Total Transportation Cost Research Articles

Optimization of intermodal routes for reefer containers under double uncertainty

Aiming at the influence of demand uncertainty and stochastic carbon trading price on the choice of intermodal transportation route for reefer containers, a hybrid robust stochastic optimization model with minimum economic cost is established, and a Monte Carlo sampling-based catastrophic adaptive genetic algorithm is designed to test the reasonableness and validity of the model. The results show that: influenced by the regret value constraint, the robust optimization of demand uncertainty will increase the total cost of reefer container multimodal transportation, while the increase of carbon trading price stochasticity doesn’t necessarily mean the increase of cost, and the reasonable setting of carbon trading price stochasticity and the trade-off between the maximum regret value and the economic cost, so that the cold-chain logistics and transportation enterprises can easily deal with the fluctuation of the demand of the freight transportation market, and also respond to the low-carbon requirements.

Optimizing the distribution of tofu products using a genetic algorithm approach: A case study in tahu kres KWB Batu City, Malang

The aim of this research is to determine the optimal route using a genetic algorithm and to compare the routes before and after optimization. The method used is the Genetic Algorithm, which consists of representation and initialization stages using permutation encode representation of the sequence of travel routes. The fitness function evaluation is the minimization of total fuel cost, selection is done using roulette wheel selection, crossover is done using PMX, and mutation is done using swap mutation. The testing of parameter combinations is carried out on population size, Cr and Mr values, and the number of generations. The parameter testing based on the highest average fitness is conducted 10 times for each parameter combination. Testing of population size and generation size was carried out in the range of 100-1000, obtained the best population size of 600 and the best generation size of 900. The combination testing of Cr and Mr is conducted for combinations of 1 and more than 1, and the values obtained are Cr: 0.6 and Mr: 0.5. This combination of parameters results in a fitness of 0.00960 with a total distance traveled of 307.61 and a total transportation cost of Rp 104,082 for fuel. Initially, the total distance traveled was 278.57 km with a fuel distribution cost of Rp 161,258. Therefore, the results of this research are able to save 35.46% of fuel transportation costs.

A fair multi-commodity two-echelon distribution problem

In the context of a short and local supply chain of fresh produce in the public sector, we introduce a fair multi-commodity two-echelon distribution problem. A decision maker has to decide on the planning of the first-echelon collection trips of commodities from suppliers to distribution centers equitably and on the second-echelon delivery routes of commodities from the centers to customers. In addition to the classic objective of minimizing the total transportation cost in vehicle routing problems, the goal is to make sure that all suppliers receive an equitable service with regard to their profits. This is done by introducing fairness measures into the problem as a set of constraints. We use two widely used inequality metrics from the literature and present a novel problem-specific equity measure as well. We model the problem as a mixed-integer program using an arc-route-based formulation and suggest a matheuristic to solve the problem. Through numerical experiments, we analyze the performance of our matheuristic on a series of generated instances and on the instances of a French fresh produce supply chain from the literature. We evaluate the efficacy of the three used fairness schemes with regard to a series of key performance metrics and investigate the strengths and weaknesses of the different fairness measures. Moreover, we study the trade-off between enforcing fairness and optimizing transportation costs to come up with insights for the managers of the supply chain.

Decarbonization through modal shift using a synchromodal platform: A case study in the Great Lakes

This paper offers an empirical study to explore the relationship between transportation modalities and environmental concerns, promoting the adoption of synchromodality as a strategic pathway to achieving sustainable freight transport. The study uses a synchromodal freight transportation platform to analyze the impact of carbon tax policy on modal shift and environmental sustainability. The synchromodal platform is based on an optimization model using Mixed Integer Linear Programming (MILP), incorporating carbon tax as a surrogate measure for environmental costs. A sensitivity analysis is conducted across four distinct scenarios in a case study in the Great Lakes region, focusing on the Canada-US transborder trade. The results of this study illustrate the considerable potential for increasing the utilization of more environmentally sustainable transportation modes in this region. While the addition of carbon tax entails increased total transportation costs for each unit of cargo, the synchromodal-enabled modal shift promises to mitigate transportation’s negative externalities, including congestion, environmental impacts, and noise pollution. The results also highlight the role of synchromodality as a catalyst for sustainable freight transport decisions in the context of a carbon-conscious world.

Enhancing Food Supply Chain Efficiency: A Consolidation Shipping Approach For Multi-Product and Multiechelon

This research applies the application of delivery consolidation in the context of a multi-product and multi-echelon food supply chain, as a strategy to address operational efficiency and cost management. The aim is to implement consolidation in multi-product and multi-echelon distribution systems, in order to optimize product placement and distribution efficiently. The method adopted is the Linear Programming model, which considers key variables such as the number of goods to be sent, delivery route, resource allocation, fleet capacity and delivery time limit. The research results show that shipment consolidation, by scheduling shipments that are delayed until the second or third day, allows combining orders into one large shipment, thereby increasing load and route efficiency, reducing trip frequency, and achieving significant transportation cost savings. This strategy successfully increased load and route efficiency, reduced the number of trips required, and resulted in substantial transportation cost savings. Using this method, the total shipping and storage costs are 1,328,834. This consolidation strategy has proven crucial in optimizing delivery types, in addition to facilitating more effective route planning, reducing travel distances and times, and resulting in significant operational cost savings.

Penentuan Rute Distribusi Feasible untuk Vehicle Routing Problem with Time Windows dengan Metode Sequential Insertion Pada CV. Hagia Mitra Mandiri

CV. Hagia Mitra Mandiri is a company that distributes black queen bee honey products. Problems faced by CV. Hagia Mitra Mandiri in the distribution of its products, namely that the company has not yet planned product delivery routes to various customers of bitter black queen bee honey in the Jakarta, Bogor, Depok, Bekasi and Karawang areas. As a result, product delivery routes often exceed customer working hours, which can make delivery schedules less than optimal in terms of distance, travel time and delivery costs. This research aims to design the route that each vehicle must take according to the user's working hours, with the aim of optimizing the total travel distance. The method used is the sequential insertion algorithm method to solve the Vehicle Routing Problem with Time Windows problem model. The sequential insertion method is used to plan proposed distribution routes by considering travel distance, travel time and transportation costs. The research results show that there are differences in the proposed route from the initial route. The proposed route resulting from the calculation of the sequential insertion algorithm method produces the best distance, namely 307 km with a savings ratio of 18.13%, a comparison of total transportation cost savings of Rp. 58,758 and the difference in fuel usage is 7.55 liters. The total travel time is 667 minutes and the total travel time ratio is 9.01%.

Optimization of river container port-access transport based on the innovatively designed electric ship in the Yangtze River Delta

In order to increase the share of the container port-access transport of river shipping and reduce the carbon emissions of container transportation, this study innovates the design of wide and shallow draft river ship and its electric power system based on the navigation condition of the rivers in the Yangtze River Delta (YRD) with the objective of raising the advantage in river shipping to truck transport. To validate the ship's practicability, we incorporate the carbon quota of container port-access transport as a constraint and build a model to optimize the river liner service for container port-access transport. The case study reveals that the adoption of innovative 48 TEU electric river ship for container port-access transport will be associated with a rise in the mode share of river liner shipping from 16.1% to 20.0%, a decrease in carbon emission by 0.124 million tons and a decrease of 0.358 billion CNY in container port-access transport in the YRD, while the higher the carbon tax price the more the modal shift will be, however, since the carbon emission cost is a part of the total transport cost, the total transport cost exhibits an upward trend.

Node location of bi-level urban metro-based ground-underground logistics distribution

Metro-based underground logistics (M-ULS) can relieve the pressure of urban traffic and avert the road congestion through coordinating with ground logistics system. A bi-level node location model is proposed based on the ground-underground logistics distribution mode. The cost of delivery and pickup from the perspective of service companies and customers are minimized as the upper and lower objectives. Since the model is belonged to NP-hard problem, the simulated annealing algorithm (SA algorithm) whose new solution generation part was improved according to the characteristics of the model is used to solve the problem. In the case analysis part, the distribution nodes and customer points close to Nanjing Metro Line 3 were selected to verify the validity of the model and algorithm. The result shows that the improved SA algorithm outperformed in taking less iteration times and obtaining better solutions. The total transportation cost of the system can be reduced by 21.7 % with the optimized node location plan, and 63.6 % of the ground transportation distance can be replaced by the underground transportation, such results are also obtained when the cargo demand increases by 1.5 times and 2 times, which verifies the advantages of M-ULS node location in reducing truck emission and total delivery cost.

An Effective Approach for Solving Multi-objective Transportation Problem

In this present study, a transportation problem is considered such that the total cost and time of transportation are minimized without taking into account their priorities. In literature, there are less techniques available for finding the efficient solutions of multi-objective transportation problem. So, we developed a heuristic algorithm to find most efficient solution of multi-objective transportation problem, which gives efficient solution with minimum difference from ideal solution. Firstly, we aim at formulating a multi-objective transportation problems along with a novel algorithm to find efficient solutions. The proposed algorithm gives optimal solution faster in comparison to other available techniques in literature for the given multi-objective transportation problem. Moreover, it avoids the degeneracy as well as requires low computational effort. Furthermore, an illustrative example is provided to show the feasibility and applicability of the proposed approach and compare the results with the existing approaches to show the effectiveness of it.

The impact of new western land and sea corridor development on port deep hinterland transport service and route selection

New transportation corridor development aims to provide more convenient transportation conditions for port deep hinterland areas and to enhance the two-way opening of land and sea through the utilization of various transport modes, such as railroad, highway, and water transportation. In this paper, the microcontainer transport service and route selection problem is introduced within a new transportation corridor context, and a decision-making tool is provided for shippers to develop door-to-door service plans. A multiobjective 0–1 planning model is constructed with the objective of minimizing the total transportation cost, transportation time, and carbon emissions. The loading and unloading time windows of railroad and waterway transportation, as well as the time window of consignee receipt, are considered in model construction to obtain the nondominated Pareto optimal front. The validity of both the model and algorithm is demonstrated in this paper by using the Chongqing-Hamburg and Chengdu-Hamburg routes, following the development of the New Western Land and Sea Corridor (NWLSC), as examples. The example results show that the NWLSC is appealing for time-sensitive cargoes, and its economic benefits can be enhanced if relevant policies such as railroad freight reductions are supported. The findings in this paper can provide decision support for western provinces in the implementation of targeted policies to regulate and optimize the regional transportation structure, which can further promote the opening up of western Chinese provinces as well as the integrated and coordinated development of coastal and inland regions, providing practical value for reducing carbon emissions.

A Lagrangian heuristic for integrated production planning, material ordering and investment multi-project scheduling in a project-driven supply chain

Effective decision making in large project planning presents a significant challenge. Despite progress in developing mathematical models, few studies comprehensively address project and supply-chain management aspects in an integrated framework. This article presents an integrated approach for multi-project resource investment, material ordering and production planning in a project-driven supply chain. A mixed-integer programming model is developed to optimize the total cost of renewable resource investment, production, transportation, and material ordering and holding, with an opportunity to share mobile renewable resources across multiple projects. A Lagrangian relaxation heuristic algorithm is proposed to determine the upper and lower bounds for the objective function, with an additional set of valid cuts to reduce the distance between bounds. The results of numerical experiments demonstrate the favourable performance of the proposed algorithm compared to the GAMS solver. This article provides insights into supply-chain participant expenses and activity scheduling based on these findings.

Environmental and energy performance of integrated passenger–freight transport

The first-last mile (FLM) transport of passengers and freight accounts for a significant share of total transport costs, pollution, and energy consumption. According to recent scientific literature and institutional inputs at the European level, operational innovations such as the combination of passenger and freight flows may be an effective approach for promoting sustainable and energy-efficient FLM transport. In this study, the energy and environmental performances of an integrated passenger and freight transport system based on the bus network of Zrenjanin (Serbia) were investigated with different future energy mix and transport policy scenarios. The operational aspects of the integrated system were designed through collaboration with territorial stakeholders and an analysis of local planning documents. The performance was evaluated and compared with current public transport and freight schemes considering vehicle fuel and technology, total mileage, and other relevant endogenous and exogenous factors. The results of our analysis indicate operational benefits and energy savings, mainly due to reduced total mileage and the predisposition to shift to the active modes for the last mile. However, most expected long-term energy savings are the result of technological development of vehicles and modal shifts induced by policy strategies.

Optimizing a Multi Period Deterministic Inventory Routing Problem in Agriculture Industries

This paper develops a solving model for multi-period deterministic inventory routing problem (MP-DIRP) in supply chain focus on agriculture industries. The issue is how to improve the perishable product delivery process from a distribution centre (DC) to a collection of customers over a planning horizon. This paper proposed a model to achieve optimization in terms of costs respectively. The transportation problem is solved by using a simulation technique and developed using an algebraic modelling language which is known as a mathematical programming language (AMPL) to find an optimal solution within the period. The route for a distribution centre (DC) is set up by a supplier depending on the number of products assigned to each customer, which contributes to determining the best inventory routing problem (IRP) for each period. As a result, by applying the transportation model developed in this study, it is expected that the industries can achieve optimization by minimizing their total inventory and transportation costs.

Multimodal container schemes freight delivery

The article highlights the topical issue of the development of container multimodal transport, which is a priority in the development of transport services; their use will increase the volume of cargo delivered to the destination by the most efficient modes of transport (their combination). Container transportation of goods significantly reduces the cost of delivery of goods from producers to consumers. Container transportation has become the most economical without transshipment technology and, above all, in the intercontinental multimodal land-sea service. The work aims to study the practical aspects and substantiate practical recommendations for the logistics of multimodal container transportation of goods in global supply chains. Conduct a comparative analysis of implementing multimodal container traffic in different containers, namely 20 and 40 feet. The analysis and calculations of the data of container transportation processes for the conditions of two international transport corridors, TRACECA and the trans-Caspian international transport route, are carried out. The cost of transportation by sea, although their number is small relative to the total share of routes, significantly affects the total cost of transportation. In order to stimulate freight traffic on these routes, member states have set discounts of up to 10% of the cost of the ferry fare. Studies suggest that the use of multimodal container traffic is currently economically feasible. The conducted research of practical aspects and substantiation of practical recommendations on logistics of multimodal container transportation of goods in global supply chains suggests that container transportation is a way of delivery today using multimodal options for delivery of goods. An in-depth comparative analysis of implementing multimodal container traffic in different containers, namely 20 and 40 feet, allows us to conclude that using the Trans-Caspian International Transport Route (TMTM) with a 20-foot container is more economically attractive and can be recommended. Keywords: container transportation, supply chains, logistics, international transport corridors, multimodal transportation.

Balancing economical and environmental trade-off in modular construction yard planning: Models and properties

This study investigates an integrated yard planning and module transportation problem in modular integrated construction (MiC). A Stackelberg game model is proposed to characterize the relations between the government and contractors. The government is the leader and decides the locations and areas of temporary storage yards to facilitate the cost-effective and eco-friendly transportation of MiC modules. The contractors are the followers and decide the transport mode (i.e., road transport or intermodal transport) for modules to minimize their total transportation costs. This study provides an in-depth analysis of model properties to derive a number of useful managerial insights. The economical and environmental trade-offs between costs and emissions are observed. Our study further proves that an optimal solution is likely to simultaneously reduce the overall costs and carbon emissions, in comparison to choosing the location with the largest area to construct a temporary storage yard. These insights offer a comprehensive framework for understanding the interactions between government and contractors. Overall, this paper aims to promote the implementation of MiC by achieving the economical and sustainable transportation of MiC modules.

Enhanced Artificial Bee Colony with Savings Algorithm for Inventory Routing Problem

Inventory Routing Problem is a critical component of Supply Chain Management, where it is a coordination of inventory management and transportation. It aims to balance the trade-off between transportation costs for delivering products and holding costs for maintaining inventory. Several real-world problems faced nowadays require effective optimization and logistical solutions, where this problem arises in various industries and has become increasingly complex. The problem addressed in this study is based on an automotive parts supply chain that consists of a depot, an assembly plant, a set of homogeneous capacitated vehicles, and multi-suppliers on a finite horizon with multi-periods. Artificial Bee Colony is a swarm intelligence algorithm that is based on the behaviour of bees in a colony, where information is shared through waggle dance. ABC consists of three phases, which are employed bee phase, onlooker bee phase, and scout bee phase. This study proposed an enhancement in the initialization phase and in onlooker bee phase of the ABC algorithm. Clarke Wright savings algorithm was implemented in the initialization phase to determine the best feasible delivery routes while minimizing the total transportation cost. 2-opt and 2-opt(asterisk) were used to improve the routes in the onlooker bee phase. Results showed that 7 better total cost were found out of 14 benchmark datasets when compared to the previous literature. The enhanced ABC algorithm obtained better results with 5.59 percent at most, which demonstrated the effectiveness of the algorithm.

Fixed charge 4-dimensional transportation problem for breakable incompatible items with type-2 fuzzy random parameters under volume constraint

Real-life problems are full of uncertainties combined with impreciseness and randomness. Transportation problems become difficult when its parameters are type-2 fuzzy random type. This paper presents a 4-dimensional fixed charge transportation problem for incompatible and compatible breakable items with type-2 fuzzy random parameters under the availability, demand, conveyance’s weight and volume capacity constraint. The model is developed for usual transportation cost minimization objective, where transportation costs, fixed charges, availabilities, demands, conveyances’ weights and volume capacities are type-2 fuzzy random. A type-2 fuzzy random parameter is converted to type-1 fuzzy random one by critical value-based reduction method and then converted to a random parameter using two different methods-generalized credibility measure and centroid method. The random parameter is converted to crisp parameter using probability chance constraint method for constraints and expectation for objective. A detailed conversion procedure from type-2 fuzzy random to crisp is also presented. The reduced deterministic problem is solved by the Generalized Reduced Gradient method using Lingo 11.0 and numerically illustrated. A real-life example is introduced. Particular models are deduced for non-breakable items or different pairwise incompatible items. The sensitivity analyses against different generalized credibility levels of different parameters are presented for total transportation cost. The numerical results show the efficiency of the proposed critical value reduction-generalized credibility-chance constraint, and expectation method. The importance of uncertainty, multi-path and vehicles’ volume capacity in transportation problems is demonstrated.

Column generation for service assignment in cloud-based manufacturing

Cloud-based manufacturing has gained significant attention in academia and industry, presenting opportunities for enhanced operational efficiency. This paper addresses two critical challenges in cloud manufacturing: service assignment and transportation within hybrid hub-and-spoke networks. We propose a novel approach to minimize the total cost, encompassing manufacturing and transportation costs, through a mixed integer programming model and a column generation-based algorithm. Numerical experiments are conducted to validate the efficacy of the proposed model and algorithm, considering different system sizes. The results demonstrate the tangible benefits of our approach. By introducing a hybrid hub-and-spoke network, we achieve a substantial average reduction of 7.46% in the total cost of the cloud manufacturing system. Furthermore, our proposed algorithm outperforms existing methods such as Particle Swarm Optimization (PSO) and CPLEX. Particularly, in large-scale instances where CPLEX fails to solve, our algorithm outperforms PSO by an additional 3.43% in terms of cost reduction. Moreover, sensitivity analysis provides valuable insights for cloud manufacturing, contributing to its effective implementation.

Feasibility of establishing an integrated railway-based containerised cargo transport network between the Port of Colombo and free trade zones in Sri Lanka

A large percentage of Sri Lanka's exports and imports are generated by the manufacturing sector and originates from facilities dispersed throughout Export Processing Zones (EPZs) around the country. An efficient hinterland transport network is required between the Port of Colombo and these EPZs. However, road trucks are used as the dominant transport mode for moving containerised cargo to/from Colombo Port. This study proposes a dry port-based containerised import/export cargo transportation method using a railway network to connect the Port of Colombo and the EPZs under several alternative network configurations. This study conducts a questionnaire survey with 40 experts to identify issues with the current road-based container transport network and ascertain the benefits of proposed railway-based networks in Sri Lanka. A majority of respondents highlight the benefits of the proposed network from multiple perspectives along with several drawbacks with the current road-based network. Initially, the feasibility of two alternative dry port locations in Orugodawatta and Kerawalapitiya are analysed. A mathematical model is developed to analyse the feasibility of the proposed alternative networks. Finally, the optimum dry port location is selected as Aluthwaththa using a simulation-based Greenfield analysis approach. Results highlight the advantages of proposed networks under several scenarios. The study demonstrates a systematic approach to decision-making by optimising the local cargo handling process, where, Sri Lankan inland logistic operations will become more efficient, with total transport costs, environmental pollution, and transportation time decreasing significantly.

A hybrid metaheuristic with learning for a real supply chain scheduling problem

In recent decades, research on supply chain management (SCM) has enabled companies to improve their environmental, social, and economic performance.This paper presents an industrial application of logistics that can be classified as an inventory-route problem. The problem consists of assigning orders to the available warehouses. The orders are composed of items that must be loaded within a week. The warehouses provide an inventory of the number of items available for each day of the week, so the objective is to minimize the total transportation costs and the costs of producing extra stock to satisfy the weekly demand. To solve this problem a formal mathematical model is proposed. Then a hybrid approach that involves two metaheuristics: a greedy randomized adaptive search procedure (GRASP) and a genetic algorithm (GA) is proposed. Additionally, a meta-learning tuning method is incorporated into our hybridized approach, which yields better results but with a longer computation time. Thus, the trade-off of using it is analyzed.An extensive evaluation was carried out over realistic instances provided by an industrial partner. The proposed technique was evaluated and compared with several complete and incomplete solvers from the state of the art (CP Optimizer, Yuck, OR-Tools, etc.). The results showed that our hybrid metaheuristic outperformed the behavior of these well-known solvers, mainly in large-scale instances (2000 orders per week). This hybrid algorithm provides the company with a powerful tool to solve its supply chain management problem, delivering significant economic benefits every week.