reduction led to a significant decrease in the time needed to solve a 24 h TC-UC problem. An added benefit of the preprocessing is that symmetry can be introduced into the problem. Identifying this symmetry and exploiting it can improve overall solution times even further. (C) 2012 Published by Elsevier Ltd.
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