scholarly journals Berth Allocation and Quay Crane Assignment for the Trade-off Between Service Efficiency and Operating Cost Considering Carbon Emission Taxation

2020 ◽  
Vol 54 (5) ◽  
pp. 1307-1331 ◽  
Author(s):  
Tingsong Wang ◽  
Yuquan Du ◽  
Debin Fang ◽  
Zhi-Chun Li
Keyword(s):  
Carbon Emission ◽  
Programming Model ◽  
Operating Cost ◽  
Maritime Transportation ◽  
Berth Allocation ◽  
Economic Interests ◽  
Service Efficiency ◽  
Emission Taxation ◽  
Quay Crane Assignment

To sustain the development of maritime transportation, “green ports,” which operate with a good balance between environmental impact and economic interests, have been the focus of port operators and government agencies and are required to look into energy saving and emission reduction initiatives. One such reduction strategy proposed by the International Maritime Organization suggested imposing a carbon emission tax on ports as a long-term solution to reduce carbon emissions, but this would definitely increase the operating cost of ports. Quay cranes (QCs), as one type of handling equipment, play an important role in the service efficiency and carbon emission of ports. Therefore, this paper makes an effort to explore the study of the integrated berth allocation and QC assignment problem with the consideration of carbon emission taxation. This problem is formulated as a biobjective integer programming model, aimed at minimizing the total completion delay of all tasks and the total operating costs for all QCs. Finally, numerical experiments are performed to assess the applicability of the proposed models and evaluate the efficiency of the developed solution algorithm.

Optimization Research of Berth Allocation and Quay Crane Assignment at Container Terminal Based on the Genetic Algorithm

2014 ◽  
Vol 505-506 ◽  
pp. 931-934
Author(s):  
Zhi Jun Gao ◽  
Jin Xin Cao ◽  
Qing Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Programming ◽  
Programming Model ◽  
Container Terminal ◽  
Mathematical Optimization ◽  
Berth Allocation ◽  
Assignment Problems ◽  
Nonlinear Programming Model ◽  
Mathematical Optimization Model ◽  
Quay Crane Assignment

In the operation of container terminal, berth allocation and quay crane assignment problems (BACAP) always prevent the container terminal from reducing time of ships in port and improving utilization of equipment. In this paper, the objective is to minimize total time of ships in port. Some reasonable and necessary hypotheses are proposed. The mathematical optimization model of BACAP based on the hypotheses is established. The genetic algorithm is used to solve the nonlinear programming model.

scholarly journals Berth Allocation and Quay Crane Assignment Under Uncertainties

2020 ◽  
Author(s):  
Caimao Tan ◽  
Junliang He ◽  
Yuancai Wang
Keyword(s):  
Stochastic Programming ◽  
Numerical Experiments ◽  
Programming Model ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Operations Planning ◽  
Proposed Model ◽  
Departure Time ◽  
Stochastic Programming Model ◽  
Quay Crane Assignment

The integration of berth allocation problem (BAP) and quay crane assignment problem (QCAP) is an cardinal seaside operations planning, which is susceptible to uncertainties, e.g. uncertain vessels arrival and maritime market. This paper addresses the integrated optimization of BAP and QCAP under uncertainties. A stochastic programming model is formulated for minimizing the waiting time and delay departure time of vessels. Besides, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model.

Taken For A Ride

2017 ◽  
Author(s):  
Matteo Rizzo
Keyword(s):  
Public Transport ◽  
Urban Poor ◽  
Dar Es Salaam ◽  
Political Organization ◽  
Bus Rapid Transit ◽  
The Political ◽  
Urban Experience ◽  
Economic Interests ◽  
Informal Economies

The growth of cities and informal economies are two central manifestations of globalization in the developing world. Taken for a Ride addresses both, drawing on long-term fieldwork in Dar es Salaam (Tanzania) and charting its public transport system’s journey from public to private provision. The book investigates this shift alongside the increasing deregulation of the sector and the resulting chaotic modality of public transport. It reviews state attempts to regain control over public transport, the political motivations behind these, and their inability to address its problems. The analysis documents how informal wage relations prevailed in the sector, and how their salience explains many of the inefficiencies of public transport. The changing political attitude of workers towards employers and the state is investigated: from an initial incapacity to respond to exploitation, to political organization and unionization, which won workers concessions on labour rights. A longitudinal study of workers throws light on patterns of occupational mobility in the sector. The book ends with an analysis of the political and economic interests that shaped the introduction of Bus Rapid Transit in Dar es Salaam and local resistance to it. Taken for a Ride is an interdisciplinary political economy of public transport, exposing the limitations of market fundamentalist and postcolonial scholarship on economic informality and the urban experience in developing countries, and its failure to locate the agency of the urban poor within their economic and political structures. It is both a contribution to and a call for the contextualized study of ‘actually existing neoliberalism’.

scholarly journals Optimal placement design for picking and packing in distribution centers

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica
Keyword(s):  
Optimal Allocation ◽  
Programming Model ◽  
Operating Cost ◽  
Nonlinear Integer Programming ◽  
Operating Costs ◽  
Optimal Placement ◽  
Distribution Centers ◽  
Suitable Space ◽  
Efficient Distribution

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.

Optimal berth allocation under regular and emergent vessel arrivals

2020 ◽  
pp. 147509022093788
Author(s):  
Abbas Al-Refaie ◽  
Hala Abedalqader
Keyword(s):  
Waiting Time ◽  
Container Terminal ◽  
Allocation Problem ◽  
Container Terminals ◽  
Future Research ◽  
Satisfaction Level ◽  
Berth Allocation ◽  
Scheduling Problems ◽  
Berth Allocation Problem ◽  
Quay Crane Assignment

This research proposes two optimization models to deal with the berth allocation problem. The first model considers the berth allocation problem under regular vessel arrivals to minimize the flow time of vessels in the marine container terminal, minimize the tardiness penalty costs, and maximize the satisfaction level of vessels’ operators on preferred times of departure. The second model optimizes the berth allocation problem under emergency conditions by maximizing the number of assigned vessels, minimizing the vessel’s waiting time, and maximizing the satisfaction level on the served ships. Two real examples are provided for model illustration under regular and emergent vessel arrivals. Results show that the proposed models effectively provide optimal vessel scheduling in the terminal, reduce costs at an acceptable satisfaction level of vessels’ operators, decrease the waiting time of vessels, and shorten the delay in departures under both regular and emergent vessel arrivals. In conclusion, the proposed models may provide valuable assistance to decision-makers in marine container terminals on determining optimal berth allocation under daily and emergency vessel arrivals. Future research considers quay crane assignment and scheduling problems.

scholarly journals Smart carbon monitoring platform under IoT-Cloud architecture for small cities in B5G

2021 ◽  
Author(s):  
He Zhang ◽  
Jianxun Zhang ◽  
Rui Wang ◽  
Yazhe Huang ◽  
Mengxiao Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Carbon Emission ◽  
Emission Measurement ◽  
Low Carbon ◽  
Time Data ◽  
Small Cities ◽  
Real Time Data ◽  
Monitoring Platform ◽  
Term Data

AbstractWith the rapid development of the Internet of Things (IoT) in the 5G age, the construction of smart cities around the world consequents on the exploration of carbon reduction path based on IoT technology is an important direction for global low carbon city research. Carbon dioxide emissions in small cities are usually higher than that in large and medium cities. However, due to the huge difference in data environment between small cities and Medium-large sized cities, the weak hardware foundation of the IoT, and the high input cost, the construction of a small city smart carbon monitoring platform has not yet been carried out. This paper proposes a real-time estimate model of carbon emissions at the block and street scale and designs a smart carbon monitoring platform that combines traditional carbon control methods with IoT technology. It can exist long-term data by using real-time data acquired with the sensing device. Therefore, the dynamic monitoring and management of low-carbon development in small cities can be achieved. The contributions are summarized as follows: (1) Intelligent thermoelectric systems, industrial energy monitoring systems, and intelligent transportation systems are three core systems of the monitoring platform. Carbon emission measurement methods based on sample monitoring, long-term data, and real-time data have been established, they can solve the problem of the high cost of IoT equipment in small cities. (2) Combined with long-term data, the real-time correction technology, they can dispose of the matter of differences in carbon emission measurement under diverse scales.

Population-based Metaheuristics for the Dynamic Minimum Cost Hybrid Berth Allocation Problem

2021 ◽  
Vol 30 (04) ◽  
pp. 2150017
Author(s):  
Nataša Kovač ◽  
Tatjana Davidović ◽  
Zorica Stanimirović
Keyword(s):  
Container Terminal ◽  
Mathematical Formulation ◽  
Minimum Cost ◽  
Population Based ◽  
Allocation Problem ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Metaheuristic Methods

This study considers the Dynamic Minimum Cost Hybrid Berth Allocation Problem (DMCHBAP) with fixed handling times of vessels. The objective function to be minimized consists of three components: costs of positioning, waiting, and tardiness of completion for all vessels. A mathematical formulation of DMCHBAP, based on Mixed Integer Linear Programming (MILP), is proposed and used within the framework of commercial CPLEX 12.3 solver. As the speed of finding high-quality solutions is of crucial importance for an efficient and reliable decision support system in container terminal, two population-based metaheuristic approaches to DMCHBAP are proposed: combined Genetic Algorithm (cGA) and improvement-based Bee Colony Optimization (BCOi). Both cGA and BCOi are evaluated and compared against each other and against state-of-the-art solution methods for DMCHBAP on five sets of problem instances. The conducted computational experiments and statistical analysis indicate that population-based metaheuristic methods represent promising approaches for DMCHBAP and similar problems in maritime transportation.

An Interval-Index-Oriented Intelligent Optimization Method and its Industrial Application

2011 ◽  
Vol 219-220 ◽  
pp. 546-550
Author(s):  
Ming Shan Cai ◽  
Ling Shuang Kong
Keyword(s):  
Optimal Control ◽  
Industrial Application ◽  
Programming Model ◽  
Optimization Method ◽  
Quality Indices ◽  
Reasoning Strategy ◽  
Goal Programming Model ◽  
Interval Goal Programming ◽  
Expert Reasoning

Based on the strong coupling and interval requirement of multiple quality indices, the interval-index-oriented optimization method is proposed to effectively realize the optimal control of alumina blending process. Firstly, the lexicographic interval goal programming model is built to describe the process requirements for quality indices. Then, based on the characteristics of the programming model, a kind of classificatory knowledge base is constructed by using the empirical knowledge accumulated in long-term production and the expert reasoning strategy is proposed to realize the optimal control of quality indexes with interval constraints. The results of industrial application shows that the proposed method can realize the optimal control of quality indices. It provides a good optimization mode for other blending processes of nonferrous metal production.

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