Fleet deployment is a complicated decision problem that must be faced by both the owner and charterer, especially in liner transportation. Therefore, an LNG fleet allocation problem studied by predecessors was optimiz...
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Fleet deployment is a complicated decision problem that must be faced by both the owner and charterer, especially in liner transportation. Therefore, an LNG fleet allocation problem studied by predecessors was optimized. In the shipping cost, the fuel cost accounts for a large proportion, and the shipping route speed is the main factor to determine the fuel consumption. Therefore, in the future, the problem of route allocation will be further optimized to make it more practical. By introducing the parameter of speed, the mixed integer programming model will be optimized by combining the changes of various costs of ships under different speeds, namely the relevant parameters, and the nonlinear programming solution method of Excel will be used for analysis. The results show that the annual operating cost can be reduced when ships with different speeds are arranged to replace fleets on different routes or on the same route and put into the operation of ships with the same speed.
In this paper, the applicability of linear programming (LP) in management of seedling transportation was compared to that of mixed integer programming (MIP). In the LP model, presented in an earlier paper, a linear ob...
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In this paper, the applicability of linear programming (LP) in management of seedling transportation was compared to that of mixed integer programming (MIP). In the LP model, presented in an earlier paper, a linear objective function was used as a surrogate for the actual objective function, which is intrinsically nonlinear. In the LP model, transportation costs were determined per seedling, whereas in the MIP model they were based on vehicle loads. When the number of transported seedlings within a certain period decreased, for instance, due to planting through the growth period, the computational accuracy of the LP model was clearly lower than that of the MIP model. Despite that, differences in allocation of orders between these two models were small. Thus, in the actual business situation of Finnish nursery companies, standard LP seems to be an adequate tool for management of seedling transportation. From the standpoint of cost-efficient seedling business, planting through the growth period increased optimal transportation costs markedly. In addition to the seedling business, these results can be utilized in other types of business dealing with analogous transportation problems.
This study proposes a model predictive control framework using a mixed integer programming for the deep neural network (DNN) model with rectified linear unit (ReLU). The accurate DNN model with ReLU using the past inp...
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This study proposes a model predictive control framework using a mixed integer programming for the deep neural network (DNN) model with rectified linear unit (ReLU). The accurate DNN model with ReLU using the past input time series for the diesel engine is constructed. In this method, the ReLU is represented by inequalities including 0-1 variables (binaries). The model predictive control problem is formulated as a mixed integer programming problem and is applied to the control problem of the diesel engine. Dynamical DNN model of a diesel engine is constructed using the experimental data. This model can represent complicate engine phenomena such as strong nonlinearity and delay. Simulation results of the worldwide harmonized transient cycle (WHTC) verify the effectiveness of the proposed method. The difficulties of non-linearity, delay, and interference in the control problem of the diesel engine are solved by using a systematic model predictive control of the DNN model.
A power grid island is a self-sufficient subnetwork in a large-scale power system. In weakly connected islands, limited inter-island power flows are allowed. Intentional islanding of a power grid is helpful for the an...
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A power grid island is a self-sufficient subnetwork in a large-scale power system. In weakly connected islands, limited inter-island power flows are allowed. Intentional islanding of a power grid is helpful for the analysis of distributed generation systems connected to a power grid, and valuable for power system reliability of extreme emergency states. In this paper, we use graph partitioning methods to form islands in a power grid and formulate these problems as mixedinteger programs. Our models are based the optimal power flow model to minimize the load shedding cost. With these mathematical programming models, optimal formation of islands can be obtained and the different approaches can be compared. Through experiment on IEEE-30-Bus system, computational results are analyzed and compared to provide insight for power grid intentional islanding.
This paper considers an optimal path generation problem that generates a path of an automobile without any collision with obstacles. The problem is formulated as a mixed integer programming problem. In the problem the...
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This paper considers an optimal path generation problem that generates a path of an automobile without any collision with obstacles. The problem is formulated as a mixed integer programming problem. In the problem the obstacles and environments around the automobile can be represent as inequality conditions. The dynamics of the obstacle is described as variation of a prohibited region. According to model predictive control we solve the optimal path generation problem at each time step then apply the first element of the optimal input. The method proposed in this paper can deal with an explicit representation of the dynamics of the obstacle and provides no collision between the automobile and the obstacle.
The bilevel programming problem is a static version of the Stackelberg's leader follower game in which Stackelberg strategy is used by the higher level decision maker called the leader given the rational reaction ...
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The bilevel programming problem is a static version of the Stackelberg's leader follower game in which Stackelberg strategy is used by the higher level decision maker called the leader given the rational reaction of the lower decision maker called the follower. The bilevel programming problem (BLPP) is a two-level hierarchical optimisation problem and is non-convex. This paper deals with finding links between the bilevel linear fractional/linear programming problem (BF/LP), the generalised linear fractional complementarity problem (GFCP) and mixedinteger linear fractional programming problem (MIFP). The (BF/LP) is reformulated as a (GFCP) which in turn is reformulated as an (MIFP). The method is supported with the help of a numerical example.
The actual bus headway often deviates from the planned departure frequency because of external factors, such as traffic conditions and public transport demand, leading to transit resource waste and reducing the qualit...
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The actual bus headway often deviates from the planned departure frequency because of external factors, such as traffic conditions and public transport demand, leading to transit resource waste and reducing the quality of service. In view of the existing shortcomings of the current dispatching strategy, a mixed integer programming model, integrating a bus-holding and stop-skipping strategy, is constructed to improve transit service with a minimum cost. The real-time optimal holding and stop-skipping strategies can be obtained by solving the proposed model using the Lagrangian relaxation algorithm. A numerical example is conducted using real transit GPS ( Global Position System) and IC ( Intelligent Card) data in Harbin. The results show that compared to a single control strategy, the proposed hybrid model is a better trade-off between the quality of the transit service and the operation cost. Notably, such a strategy would produce a minimal passengers' average travel time coefficient. It is a great help for promoting the transit service level and increasing competitiveness.
Elementary siphons are useful in the development of a deadlock prevention policy for a discrete event system modeled with Petri nets. This paper proposes an algorithm to iteratively extract a set of elementary siphons...
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Elementary siphons are useful in the development of a deadlock prevention policy for a discrete event system modeled with Petri nets. This paper proposes an algorithm to iteratively extract a set of elementary siphons in a class of Petri nets, called system of simple sequential processes with resources （S3pR）. At each iteration, by a mixed-integerprogramming （MIP） method, the proposed algorithm finds a maximal unmarked siphon, classifies the places in it, extracts an elementary siphon from the classified places, and adds a new constraint in order to extract the next elementary siphon. This algorithm iteratively executes until no new unmarked siphons can be found. It finally obtains a unique set of elementary siphons and avoids a complete siphon enumeration. A theoretical analysis and examples are given to demonstrate its efficiency and practical potentials.
Small and medium enterprise (SME) needs to apply effective scheduling in order to meet the demand schedule. This is done traditionally, though, it is necessary to allocate production resources to produce product varie...
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Small and medium enterprise (SME) needs to apply effective scheduling in order to meet the demand schedule. This is done traditionally, though, it is necessary to allocate production resources to produce product variety such as bread. The fact shows that the order fulfillment is often delayed because of incorrect scheduling. This problem can be solved by making production scheduling that have a minimum completion time (makespan) as approached by using mixed integer programming (MIP). This study is proposed to build an effective scheduling for an SME on bread products by utilize MIP. The output is then compared to the serial machine scheduling method with CDS algorithm. Both methods are having an output in minimizing makespan. The results showed that with the proposed scheduling, the SME likely able to fulfill the whole order in time.
Sustainable manufacturing considers the economic, environmental and social dimensions as equally important. For any product, like the common bicycles, a holistic view on the different life cycle phases has to be taken...
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Sustainable manufacturing considers the economic, environmental and social dimensions as equally important. For any product, like the common bicycles, a holistic view on the different life cycle phases has to be taken in order to ensure that resources are utilised adequately. Preferences on the three dimensions might lead to different selections of materials, used equipment or required education for fulfilling the considered objectives. In a first approach, bicycle manufacturing alternatives are identified and modelled via bi-criteria mixed integer programming. The material usage is used to represent the economic dimension and the carbon dioxide equivalent is used to represent the environmental dimension. The computed supported efficient solutions provide reasonable trade-off solutions for the considered bicycle manufacturing problem.
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