scholarly journals Optimization for Stop Plan of Passenger-Like Container Train with Container Distributions and Train Utilization Rates

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yang Xia ◽  
Yuguang Wei ◽  
Yihuan Lai ◽  
Qi Zhang
Keyword(s):  
Mixed Integer Linear Programming ◽  
Numerical Experiments ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Utilization Rate ◽  
Container Transportation ◽  
Accumulation Time ◽  
Railway Line ◽  
Proposed Model ◽  
Novel Concept

The railway container transportation is attracting more and more attention in China. In order to improve the service quality, a novel concept of passenger-like container train is proposed, which can reduce the accumulation time of containers at the origin station and increase the train frequency compared with the traditional container through train. With the aim of generating optimal operation strategies for passenger-like container trains, this paper establishes an optimization model for the train stop plan problem, in which the objective is to minimize the total number of stops. In addition, the specific container-to-train distribution and the utilization rate of each individual train are considered. The proposed model is a mixed-integer linear programming one, which can be solved by using the CPLEX solver. Finally, the numerical experiments are performed to test the effectiveness of our model by using a simple railway line and the China Railway Express corridor as examples. The results prove the advantages of our method.

How can mixed integer linear programming assist dairy manufacturers by integrating supply decisions and production planning?

2021 ◽  
Vol 11 (2) ◽  
pp. 178-193
Author(s):  
Juliana Emidio ◽  
Rafael Lima ◽  
Camila Leal ◽  
Grasiele Madrona
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Dairy Products ◽  
Raw Milk ◽  
Mixed Integer ◽  
Content Type ◽  
Proposed Model ◽  
By Products

PurposeThe dairy industry needs to make important decisions regarding its supply chain. In a context with many available suppliers, deciding which of them will be part of the supply chain and deciding when to buy raw milk is key to the supply chain performance. This study aims to propose a mathematical model to support milk supply decisions. In addition to determining which producers should be chosen as suppliers, the model decides on a milk pickup schedule over a planning horizon. The model addresses production decisions, inventory, setup and the use of by-products generated in the raw milk processing.Design/methodology/approachThe model was formulated using mixed integer linear programming, tested with randomly generated instances of various sizes and solved using the Gurobi Solver. Instances were generated using parameters obtained from a company that manufactures dairy products to test the model in a more realistic scenario.FindingsThe results show that the proposed model can be solved with real-world sized instances in short computational times and yielding high quality results. Hence, companies can adopt this model to reduce transportation, production and inventory costs by supporting decision making throughout their supply chains.Originality/valueThe novelty of the proposed model stems from the ability to integrate milk pickup and production planning of dairy products, thus being more comprehensive than the models currently available in the literature. Additionally, the model also considers by-products, which can be used as inputs for other products.

scholarly journals A multi-objective approach under uncertainty for designing a green meat supply chain network

2021 ◽  
Author(s):  
Fatemeh Mohebalizadehgashti
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Environmental Concerns ◽  
Supply Chain Network ◽  
Food Supply Chain ◽  
Multi Objective ◽  
Proposed Model

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this thesis, environmental concerns with a mathematical model are investigated to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. A multi-objective mixed-integer linear programming formulation is developed to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization. To demonstrate the efficiency of the proposed optimization model, a green meat supply chain network for Southern Ontario, Canada is designed. A solution approach based on augmented εε-constraint method is developed for solving the proposed model. As a result, a set of Pareto-optimal solutions is obtained. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature. Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented εε-constraint.

scholarly journals Timed Automata Relaxation for Reachability

2021 ◽  
pp. 291-310
Author(s):  
Jaroslav Bendík ◽  
Ahmet Sencan ◽  
Ebru Aydin Gol ◽  
Ivana Černá
Keyword(s):  
Mixed Integer Linear Programming ◽  
Timed Automata ◽  
Mixed Integer ◽  
Timing Constraints ◽  
System Specification ◽  
Minimal Set ◽  
Novel Concept ◽  
Time Systems ◽  
Sufficient Reduction ◽  
Correct Structure

AbstractTimed automata (TA) have shown to be a suitable formalism for modeling real-time systems. Moreover, modern model-checking tools allow a designer to check whether a TA complies with the system specification. However, the exact timing constraints of the system are often uncertain during the design phase. Consequently, the designer is able to build a TA with a correct structure, however, the timing constraints need to be tuned to make the TA comply with the specification.In this work, we assume that we are given a TA together with an existential property, such as reachability, that is not satisfied by the TA. We propose a novel concept of a minimal sufficient reduction (MSR) that allows us to identify the minimal set S of timing constraints of the TA that needs to be tuned to meet the specification. Moreover, we employ mixed-integer linear programming to actually find a tuning of S that leads to meeting the specification.

An Efficient Heuristic Algorithm for Solving Crane Scheduling Problem

2013 ◽  
Vol 442 ◽  
pp. 443-449
Author(s):  
Xie Xie ◽  
Yan Ping Li ◽  
Yong Yue Zheng ◽  
Xiao Li Li
Keyword(s):  
Heuristic Algorithm ◽  
Mixed Integer Linear Programming ◽  
Numerical Experiments ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Crane Scheduling ◽  
Technological Requirement ◽  
Iron And Steel ◽  
Analytical Properties ◽  
Upper Level

This paper focuses on a single crane scheduling problem which is motivated by cooled-rolling material warehouse in the iron and steel enterprise. As storage technological requirement, coils have been stored on the pre-specified position in two levels. If a demanded coil is in the upper level, it can be picked up directly. If a demanded coil in the lower level is blocked by un-demanded coils, the coil can not be transported until all the blocking coils are shuffled to another position. Our problem combines transportation and shuffling simultaneously for crane to pick up all demanded coils as early as possible to designated place (makespan). We first propose a mixed integer linear programming (MILP) model. Some analytical properties are further provided. Based on these properties, we propose a polynomial-time heuristic algorithm. Numerical experiments are carried out to confirm our proposed methods can provide high quality solutions.

scholarly journals Task Scheduling for Multiunit Parallel Test Using Mixed-Integer Linear Programming

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhao Yang ◽  
Han-Shan Xiao ◽  
Rui Guan ◽  
Yang Yang ◽  
Hong-Liang Ji
Keyword(s):  
Linear Programming ◽  
Task Scheduling ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Search Space ◽  
Mixed Integer ◽  
Utilization Rate ◽  
Parallel Test ◽  
Second Procedure ◽  
Space Method

Parallel test is an efficient approach for improving test efficiency in the aerospace field. To meet the challenges of implementing multiunit parallel test in practical projects, this paper presented a mixed-integer linear programming (MILP) model for solving the task scheduling problem. A novel sequence-based iterative (SBI) method is proposed to solve the model in reasonable time. The SBI method is composed of an implied sequence finding procedure (ISF) and a sequence-based iterative optimization (SBIO) procedure. The first procedure can reduce the search space by fixing free sequence variables according to the original test flowcharts, and the second procedure can solve the model iteratively in a reasonable amount of time. In addition, two indexes, namely, speed rate and average resource utilization rate, are introduced to evaluate the proposed methods comprehensively. Computational results indicate that the proposed method performs well in real-world test examples, especially for larger examples that cannot be solved by the full-space method. Furthermore, it is proved that the essence of the parallel test is trading space for time.

scholarly journals Integrated Optimization on Assortment Packing and Collaborative Shipping for Fashion Clothing

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qianying Wang ◽  
Yiping Jiang ◽  
Yang Liu
Keyword(s):  
Numerical Experiments ◽  
Optimization Problem ◽  
Programming Model ◽  
Social Resources ◽  
Mixed Integer ◽  
Integrated Optimization ◽  
Proposed Model ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
Effectiveness And Efficiency

With the diversification of customer’s demand and the shortage of social resources, meeting diverse requirements of customers and reducing logistics costs have attracted great attention in logistics area. In this paper, we address an integrated optimization problem that combines fashion clothing assortment packing with collaborative shipping simultaneously. We formulate this problem as a mixed integer nonlinear programming model (MINLP) and then convert the proposed model into a simplified model. We use LINGO 11.0 to solve the transformed model. Numerical experiments have been conducted to verify the effectiveness and efficiency of the proposed model, and the numerical results show that the proposed model is beneficial to the fashion clothing assortment packing and collaborative shipping planning.

scholarly journals Rescheduling Strategy for Berth Planning in Container Terminals: An Empirical Study from Korea

2021 ◽  
Vol 9 (5) ◽  
pp. 527
Author(s):  
Armi Kim ◽  
Hyun-Ji Park ◽  
Jin-Hyoung Park ◽  
Sung-Won Cho
Keyword(s):  
Mixed Integer Linear Programming ◽  
Arrival Time ◽  
Programming Model ◽  
Container Terminal ◽  
Container Terminals ◽  
Mixed Integer ◽  
Berth Allocation ◽  
Trade Volume ◽  
Penalty Costs ◽  
Proposed Model

The rapid increase in international trade volume has caused frequent fluctuation of the vessels’ arrival time in container terminals. In order to solve this problem, this study proposes a methodology for rescheduling berth and quay cranes caused by updated information on the arrival time of vessels. A mixed-integer linear programming model was formulated for the berth allocation and crane assignment problem, and we solved the problem using a rolling-horizon approach. Numerical experiments were conducted under three scenarios with empirical data from a container terminal located in Busan, Korea. The experiments revealed that the proposed model reduces penalty costs and overall delayed departure time compared to the results of the terminal planner.

scholarly journals Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hafiz Abd ul Muqeet ◽  
Hafiz Mudassir Munir ◽  
Aftab Ahmad ◽  
Intisar Ali Sajjad ◽  
Guang-Jun Jiang ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Solar Irradiance ◽  
Distribution System ◽  
Energy Demand ◽  
Mathematical Problem ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Proposed Model

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

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