scholarly journals Vehicles Allocation for Fruit Distribution Considering CO2 Emissions and Decisions on Subcontracting

2018 ◽  
Vol 10 (7) ◽  
pp. 2449 ◽  
Author(s):  
Rafael Tordecilla-Madera ◽  
Andrés Polo ◽  
Adrián Cañón
Keyword(s):  
Co2 Emissions ◽  
Carbon Emissions ◽  
Urban Areas ◽  
Co2 Emission ◽  
Programming Model ◽  
Pareto Frontier ◽  
Operating Costs ◽  
Mixed Integer ◽  
Conflicting Objectives ◽  
Constraint Method

An important problem in rural-area supply chains is how to transport the harvested fruit to urban areas. Low- and medium-capacity vehicles are used in Colombia to carry out this activity. Operating them comes with an inherent cost and generates carbon emissions. Normally, minimizing operating costs and minimizing carbon emissions are conflicting objectives to allocate such vehicles efficiently in any of the supply chain echelons. We designed a multi-objective mixed-integer programming model to address this problem and solved it via the ε-constraint method. It includes decisions mainly about quantities of fruit to transport and store, types of vehicles to allocate according to their capacities, CO2 emission levels of these vehicles, and subcontracting on the collection process. The main results show two schedules for allocating the vehicles, showing minimum and maximum CO2 emissions. Minimum CO2 emissions scheme require subcontracting and the maximum CO2 scheme does not. Then, a Pareto frontier shows that CO2 emissions level are inversely proportional to total management cost for different scenarios in which fruit supply was modified.

Multicriteria Synthesis of Trigeneration Systems Assisted With Renewable Energy Sources and Thermal Energy Storage

2017 ◽  
Author(s):  
Eduardo A. Pina ◽  
Miguel A. Lozano ◽  
Luis M. Serra
Keyword(s):  
Co2 Emissions ◽  
Energy Demand ◽  
High Efficiency ◽  
Programming Model ◽  
Environmental Concern ◽  
Renewable Energy Sources ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Trade Off ◽  
Conflicting Objectives

The increasing world energy demand as a result of society development brings forth a growing environmental concern. The use of high-efficiency alternative systems is becoming progressively more interesting due to economic reasons and regional incentives. The issue of finding the best configuration that minimizes total annual cost is not enough anymore, as the environmental concern has become one of the objectives in the synthesis of energy systems. The minimization of costs is often contradictory to the minimization of environmental impact. Multi-objective optimization tackles the conflicting objectives issue by providing a set of trade-off solutions, or Pareto solutions, that can be examined by the decision maker in order to choose the best configuration for the given scenario. The present work proposes a mixed integer linear programming model for the synthesis of a trigeneration system that must attend the electricity, heat, and cooling demands of a multifamily building complex in Zaragoza, Spain. The objective functions to be minimized are the overall annual costs and the overall annual CO2 emissions, considering investment, maintenance and operation costs. As a first approach, the single-objective configurations for each objective function are evaluated. Then, the Pareto frontier is obtained for the minimization of total annual costs and total annual CO2 emissions, allowing to obtain the best trade-off configuration, which brings results close to the optimal single objectives. It is worth mentioning that the treatment of the energy prices was simplified in order to keep on the same level of detail as energy CO2 emissions, which are given only on an annual basis. On the other hand, the optimization model developed can be further complicated in order to consider more complex situations.

Research on Remanufacturing Closed-Loop Logistics Network Design under Low-Carbon Restriction

2012 ◽  
Vol 159 ◽  
pp. 224-234
Author(s):  
Ya Can Wang ◽  
Tao Lu ◽  
Chun Hua Gao ◽  
Chun Hui Zhang ◽  
Chi Chen
Keyword(s):  
Network Design ◽  
Co2 Emission ◽  
Closed Loop ◽  
Programming Model ◽  
Pareto Frontier ◽  
Mixed Integer ◽  
Low Carbon ◽  
Waste Generation ◽  
Low Carbon Economy ◽  
Logistics Network

In this paper we study how to trade off the economic and ecological effects in the remanufacturing closed-loop logistics network design in the context of low-carbon economy. We establish a multi-objective mixed integer linear programming model to find the optimal facility locations and materials flow allocation. In the objective function, we set three minimum targets: economic cost, CO2 emission and waste generation. Through an iterative algorithm, we get the Pareto Frontier of our problem. In the numeric study, we find that in order to achieve a Pareto improvement over an original system, three of the critical rates (i.e. return rate, recovery rate, and cost substitute rate) should be increased. Also, to meet the need of low-carbon dioxide, we plot an iso-CO2 emission curve in which decision makers have a series of optimal choices with the same CO2 emission but different cost and waste generation. Each choice may have different network design but all of these are Pareto optimal solutions, which provide a comprehensive evaluation of both economics and ecology for the decision making.

Multi-Objective Pricing Optimization for a High-Speed Rail Network Under Competition

2019 ◽  
Vol 2673 (7) ◽  
pp. 215-226 ◽  
Author(s):  
Huizhuo Cao ◽  
Xuemei Li ◽  
Vikrant Vaze ◽  
Xueyan Li
Keyword(s):  
High Speed ◽  
Programming Model ◽  
Pareto Frontier ◽  
Multiple Objectives ◽  
Multi Objective Optimization ◽  
High Speed Rail ◽  
Multi Objective ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Single Objective

Multi-objective pricing of high-speed rail (HSR) passenger fares becomes a challenge when the HSR operator needs to deal with multiple conflicting objectives. Although many studies have tackled the challenge of calculating the optimal fares over railway networks, none of them focused on characterizing the trade-offs between multiple objectives under multi-modal competition. We formulate the multi-objective HSR fare optimization problem over a linear network by introducing the epsilon-constraint method within a bi-level programming model and develop an iterative algorithm to solve this model. This is the first HSR pricing study to use an epsilon-constraint methodology. We obtain two single-objective solutions and four multi-objective solutions and compare them on a variety of metrics. We also derive the Pareto frontier between the objectives of profit and passenger welfare to enable the operator to choose the best trade-off. Our results based on computational experiments with Beijing–Shanghai regional network provide several new insights. First, we find that small changes in fares can lead to a significant improvement in passenger welfare with no reduction in profitability under multi-objective optimization. Second, multi-objective optimization solutions show considerable improvements over the single-objective optimization solutions. Third, Pareto frontier enables decision-makers to make more informed decisions about choosing the best trade-offs. Overall, the explicit modeling of multiple objectives leads to better pricing solutions, which have the potential to guide pricing decisions for the HSR operators.

scholarly journals Research on Optimization and Design of Sustainable Urban Underground Logistics Network Framework

2020 ◽  
Vol 12 (21) ◽  
pp. 9147
Author(s):  
Hairui Wei ◽  
Anlin Li ◽  
Nana Jia
Keyword(s):  
Hybrid Method ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Programming Model ◽  
Mixed Integer ◽  
Set Cover ◽  
Exhaust Emission ◽  
Logistics Network ◽  
Design And Optimization ◽  
Fuzzy Clustering Method

As a new mode of transportation, the underground logistics system (ULS) has become one of the solutions to the problems of environmental pollution and traffic congestion. Considering the environmental and economic factors in urban logistics, this paper conducts comprehensive design and optimization research on the network nodes and passages of urban underground logistics and proposes a relatively complete framework for a sustainable underground logistics network. A hybrid method is proposed, which includes the set cover model used to perform the first location of urban underground logistics nodes, the fuzzy clustering method applied to classify the located logistics nodes into the first-level and second-level nodes considering the congestion in different urban areas of the city and a mixed integer programming model proposed to optimize and design the underground logistics passage to find optimal passage parameters at every underground logistics node. Based on the above hybrid method, a sustainable underground logistics network framework including all-levels logistics nodes and passages is formed, with a subdistrict of Nanjing as a case study. The discussion of results shows that this underground logistics network framework proposal is very effective in reducing logistics time cost, exhaust emission and congestion cost. It provides support for decisions in the design and development of urban sustainable underground logistics networks.

scholarly journals Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

2020 ◽  
Vol 10 (12) ◽  
pp. 4362 ◽  
Author(s):  
Junsu Kim ◽  
Hongbin Moon ◽  
Hosang Jung
Keyword(s):  
Urban Areas ◽  
Programming Model ◽  
Computation Time ◽  
Intelligent Transportation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Logistics System ◽  
Proposed Model ◽  
Optimality Gap ◽  
Good Operation

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

scholarly journals A Robust Mixed-Integer Linear Programming Model for Sustainable Collaborative Distribution

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2318
Author(s):  
Islem Snoussi ◽  
Nadia Hamani ◽  
Nassim Mrabti ◽  
Lyes Kermad
Keyword(s):  
Linear Programming ◽  
Co2 Emissions ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Distribution Network ◽  
Uncertainty Budget ◽  
Interval Uncertainty ◽  
Network Design Problem ◽  
Mixed Integer

In this paper, we propose robust optimisation models for the distribution network design problem (DNDP) to deal with uncertainty cases in a collaborative context. The studied network consists of collaborative suppliers who satisfy their customers’ needs by delivering their products through common platforms. Several parameters—namely, demands, unit transportation costs, the maximum number of vehicles in use, etc.—are subject to interval uncertainty. Mixed-integer linear programming formulations are presented for each of these cases, in which the economic and environmental dimensions of the sustainability are studied and applied to minimise the logistical costs and the CO2 emissions, respectively. These formulations are solved using CPLEX. In this study, we propose a case study of a distribution network in France to validate our models. The obtained results show the impacts of considering uncertainty by comparing the robust model to the deterministic one. We also address the impacts of the uncertainty level and uncertainty budget on logistical costs and CO2 emissions.

scholarly journals Enhancing water levels of degraded, bare, tropical peatland in West Kalimantan, Indonesia: Impacts on CO2 emission from soil respiration

2018 ◽  
Vol 19 (2) ◽  
pp. 472-477
Author(s):  
DWI ASTIANI ◽  
BURHANUDDIN BURHANUDDIN ◽  
EVI GUSMAYANTI ◽  
TRI WIDIASTUTI ◽  
MUHAMMAD J. TAHERZADEH
Keyword(s):  
Soil Respiration ◽  
Co2 Emissions ◽  
Water Table ◽  
Carbon Emissions ◽  
Co2 Emission ◽  
Water Levels ◽  
Small Scale ◽  
West Kalimantan ◽  
Tropical Peatland ◽  
Water Tables

Astiani D, Burhanuddin, Gusmayanti E, Widiastuti T, Taherzadeh MJ. 2018. Enhancing water levels of degraded, bare, tropical peatland in West Kalimantan, Indonesia: Impacts on CO2 emission from soil respiration. Biodiversitas 19: 472-477. The major drivers of deforestation in West Kalimantan have been the development for large or small-scale expansion of agricultural activities; the establishment of oil palm and other plantations; fire; and degradation of forests particularly from industrial logging. Our previous research findings have shown that such activities in affected peatland areas have lowered the water table levels (down to 0.5-1.0 m depths), and have significantly increased CO2 emissions from the peat soils. It has been demonstrated that unmanaged, lowered water tables in peatlands act as one of the main factors inflating soil carbon emissions - an issue that has assumed global significance in recent decades. Regulating peatland water tables has the potential to mitigate degraded peatland carbon emissions as well as improve the hydrological functions for communities who farm the peatlands. However, we are still uncertain exactly how much impact controlled raising of the peatlands water tables will have on reducing soil CO2 emissions. The research described here aimed to mitigate CO2 emissions by raising and regulating water levels on drained peatland to restore and enhance its hydrological functions. The results confirmed that raising the water table significantly decreases CO2 emissions and improves water availability and management for crop production in the coastal peatland of Kubu Raya district, West Kalimantan. Water levels previously at 60cm below the soil surface were regulated to raise the watertable up to just 30 cm below the surface and this reduced peatland carbon emissions by about 49%. However, longer-term monitoring is required to ensure that the hydrological benefits and CO2 mitigation can be sustained.

scholarly journals Creation of Zero CO2 Emission Plants Due to Energy Use: A Case Study in Crete, Greece

2018 ◽  
Vol 5 (1) ◽  
pp. 55
Author(s):  
John Vourdoubas
Keyword(s):  
Co2 Emissions ◽  
Carbon Emissions ◽  
Co2 Emission ◽  
Energy Use ◽  
Energy Intensity ◽  
Electricity Consumption ◽  
Photovoltaic System ◽  
Tree Plantation ◽  
Electricity Use ◽  
Solar Photovoltaic System

Creation of zero CO2 emission enterprises due to energy use in Crete, Greece has been examined with reference to an orange juice producing plant (Viochym). Energy intensity at Viochym has been estimated at 1.66 KWh per € of annual sales. Oil used for heat generation has been replaced with solid biomass produced locally in Crete and resulting in zero CO2 emissions due to the use of heat. Offsetting CO2 emissions due to grid electricity use has been proposed with two options. The first includes the installation of a solar photovoltaic system with nominal power of 417 KWp, according to net metering regulations, generating annually 625 MWh equal to annual grid electricity consumption in the plant. Its capital cost has been estimated at 0.5 mil € which corresponds to 1.07 € per kg of CO2 saved annually.The second option includes the creation of a tree plantation in an area of 107 hectare resulting in carbon sequestration equal to carbon emissions in the plant due to electricity use. Both options for offsetting CO2 emissions in Viochym have various advantages and drawbacks and they are considered realistic and feasible, resulting in the elimination of its carbon emissions due to energy use. Improvement of the energy intensity of various processes in Viochym could result in lower CO2 emissions and smaller sizing of the required renewable energy systems for eliminating them.

scholarly journals Research on Berth-Quay Crane Joint Scheduling Considering Carbon Emission

2021 ◽  
pp. 1-6
Author(s):  
Rui Yang ◽  
◽  
Junqing Sun
Keyword(s):  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Programming Model ◽  
Container Terminal ◽  
Optimal Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Scheme ◽  
Elite Strategy

With the increasing awareness of environmental protection, all walks of life a are paying more and more attention to the carbon dioxide emissions brought by their own industries. For the container terminal, a large proportion of carbon emissions come from the fuel consumption of vessels. In this paper, the consideration of carbon emissions is added to the original berth quay crane joint scheduling problem, and the constraints such as vessel preference for berths and quay crane interference are added. A dual-objective nonlinear mixed integer programming model is established to minimize carbon emissions and minimize costs. The model is solved by the Non-Dominated Sorting Genetic Algorithm with Elite Strategy, and the optimal scheduling scheme is obtained. Finally, the calculation examples are verified to prove the effectiveness and practicability of the model and algorithm.

Work continuity constraints in repetitive project scheduling considering soft logic

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Zou ◽  
Guangchuan Wu ◽  
Qian Zhang
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Future Research ◽  
Small Scale ◽  
Content Type ◽  
Project Duration ◽  
Additional Information ◽  
Work Interruptions ◽  
Conflicting Objectives ◽  
Soft Logic

PurposeRepetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.Design/methodology/approachThis paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.FindingsUsing soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.Research limitations/implicationsThe main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.Practical implicationsThis study assists practitioners in determining the “most preferred” schedule once additional information is provided.Originality/valueThis paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.

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