scholarly journals MILP formulations for highway petrol station replenishment in initiative distribution mode

2021 ◽  
Author(s):  
Xin-Tong Wei ◽  
Qi Liao ◽  
Hao-Ran Zhang ◽  
Yong-Tu Liang ◽  
Bo-Hong Wang ◽  
...  
Keyword(s):  
Task Assignment ◽  
Mixed Integer ◽  
Time Interval ◽  
Transport Costs ◽  
Petrol Station ◽  
Road Congestion ◽  
Distribution Process ◽  
Distribution Mode ◽  
Working Day ◽  
Operational Constraints

AbstractTo investigate highway petrol station replenishment in initiative distribution mode, this paper develops a mixed-integer linear programming (MILP) model with minimal operational costs that includes loading costs, unloading costs, transport costs and the costs caused by unpunctual distribution. Based on discrete representation, the working day is divided into equal time intervals, and the truck distribution process is decomposed into a pair of tasks including driving, standby, rest, loading and unloading. Each truck must execute one task during a single interval, and the currently executing task is closely related to the preceding and subsequent tasks. By accounting for predictive time-varying sales at petrol stations, real-time road congestion and a series of operational constraints, the proposed model produces the optimal truck dispatch, namely, a detailed task assignment for all trucks during each time interval. The model is tested on a real-world case of a replenishment system comprising eight highway petrol stations, one depot, one garage and eight trucks to demonstrate its applicability and accuracy.

scholarly journals A New Peak-Shaving Model Based on Mixed Integer Linear Programming with Variable Peak-Shaving Order

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 887
Author(s):  
Xianliang Cheng ◽  
Suzhen Feng ◽  
Yanxuan Huang ◽  
Jinwen Wang
Keyword(s):  
Linear Programming ◽  
Power Systems ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Time Interval ◽  
Renewable Energy Resources ◽  
Load Curve ◽  
Peak Shaving ◽  
Model Based

Peak-shaving is a very efficient and practical strategy for a day-ahead hydropower scheduling in power systems, usually aiming to appropriately schedule hourly (or in less time interval) power generations of individual plants so as to smooth the load curve while enforcing the energy production target of each plant. Nowadays, the power marketization and booming development of renewable energy resources are complicating the constraints and diversifying the objectives, bringing challenges for the peak-shaving method to be more flexible and efficient. Without a pre-set or fixed peak-shaving order of plants, this paper formulates a new peak-shaving model based on the mixed integer linear programming (MILP) to solve the scheduling problem in an optimization way. Compared with the traditional peak-shaving methods that need to determine the order of plants to peak-shave the load curve one by one, the present model has better flexibility as it can handle the plant-based operating zones and prioritize the constraints and objectives more easily. With application to six cascaded hydropower reservoirs on the Lancang River in China, the model is tested efficient and practical in engineering perspective.

Mapping properties of an asynchronous crop: the example of time interval between flowering and maturity of banana

2017 ◽  
Vol 8 (2) ◽  
pp. 481-486 ◽  
Author(s):  
J. Lamour ◽  
O. Naud ◽  
M. Lechaudel ◽  
B. Tisseyre
Keyword(s):  
Precision Agriculture ◽  
Development Stage ◽  
Production Data ◽  
Time Interval ◽  
Plant Responses ◽  
Spatial Structures ◽  
Kriging Method ◽  
New Methods ◽  
Operational Constraints ◽  
Banana Crops

Precision agriculture for banana crops has been little investigated so far. The main difficulty to implement precision agriculture methods lies in the asynchronicity of this crop: after a few cycles, each plant has its own development stage in the field. Indeed, maps of agronomical interest are difficult to produce from plant responses without implementing new methods. The present study explores the feasibility to derive a spatially relevant indicator from the date of flowering and the date of maturity (time to harvest). The time between these dates (TFM) may give insight in spatial distribution of vigor. The study was carried out using production data from 2015 acquired in a farm from Cameroon. Data from individual plants that flowered at different weeks were gathered so as to increase the density of TFM sampling. The temporal variability of TFM, which is induced by weather and operational constraints, was compensated by centering TFM data on their medians (TFMc). The mapping of TFMc was obtained using a classical kriging method. Spatial structures highlighted by TFMc either at the farm level or at the plot level, suggest that such maps could be used to support agronomic decisions.

scholarly journals A seismologically motivated survey of blasting activity in the northern Rhine area

2000 ◽  
Vol 79 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Klaus-G. Hinzen ◽  
Stefan Pietsch
Keyword(s):  
Charge Weight ◽  
Time Interval ◽  
Maximum Charge ◽  
Comprehensive Test Ban Treaty ◽  
Comprehensive Test ◽  
Explosive Charges ◽  
Chemical Explosions ◽  
Working Day ◽  
Test Ban ◽  
Natural Earthquakes

AbstractDiscrimination between quarry blasts and earthquakes has gained importance due to signature of the Comprehensive Test Ban Treaty. In this context, large chemical explosions are significant. In the routine analysis of data from local seismograph networks, discrimination between smaller blasts and micro-earthquakes is not always clear. Many quarries are in operation and blasts far outnumber natural earthquakes in the highly industrialized northern Rhine area.We compiled a list of active quarries in the Northern Rhine Area and mapped their locations. We then created a database from a questionnaire sent out to all quarries on the list. From the 33% of questionnaires that were returned, we discerned some representative values for the main blasting parameters and explosive consumption. In the study area of 72,000 km2, approx. 21,000 blasts are fired per year (80 per working day). Most of the blasts (72%) have total explosive charges between 400 and 4500 kg. Shots with charges above 10 tons are rare (20-30 per year). Some 80% of the blasts are ripple-fired with a nominal firing time interval of 20 ms.Based on empirical amplitude vs. distance curves from vibration control measurements, a relation between maximum charge weight per delay time, L (kg), and a ‘quarry blast’ magnitude, MQB, is derived: MQB = 0.6·log10(L) + 0.131. Using this relation and extrapolating the database from the questionnaire shows that for magnitudes between 1 and 2, blasts occur 200–250 times more frequently than micro-earthquakes in the Northern Rhine area.

Mixed Integer Programming Models on Scheduling Automated Stacking Cranes

2021 ◽  
Vol 8 (4) ◽  
pp. 11-33
Author(s):  
Amir Gharehgozli ◽  
Orkideh Gharehgozli ◽  
Kunpeng Li
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Recent Trend ◽  
Container Terminals ◽  
Programming Models ◽  
Mixed Integer ◽  
Global Supply Chains ◽  
Objective Functions ◽  
Operational Constraints ◽  
Automated Stacking Cranes

Automated deep-sea container terminals are the main hubs to move millions of containers in today's global supply chains. Terminal operators often decouple the landside and waterside operations by stacking containers in stacks perpendicular to the quay. Traditionally, a single automated stacking cranes (ASC) is deployed at each stack to handle containers. A recent trend is to use new configurations with more than one crane to improve efficiency. A variety of new configurations have been implemented, such as twin, double, and triple ASCs. In this paper, the authors explore and review the mixed integer programming models that have been developed for the stacking operations of these new configurations. They further discuss how these models can be extended to contemplate diverse operational constraints including precedence constraints, interference constraints, and other objective functions.

Coordinating lot sizing and integrated production and distribution scheduling with batch delivery and holding cost

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maedeh Bank ◽  
Mohammad Mahdavi Mazdeh ◽  
Mahdi Heydari ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Time Interval ◽  
Content Type ◽  
Integrated Production ◽  
Holding Costs ◽  
Integrated Production And Distribution ◽  
Distribution Scheduling ◽  
Production And Distribution

PurposeThe aim of this paper is to present a method for finding the optimum balance between sequence-dependent setup costs, holding costs, delivery costs and delay penalties in an integrated production–distribution system with lot sizing decisions.Design/methodology/approachTwo mixed integer linear programming models and an optimality property are proposed for the problem. Since the problem is NP-hard, a genetic algorithm reinforced with a heuristic is developed for solving the model in large-scale settings. The algorithm parameters are tuned using the Taguchi method.FindingsThe results obtained on randomly generated instances reveal a performance advantage for the proposed algorithm; it is shown that lot sizing can reduce the average cost of the supply chain up to 11.8%. Furthermore, the effects of different parameters and factors of the proposed model on supply chain costs are examined through a sensitivity analysis.Originality/valueAlthough integrated production and distribution scheduling in make-to-order industries has received a great deal of attention from researchers, most researchers in this area have treated each order as a job processed in an uninterrupted time interval, and no temporary holding costs are assumed. Even among the few studies where temporary holding costs are taken into consideration, none has examined the effect of splitting an order at the production stage (lot sizing) and the possibility of reducing costs through splitting. The present study is the first to take holding costs into consideration while incorporating lot sizing decisions in the operational production and distribution problem.

scholarly journals Collaborative Multidepot Petrol Station Replenishment Problem with Multicompartments and Time Window Assignment

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Guangcan Xu ◽  
Maozeng Xu ◽  
Yong Wang ◽  
Yong Liu ◽  
Qiguang Lv
Keyword(s):  
Energy Supply ◽  
Time Window ◽  
Programming Model ◽  
Urban Transportation ◽  
Mixed Integer ◽  
Supply Network ◽  
Transportation Energy ◽  
The Sustainable Development ◽  
Petrol Station ◽  
Chongqing City

Energy supply is an important system that affects the overall efficiency of urban transportation. To improve the system operational efficiency and reduce costs, we formulate and solve a collaborative multidepot petrol station replenishment problem with multicompartments and time window assignment by establishing a mixed-integer linear programming model. The hybrid heuristic algorithm composed of genetic algorithm and particle swarm optimization is used as a solution, and then the Shapley value method is applied to analyze the profit allocation of each petrol depot under different coalitions. The optimal membership sequence of the cooperation is determined according to the strict monotone path. To analyze and verify the effectiveness of the proposed method, a regional petrol supply network in Chongqing city in China is investigated. Through cooperation between petrol depots in the supply network, the utilization of customer clustering, time window coordination, and distribution truck sharing can significantly reduce the total operation costs and improve the efficiency of urban transportation energy supply. This approach can provide theoretical support for relevant government departments and enterprises to make optimal decisions. The implementation of the joint distribution of energy can promote the sustainable development of urban transportation.

scholarly journals Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode

2019 ◽  
Vol 11 (15) ◽  
pp. 4248 ◽  
Author(s):  
Jinghua Li ◽  
Hui Guo ◽  
Qinghua Zhou ◽  
Boxin Yang
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Water Drop ◽  
Time Windows ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Vehicle Routing And Scheduling ◽  
Routing And Scheduling ◽  
Distribution Process ◽  
The Cost

Timeliness of steel distribution centers can effectively ensure the smooth progress of ship construction, but the carbon emissions of vehicles in the distribution process are also a major source of pollution. Therefore, when considering the common cost of vehicle distribution, taking the carbon emissions of vehicles into account, this paper establishes a Mixed Integer Linear Programming (MILP) model called green vehicle routing and scheduling problem with simultaneous pickups and deliveries and time windows (GVRSP-SPDTW). An intelligent water drop algorithm is designed and improved, and compared with the genetic algorithm and traditional intelligent water drop algorithm. The applicability of the improved intelligent water drop algorithm is proven. Finally, it is applied to a specific example to prove that the improved intelligent water drop algorithm can effectively reduce the cost of such problems, thereby reducing the carbon emissions of vehicles in the distribution process, achieving the goals of reducing environmental pollution and green shipbuilding.

scholarly journals Centralized Ambulance Diversion Policy Using Rolling-Horizon Optimization Framework to Minimize Patient Tardiness

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 266
Author(s):  
Sohye Baek ◽  
Young Hoon Lee ◽  
Seong Hyeon Park
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Time Interval ◽  
Rolling Horizon ◽  
Decentralized Optimization ◽  
Hospital System ◽  
Ambulance Diversion ◽  
Optimization Framework ◽  
The Impact ◽  
Rolling Horizon Optimization

Ambulance diversion (AD) is a common method for reducing crowdedness of emergency departments by diverting ambulance-transported patients to a neighboring hospital. In a multi-hospital system, the AD of one hospital increases the neighboring hospital’s congestion. This should be carefully considered for minimizing patients’ tardiness in the entire multi-hospital system. Therefore, this paper proposes a centralized AD policy based on a rolling-horizon optimization framework. It is an iterative methodology for coping with uncertainty, which first solves the centralized optimization model formulated as a mixed-integer linear programming model at each discretized time, and then moves forward for the time interval reflecting the realized uncertainty. Furthermore, the decentralized optimization, decentralized priority, and No-AD models are presented for practical application, which can also show the impact of using the following three factors: centralization, mathematical model, and AD strategy. The numerical experiments conducted based on the historical data of Seoul, South Korea, for 2017, show that the centralized AD policy outperforms the other three policies by 30%, 37%, and 44%, respectively, and that all three factors contribute to reducing patients’ tardiness. The proposed policy yields an efficient centralized AD management strategy, which can improve the local healthcare system with active coordination between hospitals.

scholarly journals Task Assignment Algorithm Based on Trust in Volunteer Computing Platforms

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 244 ◽  
Author(s):  
Ling Xu ◽  
Jianzhong Qiao ◽  
Shukuan Lin ◽  
Ruihua Qi
Keyword(s):  
Completion Time ◽  
Fuzzy Model ◽  
Task Assignment ◽  
Experimental Results ◽  
Volunteer Computing ◽  
Time Interval ◽  
Reliability Model ◽  
Assignment Algorithm ◽  
Computing Platforms ◽  
Task Segmentation

In volunteer computing (VC), the expected availability time and the actual availability time provided by volunteer nodes (VNs) are usually inconsistent. Scheduling tasks with precedence constraints in VC under this situation is a new challenge. In this paper, we propose two novel task assignment algorithms to minimize completion time (makespan) by a flexible task assignment. Firstly, this paper proposes a reliability model, which uses a simple fuzzy model to predict the time interval provided by a VN. This reliability model can reduce inconsistencies between the expected availability time and actual availability time. Secondly, based on the reliability model, this paper proposes an algorithm called EFTT (Earliest Finish Task based on Trust, EFTT), which can minimize makespan. However, EFTT may induce resource waste in task assignment. To make full use of computing resources and reduce task segmentation rate, an algorithm IEFTT (improved earliest finish task based on trust, IEFTT) is further proposed. Finally, experimental results verify the efficiency of the proposed algorithms.

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