Vehicle routing analyses with integrated order picking and delivery problem under carbon cap and trade policy

2019 ◽  
Vol 43 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Sanjay Jharkharia ◽  
Chiranjit Das
Keyword(s):  
Sensitivity Analysis ◽  
Trade Policy ◽  
Vehicle Routing ◽  
Carbon Footprint ◽  
Order Picking ◽  
Mixed Integer ◽  
Vehicle Speed ◽  
Cap And Trade ◽  
Content Type ◽  
Total Cost

Purpose The purpose of this study is to model a vehicle routing problem with integrated picking and delivery under carbon cap and trade policy. This study also provides sensitivity analyses of carbon cap and price to the total cost. Design/methodology/approach A mixed integer linear programming (MILP) model is formulated to model the vehicle routing with integrated order picking and delivery constraints. The model is then solved by using the CPLEX solver. Carbon footprint is estimated by a fuel consumption function that is dependent on two factors, distance and vehicle speed. The model is analyzed by considering 10 suppliers and 20 customers. The distance and vehicle speed data are generated using simulation with random numbers. Findings Significant amount of carbon footprint can be reduced through the adoption of eco-efficient vehicle routing with a marginal increase in total transportation cost. Sensitivity analysis indicates that compared to carbon cap, carbon price has more influence on the total cost. Research limitations/implications The model considers mid-sized problem instances. To analyze large size problems, heuristics and meta-heuristics may be used. Practical implications This study provides an analysis of carbon cap and price model that would assist practitioners and policymakers in formulating their policy in the context of carbon emissions. Originality/value This study provides two significant contributions to low carbon supply chain management. First, it provides a vehicle routing model under carbon cap and trade policy. Second, it provides a sensitivity analysis of carbon cap and price in the model.

scholarly journals Achieve a low carbon supply chain through product mix

2017 ◽  
Vol 117 (10) ◽  
pp. 2468-2484 ◽  
Author(s):  
Xu Chen ◽  
Xiaojun Wang
Keyword(s):  
Supply Chain ◽  
Trade Policy ◽  
Carbon Emissions ◽  
Channel Structure ◽  
Low Carbon ◽  
Cap And Trade ◽  
Product Mix ◽  
Content Type ◽  
Carbon Supply ◽  
Trade Offs

Purpose In the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy. Design/methodology/approach The authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain. Findings The analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability. Originality/value The research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control.

Dynamic supplier selection approach for mining equipment company

2019 ◽  
Vol 14 (1) ◽  
pp. 77-105 ◽  
Author(s):  
Md. Tanweer Ahmad ◽  
Sandeep Mondal
Keyword(s):  
Sensitivity Analysis ◽  
Supplier Selection ◽  
Business Environment ◽  
Spare Parts ◽  
Mixed Integer ◽  
Optimal Order ◽  
Mining Equipment ◽  
Order Allocation ◽  
Managerial Implication ◽  
Content Type

PurposeThis paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.Design/methodology/approachAn integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.FindingsThe ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.Practical implicationsThis paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.Originality/valueIt provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

Municipal solid waste management considering NGO’s role in consumer environmental awareness and government regulations for air pollution

2020 ◽  
Vol 15 (3) ◽  
pp. 783-807
Author(s):  
Masoud Rabbani ◽  
Parisa Hashemi ◽  
Pegah Bineshpour ◽  
Hamed Farrokhi-Asl
Keyword(s):  
Air Pollution ◽  
Sensitivity Analysis ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Environmental Awareness ◽  
Mixed Integer ◽  
Good Effect ◽  
Municipal Solid Waste Management ◽  
Content Type

Purpose The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs). Design/methodology/approach This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern. Findings This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased. Research limitations/implications In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results. Practical implications Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW. Originality/value The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

Optimization of the simultaneous pickup and delivery vehicle routing problem based on carbon tax

2019 ◽  
Vol 119 (9) ◽  
pp. 2055-2071 ◽  
Author(s):  
Gaoyuan Qin ◽  
Fengming Tao ◽  
Lixia Li ◽  
Zhenyu Chen
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Carbon Tax ◽  
Pickup And Delivery ◽  
Vehicle Speed ◽  
Low Carbon ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Content Type ◽  
Simultaneous Pickup And Delivery

Purpose In order to reduce logistics transportation costs and respond to low-carbon economy, the purpose of this paper is to study the more practical and common simultaneous pickup and delivery vehicle routing problem, which considers the carbon tax policy. A low-carbon simultaneous pickup and delivery vehicle routing problem model is constructed with the minimum total costs as the objective function. Design/methodology/approach This study develops a mathematical optimization model with the minimum total costs, including the carbon emissions costs as the objective function. An adaptive genetic hill-climbing algorithm is designed to solve the model. Findings First, the effectiveness of the algorithm is verified by numerical experiments. Second, the research results prove that carbon tax mechanism can effectively reduce carbon emissions within effective carbon tax interval. Finally, the research results also show that, under the carbon tax mechanism, the effect of vehicle speed on total costs will become more obvious with the increase of carbon tax. Research limitations/implications This paper only considers the weight of the cargo, but it does not consider the volume of the cargo. Originality/value Few studies focus on environmental issues in the simultaneous pickup and delivery problem. Thus, this paper constructs a green path optimization model, combining the carbon tax mechanism for the problem. This paper further analyzes the impact of carbon tax value on total costs and carbon emission; at the same time, the effect of vehicle speed on total cost is also analyzed.

Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1267-1284 ◽  
Author(s):  
Yandong He ◽  
Xu Wang ◽  
Fuli Zhou ◽  
Yun Lin
Keyword(s):  
Vehicle Routing ◽  
Delivery System ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem ◽  
Content Type ◽  
Last Mile ◽  
Last Mile Delivery

Purpose This paper aims to study the vehicle routing problem with dynamic customers considering dual service (including home delivery [HD] and customer pickup [CP]) in the last mile delivery in which three decisions have to be made: determine routes that lie along the HD points and CP facilities; optimize routes in real time, which mode is better between simultaneous dual service (SDS, HD points and CP facilities are served simultaneously by the same vehicle); and respective dual service (RDS, HD points and CP facilities are served by different vehicles)? Design/methodology/approach This paper establishes a mixed integer linear programing model for the dynamic vehicle routing problem considering simultaneous dual services (DVRP-SDS). To increase the practical usefulness and solve large instances, the authors designed a two-phase matheuristic including construction-improvement heuristics to solve the deterministic model and dynamic programing to adjust routes to dynamic customers. Findings The computational experiments show that the CP facilities offer greater flexibility for adjusting routes to dynamic customers and that the SDS delivery system outperforms the RDS delivery system in terms of cost and number of vehicles used. Practical implications The results provide managerial insights for express enterprises from the perspective of operation research to make decisions. Originality/value This paper is among the first papers to study the DVRP-SDS. Moreover, this paper guides the managers to select better delivery mode in the last mile delivery.

Sensitivity analysis in an imperfect substitutes model of preferential trade

2014 ◽  
Vol 41 (5) ◽  
pp. 630-643 ◽  
Author(s):  
Kenneth A. Reinert
Keyword(s):  
Sensitivity Analysis ◽  
Policy Analysis ◽  
Trade Policy ◽  
Sensitivity Analyses ◽  
Formal Representation ◽  
Content Type ◽  
Conduct Sensitivity Analysis ◽  
Behavioral Parameters ◽  
Applied General Equilibrium Models

Purpose – The purpose of this paper is to develop a formal representation of the imperfect substitutes model (ISM) of partial equilibrium, trade policy analysis and to conduct sensitivity analysis on the behavioral parameters of the model. Design/methodology/approach – The paper develops an ISM in a manner that is conformable to more complex, applied general equilibrium models of trade policy analysis. Findings – The paper presents a set of sensitivity analyses on key behavioral parameters for a better understanding of the model's properties. Research limitations/implications – Sensitivity analysis on the values of behavioral parameters in ISMs needs to be conducted by trade policy modelers. Practical implications – The ISM is made more explicit here than in most representations, something that will be of great use to practitioners. Originality/value – While widely used in trade policy circles, the ISM is rarely explicitly formulated, nor the role of its behavioral parameters explored.

Multi-period reverse logistics network design with emission cost

2017 ◽  
Vol 28 (1) ◽  
pp. 127-149 ◽  
Author(s):  
Sajan T. John ◽  
Rajagopalan Sridharan ◽  
P.N. Ram Kumar
Keyword(s):  
Mathematical Model ◽  
Network Design ◽  
Reverse Logistics ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Single Type ◽  
Reverse Supply Chain ◽  
Design Decisions ◽  
Content Type ◽  
Total Cost

Purpose The purpose of this paper is to develop a mathematical model for the network design of a reverse supply chain in a multi-product, multi-period environment. The emission cost due to transportation activities is incorporated into the model to reduce the total cost of emission and study the significance of inclusion of emission cost on the network design decisions. Design/methodology/approach Mixed integer linear programming formulation is used to model the network. The developed model is solved and analysed using the commercial solver LINGO. Findings The mathematical model provides a unified design of the network for the entire planning horizon comprising of different periods. A reduction in the total cost of emission is achieved. The analysis of the problem environment shows that the network design decisions significantly vary with the consideration of emission cost. Research limitations/implications A single mode of transportation is considered in this study. Also, a single type of vehicle is considered for the transportation purpose. Practical implications The developed model can aid the decision makers in making better decisions while reducing the total emission cost. The quantification of the emission cost due to transportation activities is presented in an Indian context and can be used for future studies. Originality/value An all-encompassing approach for the design of reverse logistics networks with explicit consideration of product structure and emission cost.

Optimization of concrete placing operation based on competing carbon footprint, cost and production rate objectives

2018 ◽  
Vol 25 (7) ◽  
pp. 938-957
Author(s):  
Zahra Sadat Moussavi Nadoushani ◽  
Ali Akbarnezhad ◽  
David Rey
Keyword(s):  
Sensitivity Analysis ◽  
Production Rate ◽  
Carbon Footprint ◽  
Carbon Emissions ◽  
Arrival Time ◽  
Discrete Event ◽  
Optimal Number ◽  
Emission Rates ◽  
Content Type ◽  
Activity Duration

Purpose Due to considerable contributions of the construction industry to the global carbon emissions, a great deal of attention is placed on possible incorporation of carbon footprint minimization as an important objective in the planning of construction operations. The purpose of this paper is to present a framework to estimate and minimize the carbon emissions of the concrete placing operation through identifying the optimal number of pumps and the inter-arrival time of truck mixers. Design/methodology/approach The proposed framework integrates discrete event simulation and multi-objective optimization to estimate and minimize the carbon emission, costs and production rate of the concrete placing operation. An actual construction project is used to demonstrate the application of the proposed framework. Furthermore, a sensitivity analysis is performed to investigate the sensitivity of the results to variations in modeling parameters including the ratio of idle to non-idle emission rates of equipment and the activity duration distributions. Findings The results of the case study highlight that variations in the number of pumps and inter-arrival time of truck mixers significantly affect the carbon emissions, cost and production rate of the concrete placing operation. Furthermore, the results of the sensitivity analysis show that variations in the ratio of idle to non-idle emission rates for pumps and truck mixers have little effects on the selected setting for the project. This is contrary to the effect of uncertainty in the activity duration distributions, which was found to be significant. Originality/value Results of this study provide an insight into the trade-off between carbon emissions, cost and production rate of the concrete placing operation.

scholarly journals A Simulated Annealing Heuristic for the Capacitated Green Vehicle Routing Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Nur Mayke Eka Normasari ◽  
Vincent F. Yu ◽  
Candra Bachtiyar ◽  
Sukoyo
Keyword(s):  
Sensitivity Analysis ◽  
Simulated Annealing ◽  
Numerical Experiment ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Routing Problem ◽  
Total Distance ◽  
Number Of Customers

This research studies the capacitated green vehicle routing problem (CGVRP), which is an extension of the green vehicle routing problem (GVRP), characterized by the purpose of harmonizing environmental and economic costs by implementing effective routes to meet any environmental concerns while fulfilling customer demand. We formulate the mathematical model of the CGVRP and propose a simulated annealing (SA) heuristic for its solution in which the CGVRP is set up as a mixed integer linear program (MILP). The objective of the CGVRP is to minimize the total distance traveled by an alternative fuel vehicle (AFV). This research conducts a numerical experiment and sensitivity analysis. The results of the numerical experiment show that the SA algorithm is capable of obtaining good CGVRP solutions within a reasonable amount of time, and the sensitivity analysis demonstrates that the total distance is dependent on the number of customers and the vehicle driving range.

scholarly journals A heuristic algorithm for multiple trip vehicle routing problems with time window constraint and outside carrier selection

2019 ◽  
Vol 4 (3) ◽  
pp. 256-273
Author(s):  
Ching-Wu Chu ◽  
Hsiu-Li Hsu
Keyword(s):  
Cost Function ◽  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Real World ◽  
Time Windows ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Content Type ◽  
Total Cost ◽  
Total Cost Function

Purpose In this paper, the authors introduced a real world new problem, the multi-trip vehicle routing problem with time windows and the possible use of a less-than-truckload carrier to satisfy customer demands. The purpose of this paper is to develop a heuristic algorithm to route the private trucks with time windows and to make a selection between truckload and less-than-truckload carriers by minimizing a total cost function. Design/methodology/approach Both mathematical model and heuristic algorithm are developed for routing the private trucks with time windows and for selecting of less-than-truckload carriers by minimizing the total cost function. Findings In all, 40 test problems were examined with the heuristics. Computational results show that the algorithm obtains the optimal or near-optimal solutions efficiently in terms of time and accuracy. Originality/value The research described in this paper differs from the previous one on fleet planning or vehicle routing, in that it modifies the Clarke and Wright method by shifting the performance measure from a distance to cost and also incorporates the fixed cost of different types of trucks into the model. In addition, the authors simultaneously consider the multiple trip vehicle routing problems with time windows and the selection of less-than-truckload carriers that is an integrated scenario of real-world application. To the best of the authors’ knowledge, this scenario has not been considered in the literature.

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