scholarly journals Speed Optimization for Container Ship Fleet Deployment Considering Fuel Consumption

2021 ◽  
Vol 13 (9) ◽  
pp. 5242
Author(s):  
Chao-Feng Gao ◽  
Zhi-Hua Hu
Keyword(s):  
Energy Consumption ◽  
Approximation Algorithm ◽  
Fuel Consumption ◽  
Programming Model ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Container Ship ◽  
Trade Offs ◽  
Speed Optimization ◽  
Fleet Deployment

In recent years, low energy consumption has become the common choice of economic development in the world. In order to control energy consumption, shipping line speed optimization has become strategically important. to reduce fuel consumption, this study optimizes the container ship fleet deployment problem by adopting the strategy of adjusting each leg of each route’s sailing speed. To calculate fuel consumption more accurately, both sailing speed and the ship's payload are considered. A multi-objective mixed integer nonlinear programming model is established to optimize the allocation of liner routes with multiple ship types on multiple routes. A linear outer-approximation algorithm and an improved piecewise linear approximation algorithm are used for linearization. If segments of an interval increase, the results will be more accurate but will take more time to compute. As fuel prices increase, to make trade-offs among economic and environmental considerations, the shipping company is adopting the “adding ship and slow down its speed” strategy, which verifies the validity and applicability of the established model.

scholarly journals Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption

2019 ◽  
Vol 11 (11) ◽  
pp. 3127 ◽  
Author(s):  
Tarik Chargui ◽  
Abdelghani Bekrar ◽  
Mohamed Reghioui ◽  
Damien Trentesaux
Keyword(s):  
Energy Consumption ◽  
Programming Model ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Optimal Solutions ◽  
Multi Objective ◽  
Sustainable Logistics ◽  
Cross Docking ◽  
Physical Internet

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed.

scholarly journals Extending and Solving the Refrigerated Routing Problem

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6214
Author(s):  
Sara Ceschia ◽  
Luca Di Gaspero ◽  
Antonella Meneghetti
Keyword(s):  
Fuel Consumption ◽  
Programming Model ◽  
Waiting Times ◽  
Hill Climbing ◽  
Mixed Integer ◽  
Routing Problem ◽  
Climate Conditions ◽  
Life Style Changes ◽  
Constraint Programming Model ◽  
High Level

In recent years, cold food chains have shown an impressive growth, mainly due to customers life style changes. Consequently, the transportation of refrigerated food is becoming a crucial aspect of the chain, aiming at ensuring efficiency and sustainability of the process while keeping a high level of product quality. The recently defined Refrigerated Routing Problem (RRP) consists of finding the optimal delivery tour that minimises the fuel consumption for both the traction and the refrigeration components. The total fuel consumption is related, in a complex way, to the distance travelled, the vehicle load and speed, and the outdoor temperature. All these factors depend, in turn, on the traffic and the climate conditions of the region where deliveries take place and they change during the day and the year. The original RRP has been extended to take into account also the total driving cost and to add the possibility to slow down the deliveries by allowing arbitrarily long waiting times when this is beneficial for the objective function. The new RRP is formulated and solved as both a Mixed Integer Programming and a novel Constraint Programming model. Moreover, a Local Search metaheuristic technique (namely Late Acceptance Hill Climbing), based on a combination of different neighborhood structures, is also proposed. The results obtained by the different solution methods on a set of benchmarks scenarios are compared and discussed.

Integrated Scheduling Optimization of Handling Operations in Container Terminal

2013 ◽  
Vol 380-384 ◽  
pp. 4775-4781
Author(s):  
Ji Feng Qian ◽  
Xiao Ning Zhu ◽  
Zhan Dong Liu
Keyword(s):  
Approximate Solution ◽  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Operating Efficiency ◽  
Container Ship ◽  
Scheduling Problem ◽  
Scheduling Optimization ◽  
Integrated Scheduling ◽  
Different Types

In order to improve the efficiency of the handling operations equipment in container terminal, reduce the waiting time of container ship in Port, this paper researches the integrated scheduling of the different types of handling equipment in container terminal, considers the constraints of different handling equipment impact between each other, build a mixed integer programming model, presents a heuristic algorithm for the of the scheduling problem and gets the approximate solution. The results show that the integrated scheduling can effectively reduce the time of the ship staying in port, and improve the overall operating efficiency of the port.

scholarly journals The Effect of Nonlinear Charging Function and Line Change Constraints on Electric Bus Scheduling

2021 ◽  
Vol 33 (4) ◽  
pp. 527-538
Author(s):  
Aijia Zhang ◽  
Tiezhu Li ◽  
Ran Tu ◽  
Changyin Dong ◽  
Haibo Chen ◽  
...  
Keyword(s):  
Real World ◽  
Control Method ◽  
Large Deviation ◽  
Programming Model ◽  
Piecewise Linear ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Effective Control ◽  
Electric Bus ◽  
Bus Schedule

The recharging plans are a key component of the electric bus schedule. Since the real-world charging function of electric vehicles follows a nonlinear relationship with the charging duration, it is challenging to accurately estimate the charging time. To provide a feasible bus schedule given the nonlinear charging function, this paper proposes a mixed integer programming model with a piecewise linear charging approximation and multi-depot and multi-vehicle type scheduling. The objective of the model is to minimise the total cost of the schedule, which includes the vehicle purchasing cost and operation cost. From a practical point of view, the number of line changes of each bus is also taken as one of the constraints in the optimisation. An improved heuristic algorithm is then proposed to find high-quality solutions of the problem with an efficient computation. Finally, a real-world dataset is used for the case study. The results of using different charging functions indicate a large deviation between the linear charging function and the piecewise linear approximation, which can effectively avoid the infeasible bus schedules. Moreover, the experiments show that the proposed line change constraints can be an effective control method for transit operators.

Train Scheduling Method to Reduce Substation Energy Consumption and Peak Power of Metro Transit Systems

2021 ◽  
pp. 036119812097467
Author(s):  
Bo Jin ◽  
Xiaoyun Feng ◽  
Qingyuan Wang ◽  
Pengfei Sun ◽  
Qian Fang
Keyword(s):  
Energy Consumption ◽  
Optimization Model ◽  
Peak Power ◽  
Programming Model ◽  
Rapid Development ◽  
Mixed Integer ◽  
Power Requirement ◽  
Transit Systems ◽  
Train Scheduling ◽  
Timetable Optimization

The rapid development of metro transit systems brings very significant energy consumption, and the high service frequency of metro trains increases the peak power requirement, which affects the operation of systems. Train scheduling optimization is an effective method to reduce energy consumption and substation peak power by adjusting timetable parameters. This paper proposes a train timetable optimization model to coordinate the operation of trains. The overlap time between accelerating and braking phases is maximized to improve the utilization of regenerative braking energy (RBE). Meanwhile, the overlap time between accelerating phases is minimized to reduce the substation peak power. In addition, the timetable optimization model is rebuilt into a mixed integer linear programming model by introducing logical and auxiliary variables, which can be solved by related solvers effectively. Case studies based on one of Guangzhou Metro Lines indicate that, for all-day operation, the utilization of RBE would likely be improved on the order of 23%, the substation energy consumption would likely be reduced on the order of 14%, and the duration of substation peak power would likely be reduced on the order of 66%.

scholarly journals Mixed-Integer Linear Programming Model by Linear Approximation for a Strike Package-to-Target Assignment Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Heungseob Kim
Keyword(s):  
Linear Programming ◽  
Linear Approximation ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Heterogeneous Vehicle Routing Problem ◽  
Target Assignment ◽  
Milp Model

This study deals with an aircraft-to-target assignment (ATA) problem considering the modern air operation environment, such as the strike package concept, multiple targets for a sortie, and the strike packages’ survivability. For the ATA problem, this study introduces a novel mathematical model in which a heterogeneous vehicle routing problem (HVRP) and a weapon-to-target assignment (WTA) problem are conceptually integrated. The HVRP generates the flight routes for strike packages because this study confirms that the survivability of a strike package depends on the path, and the WTA problem evaluates the likelihood of successful target destruction of assigned weapons. Although the first version of the model is developed as a mixed-integer nonlinear programming (MINLP) model, this study attempts to convert it to a mixed-integer linear programming (MILP) model using the logarithmic transformation and piecewise linear approximation methods. For an ATA problem, this activity could provide an opportunity to use the excellent existing algorithms for searching the optimal solution of LP models. To maximize the operational effectiveness, the MILP model simultaneously determines the following for each strike package: (a) composition type, (b) targets, (c) flight route, (d) types, and (e) quantity of weapons for each target.

scholarly journals An Optimization Approach to the Intermodal Transportation Network in Fruit Cold Chain, Considering Cost, Quality Degradation and Carbon Dioxide Footprint

2018 ◽  
Vol 25 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Qianli Ma ◽  
Wenyuan Wang ◽  
Yun Peng ◽  
Xiangqun Song
Keyword(s):  
Carbon Dioxide ◽  
Programming Model ◽  
Cost Minimization ◽  
Network Planning ◽  
Cold Chain ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Intermodal Transportation ◽  
Quality Degradation ◽  
Trade Offs

AbstractThis model optimizes port hinterland intermodal refrigerated container flows, considering both cost and quality degradation, which is distinctive from the previous literature content in a way that it quantifies the influence of carbon dioxide (CO2) emission in different setting temperature on intermodal network planning. The primary contribution of this paper is that the model is beneficial not only to shippers and customers for the novel service design, but also offer, for policy-makers of the government, insights to develop inland transport infrastructures in consideration of intermodal transportation. The majority of models of multimodal system have been established with an objective of cost minimization for normal commodities. As the food quality is possible to be influenced by varying duration time required for the storage and transportation, and transportation accompanied with refrigeration producing more CO2emission, this paper aims to address cost minimization and quality degradation minimization within the constraint of CO2footprint. To achieve this aim, we put the quality degradation model in a mixed-integer linear programming model used for intermodal network planning for cold chain. The example of Dalian Port and Yingkou Port offer insight into trade-offs between transportation temperature and transport mode considering CO2footprint. Furthermore, the model can offer a useful reference for other regions with the demand for different imported food, which requires an uninterrupted cold chain during the transportation and storage.

scholarly journals A Green Transportation Planning Approach for Coal Heavy-Haul Railway System by Simultaneously Optimizing Energy Consumption and Capacity Utilization

2021 ◽  
Vol 13 (8) ◽  
pp. 4173
Author(s):  
Jianjun Fu ◽  
Junhua Chen
Keyword(s):  
Energy Consumption ◽  
Optimization Model ◽  
Programming Model ◽  
Short Form ◽  
Capacity Utilization ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Trajectory Data ◽  
Heavy Haul ◽  
Heavy Haul Railway

Coal heavy-haul railway has been aiming at maximizing capacity utilization, but ignoring energy consumption for a long time. With the focus on green production, heavy-haul railways need transportation organization plans that can balance energy consumption and capacity utilization. Based on this, this paper proposes a data mining + optimization framework that uses train trajectory data to estimate train energy consumption and then uses a mixed integer programming model to simultaneously optimize plans from energy and capacity aspects. We use Gaussian distribution to describe features of energy consumption under different situations, and build a multi-dimensional cube to store these features to connect with the optimization model. In addition, a branch-and-bound algorithm is design to solve the optimization model. From the sensitivity analyses we can conclude that (1) shortening the departure interval from 13 min to 9 min will generate more energy consumption, about 3.6%; (2) combining short-form trains (50 units) with long-form trains (100 units) while increasing the carrying capacity will generate more energy consumption, about 5~14%; and (3) by controlling weights of the optimization model, capacity–energy-balanced plans can be obtained. The results can contribute to improving the sustainability of railways.

scholarly journals A rich vehicle routing problem arising in the replenishment of automated teller machines

2018 ◽  
Vol 8 (2) ◽  
pp. 276-287
Author(s):  
Çağrı Koç ◽  
Mehmet Erbaş ◽  
Eren Ozceylan
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Practical Problem ◽  
Programming Model ◽  
Optimization Method ◽  
Mixed Integer ◽  
Routing Problem ◽  
Automated Teller Machines ◽  
Trade Offs ◽  
Multiple Depots

This paper introduces, models, and solves a rich vehicle routing problem (VRP) motivated by the case study of replenishment of automated teller machines (ATMs) in Turkey. In this practical problem, commodities can be taken from the depot, as well as from the branches to efficiently manage the inventory shortages at ATMs. This rich VRP variant concerns with the joint multiple depots, pickup and delivery, multi-trip, and homogeneous fixed vehicle fleet. We first mathematically formulate the problem as a mixed-integer linear programming model. We then apply a Geographic Information System (GIS)-based solution method, which uses a tabu search heuristic optimization method, to a real dataset of one of the major bank. Our numerical results show that we are able to obtain solutions within reasonable solution time for this new and challenging practical problem. The paper presents computational and managerial results by analyzing the trade-offs between various constraints.

scholarly journals OPTIMIZATION OF SHIP SPEED AND FLEET DEPLOYMENT UNDER CARBON EMISSIONS POLICIES FOR CONTAINER SHIPPING

Transport ◽  
2019 ◽  
Vol 34 (3) ◽  
pp. 260-274 ◽  
Author(s):  
Yuwei Xing ◽  
Hualong Yang ◽  
Xuefei Ma ◽  
Yan Zhang
Keyword(s):  
Carbon Emissions ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Carbon Tax ◽  
Mixed Integer ◽  
Container Shipping ◽  
Nonlinear Programming Model ◽  
Annealing Algorithm ◽  
Ship Speed ◽  
Fleet Deployment

In this paper, under the consideration of two carbon emissions policies, the issues of optimizing ship speed and fleet deployment for container shipping were addressed. A mixed-integer nonlinear programming model of ship speed and fleet deployment was established with the objective of minimising total weekly operating costs. A simulated annealing algorithm was proposed to solve the problem. An empirical analysis was conducted with the data selected from the benchmark suite. The applicability and effectiveness of the established model and its algorithm are verified by the results. According to the results, two policies of the cap-and-trade programme and the carbon tax can better optimize the results of the ship speed and fleet deployment problem to achieve the goal of reducing carbon emissions. The research remarks in this paper will provide a solution for container shipping companies to make optimized decisions under carbon emissions policies.

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