Total Logistics Research Articles

The Means of Sea Transportation

Sea transportation as part of the national transportation system needs to be developed in order to realize an archipelago insight that unites all regions of Indonesia, including the archipelago seas as a national territory unit. The development of sea transportation must be able to drive Indonesia's development. Sea transportation makes a huge contribution to the world economy where the transportation of goods is the most important part of the sea transportation business where more than seven billion tonnes of goods are sent by sea every year. The effectiveness of shipping operations will reduce operating costs which will have a big impact on both consumers and transportation service providers themselves. It should be noted that the contribution of sea transportation is becoming increasingly important because the value of the costs incurred is the smallest when compared to the cost of land or air transportation. In addition, efficiency in the transportation and distribution process is one of the important things because the proportion of transportation costs can reach 66% of the total logistics costs. Considering the geographical condition of Indonesia as the largest archipelagic country in the world and two-thirds of its territory is water, Indonesia needs a large enough mass sea transportation to support the distribution of goods and to mobilize passengers. An effective and efficient transportation system that is integrated between transportation modes is essential to create a reliable and dynamic national distribution pattern. It cannot be denied that sea transportation in an archipelagic country such as Indonesia has become the main backbone of the movement of large-scale distribution of goods using ships. From an economic and business perspective, the use of transportation by ships is more effective and has great benefits. So that with the existence of marine transportation infrastructure for moving goods from one place to another, it is hoped that the economic activities of the community will be followed by a positive impact in improving the economy of a region.

Multi-objective robust mathematical modeling for emergency relief in disaster under uncertainty

This paper presents a robust location-allocation planning problem for emergency relief in a disaster situation, which is formulated as a robust optimization model. It is a multi-objective, multi-commodity, multi-vehicle and multi-level logistics model considering injury variety through service prioritizing for more injuries and considering unmet demand of particular item type in various damaged areas, public donation of different relief goods, using capacitated medical centers and emergency centers regarding damage type and capacitated relief distribution centers and disaster management centers. This a non-linear mixed-integer programming model that simultaneously optimizes three objectives; i.e., maximizing service fairness to damaged areas, maximizing fair commodity disaster management, and minimizing the total logistics cost. To solve such a hard problem, an NSGA-II is developed and the Taguchi method is applied to adjust its parameters. The e-constraint method is used for the evaluation of the proposed algorithm performance. Three comparison metrics, including diversification, spacing and mean ideal distance, are used. The results verify the algorithm’s effectiveness in a reasonable computational time. Eventually, to examine the applicability of the presented model and the proposed algorithm, a case study is analyzed in the area located in the north of Iran, known with historical earthquake records and aggregated active faults.

Simulating long-term performance of regional distribution centers in archipelagic logistics systems

Indonesia has reevaluated its archipelagic logistics system to implement a strategic shift from a point-to-point network to a hub-and-spoke network, with a plan to establish seven new regional distribution centers (RDCs). To supplement the previous qualitative assessment of the plan and to potentially justify continuing with its implementation, this paper aims to evaluate the prospective long-term performance of the planned RDCs within a hub-and-spoke (HS) network. The chosen methodology for this analysis is a hybrid of optimization and simulation, using an agent-based modeling and simulation platform that incorporates a geographic information system (GIS) element to provide a realistic geographical context. This constitutes a relatively novel innovation in logistics research. Experiments were developed to estimate the logistics performance of the hub-and-spoke network and planned RDCs, as well as to identify potential problems such as bottlenecks at the RDCs and the relative (in)efficiency of the selected multimodal transport. Transport costs, inventory costs, and the order backlog of RDCs are evaluated based on the average results from 100 replications. Outcomes from the model are validated against empirical data on Indonesia’s logistics costs from the World Bank. Model results indicate that the hub-and-spoke network performs better than the point-to-point network when it comes to transportation costs. Since this is found to be the dominant element of total logistics costs, appropriate modal choice and route optimization are, therefore, critical to reducing logistics costs. The planned RDCs are found to have significant imbalance in their loadings, which is likely to produce bottlenecks. The paper concludes that a planned move to a hub-and spoke system is appropriate and that the planned investment in the RDCs is therefore justified. However, there is a need to streamline the predicted loadings at the RDCs to avoid bottlenecks. Our results suggest that the government should reopen the case and reevaluate the locations and coverage of each RDC. More generically, it is concluded that the application of hybrid optimization and simulation using agent-based modeling and simulation is feasible and the methodological approach adopted herein is generalizable to other archipelagic logistics systems.

Slotting y picking: una revisión de metodologías y tendencias

espanolLa gestion de cadenas de suministro implica la formulacion de modelos y metodologias de mejora y optimizacion de operaciones y procesos internos, con el fin de aumentar la eficiencia y la capacidad de respuesta y a su vez reducir costos. En la gestion de cadenas de suministro, las actividades llevadas a cabo en almacenes y centros de distribucion son fundamentales para garantizar un nivel de servicio optimo y para obtener ahorros significativos en los costos logisticos totales. El slotting y el picking son dos actividades fundamentales en la operacion y administracion eficiente de las instalaciones de almacenamiento. Por ello, en este articulo se hace una revision bibliografica exhaustiva sobre los modelos y metodologias usados en la optimizacion de dichas actividades entre los anos 2000 y 2018, identificando aplicaciones indirectas en otro tipo de industrias y oportunidades y tendencias de investigacion, considerando los factores que influyen en los flujos de materiales y componentes estocasticos en la planeacion de inventarios: acomodo dinamico, analisis de rutas, metodologias de ubicacion de clusteres y division de almacen por tipo de productos. EnglishSupply Chain Management is based on formulating models and methodologies to improve and optimize operations and internal processes, in order to increase efficiency and response capacity and simultaneously reduce costs. In Supply Chain Management, activities carried out in warehouses and distribution centers are critical to ensure an optimum service level and to obtain significant savings in total logistics costs. Slotting and picking are two fundamental activities in the efficient warehouses operation and management. For this reason, we made in this article an exhaustive bibliographic review on models and methodologies used for optimizing slotting and picking, between 2000 and 2018, identifying indirect applications in other types of industries and research opportunities and trends, considering the factors that influence the flow of materials and stochastic components in inventory planning: dynamic accommodation, route analysis, cluster location methodologies and warehouse division according to the type of products.

A robust neutrosophic fuzzy-based approach to integrate reliable facility location and routing decisions for disaster relief under fairness and aftershocks concerns

Relief distribution and victim evacuation are the crucial emergency relief operations after sudden-onset disasters to alleviate the repercussions of catastrophes in the concerned areas, although aftershocks and unfair distribution of relief items can affect these planning and beget plenty of undesirable reflections. In this paper, a new multi-objective reliable optimization model to organize a humanitarian relief chain is rendered to make a broad range of decisions, including reliable facility location-allocation, fair distribution of relief items, assignment of victims, and routing of trucks. For this purpose, the first objective function is to minimize the total logistics costs, the second one is to minimize the total time of relief operations, and the third one minimizes the variation between upper and lower bounds of transportation cost of distribution centers to regulate the workload of them. What is more, due to the fact that the uncertain essence of catastrophes, such as demand, the capacity of facilities, miscellaneous costs and transportation times, a novel uncertainty approach, including robust optimization and the neutrosophic set, is proposed to surmount these obstacles. Ultimately, a real case study is examined to illustrate the validity of the proposed model and solution method. The obtained results reveal that via increasing the capacity of the emergency centers by 30%, the total cost of the humanitarian relief network is reduced by 18%, and the operating time is reduced by 9%. What is more, if the probability of disruption in one of the distribution centers reaches zero, the logistics costs will be reduced to approximately 20%, and also the distance between the maximum and minimum distance traveled will be reduced by 30%, and the workload between distribution centers will be more balanced.

Chasing END TB 2025: Arithmetic needed for logistics!

India adopted changes in NTEP (Erstwhile RNTCP, Revised National TB Program, renamed as National TB Elimination Program) in the recent years with an aim to End TB by 2025 way ahead of the global target of ending TB by 2030. It is taking a long time for the changes to trickle down to the grass root level to change the behavior of the ground level force to understand and adopt to the changes that are being ordered and several other changes that are being pushed to the field in tandem. This has made field workers to be on their toes to understand and implement all the changes. The logistics like referral forms, GeneXpert/CBNAAT cartridges, slides etc., required for the program need to be calculated and used as per the changes. Shortages in the procurement or indenting will result in hampering the smooth functioning of the program. Accordingly, we calculated the logistics required for the patients estimated to occur in an area depending on the previous year's patient load. The breakup of the patients was adopted from the available references given. Also, the 2019 data of the load of different type of patients in India and the world were also taken. Total logistics were calculated for two hundred patients. Based on the calculations, a generic formula was derived. When the total number of patients in the previous year/quarter/or any period is N, then below is the formula which can estimate the required logistics for the next similar period.

Cost and Scenario Analysis of Intermodal Transportation Routes from Korea to the USA: After the Panama Canal Expansion

This study is aimed at suggesting the most economical transportation route by comparing seven different Korea–US intermodal transportation routes for automotive parts exported to Southeastern USA. To keep up with the global competition of parts makers, which are expanding their markets based on advanced technology and enormous capital, Korean automotive parts makers also need to actively advance their markets overseas. From this point of view, selecting an efficient transport route and transportation modes for overseas export is essential. To this end, the most efficient transportation route from the perspective of total logistics cost was selected by adapting the inventory-theoretic model, using information such as the logistics status of a specific company and the logistics freight rates and transit time for the third quarter of 2019. Thus, the scenario analysis was conducted assuming that variables—namely transportation cost per unit, commodity value, inventory cost and additional conditions such as terminal free time—were modified. Through this study, the optimal transportation route was selected by fully considering and predicting the total logistics cost component and the variability of the major factors.

Biobjective low-carbon location-routing problem for cold chain logistics: Formulation and heuristic approaches

Sustainable development is critical to cold chain logistics, including its economic, environmental, and social effects, especially in road transportation. To simultaneously address these issues, we propose a comprehensive cold-chain-based low-carbon location-routing-problem optimization model to minimize the total logistics costs and client and vehicle waiting time. The first objective comprises the fixed costs of depots to open and vehicles to rent, vehicle renting cost, driver salaries, fuel consumption cost, carbon emission costs, and damage costs of cargos that need to be refrigerated or frozen. The second objective consists of the waiting time of clients and vehicles to improve client satisfaction and the efficiency of the cold chain logistics network. In the proposed problem, we developed a strategy for improving the efficiency of the cold chain logistics network by mixing the types of cargos arranged in one vehicle. Aiming at efficiently solving the proposed model, six well-known multi-objective evolutionary algorithms (MOEAs) were used by combining an efficient framework, and first (FI) and best-improvement (BI) search mechanisms were considered. In the experiments, we examined the effectiveness of six MOEAs inserting the proposed framework and search mechanisms, and the result showed that NSGA-II/FI, SPEA2/FI, and NSGA-II/BI were the top three MOEAs. In the extensive experiments, the results showed that the delivery strategy, depot cost, depot capacity, crowding distance, and traveling speed have significant effects on the Pareto front, fuel consumption, carbon emission, vehicle and client waiting times, traveling distance, and traveling time.

Assessing Total Logistics Costs

Logistics infrastructure is widely known as the most significant economics hurdle in Indonesia over recent decades due to the limited logistics infrastructure. This study aims to examine total logistics costs during the execution of several cement projects in Indonesia within the period 2010-2018. The panel data method of eight cement projects in Indonesia has been developed, analysed, and measured. Due to the limited logistics infrastructures, the logistics cost rose to 27.129% of the Gross National Product (GNP) in Indonesia. Further, this paper provides suggestions for Indonesia's government to develop logistics infrastructure.

Determining value of logistics costs in projects: empirical findings based-on executing several cement projects in Indonesia

This research tries to shed light on precise values of logistics costs that so far undisclosed. The values are important for every project planners to evaluate, control and monitoring, and especially imperative for procurement activities. Tender, bidding, and defining the scope of contracts and value can be well organized without time-consuming. This research uses methodology previously developed by Subiyanto (2020a) and discussed only a few particular and directly related to the logistics. The model had been decomposed by utilizing path analysis and the data had been regressed to define variables as the most inflator for logistics. The findings are total logistics costs in Indonesia generally at around 14.6% to total costs of investment. It consists following of insurance cost 0.11%, costs for customs clearance 6.52%, foreign logistics costs 6.62%, domestic manufacture 0.47%, and domestic logistics costs 0.89%. This research is not discussing logistics costs relating to human resources, human travelling, and internal logistics conducted by vendors or contractors as the scope included counted within their procurement contract. These results are important as guidance for project planners, controllers, and other parties to prepare costs more precisely. Negotiating to the banks will be easier as the more precise amount of budgets had been estimated. Due to the important values that have been identified, there will help transparency and governance conducting the projects. Procurement processes involving societies are more objective and better. This is a novelty finding as previous researchers have not decided yet.

Decomposition-based hyperheuristic approaches for the bi-objective cold chain considering environmental effects

This paper proposed a novel approach for a practical version of the cold chain, namely location-routing problem-based low-carbon cold chain (LRPLCCC). In the proposed bi-objective model, the first objective is the total logistics cost, including the fixed costs of the opened depots and leased vehicles, as well as the cost of fuel consumption and carbon emissions, and the second is to minimize the amount of quality degradation that aims at improving clients’ satisfaction and maintain product freshness. The cargos of clients are classified into three types: general, refrigerated, and frozen cargos. Since the presented problem is NP-hard, a novel multi-objective hyperheuristic (MOHH) was proposed to obtain the Pareto solutions. In this framework, three selection strategies were developed to improve the performance of MOHH, that is, random simple, choice function, and FRR-MAB (fitness rate rank based multi-armed bandit), and three acceptance criteria using the decomposition approaches in MOEA/D were also developed, namely penalty-based boundary intersection, Tchebycheff, and modified Tchebycheff approaches. Extensive experiments were provided to verify the efficiency of the proposed algorithms and assessed the effects of algorithm parameters on the Pareto front. The results showed that the efficiency of the proposed algorithm outperforms several existing well-known multi-objective evolutionary algorithms (MOEA).

Otimização da rota de veículos e seus impactos na logística de distribuição: um estudo de caso em uma distribuidora de produtos de limpeza

Em decorrência de um mercado cada vez mais dinâmico e competitivo, as atividades logísticas ganham destaque como diferencial competitivo em uma organização, exigindo sistemas de distribuição cada vez mais eficientes, posto que os custos de transporte representam a maior parcela dentre os custos logísticos. Nesse contexto, a presente pesquisa visa otimizar a rota de veículos em uma distribuidora de produtos de limpeza localizada. Dessa forma, a metodologia empregada nesse trabalho consiste em um estudo de caso, no qual os dados foram coletados por meio de entrevistas semiestruturadas realizadas com o gestor e demais colaboradores em conjunto ao acesso as informações do sistema de ERP da organização. Após a obtenção dos dados, estes foram tabulados em planilhas eletrônicas do Microsoft Excel para uma posterior análise por meio de um comparativo entre a rota atual e a otimizada pelo software logístico LOGWARE. Os resultados alcançados indicam que as empresas podem obter benefícios e melhorias significativas na logística de distribuição, que para esse caso específico analisado durante 18 dias promoveu uma redução no deslocamento de 183,5 km, no tempo de atendimento de 6,1 h e ainda, uma economia monetária de aproximadamente 12,34% em seus custos variáveis. Portanto, conclui-se que é de fundamental importância o uso de métodos computacionais no auxílio da elaboração de rota de distribuição em uma empresa, especialmente considerando a importância dos custos de transportes no custo de logístico total.

Robust possibilistic programming for joint order batching and picker routing problem in warehouse management

Decisions made for designing and operating a warehouse system are of great significance. These operational decisions are strongly affected by total logistics costs, including investment and direct operating costs. The number of orders made by customers in the logistics section of warehouse management is very high because the number, type of products and items ordered by different customers vary broadly. However, machines layout for picking up products at logistics centres is minimal, inflexible, and, in some cases, inconclusive. In this study, we address joint order batching procedures of orders considering picker routing problem as a mixed-integer programming model. Extensive numerical experiments were generated in small, medium, and large sizes. In order to consider the uncertainty of parameters, we applied robust possibilistic programming for this problem. Three different meta-heuristic algorithms; genetic algorithm, particle swarm optimisation algorithm, and honey artificial bee colony algorithms are used as solution approaches to solve the formulated model. The performance of solution approaches over the problem was analysed using several test indexes. In all three group examples, there was no significant difference among mean values of the objective function, while there was a remarkable difference among computing times.

Comprehensive Evaluation of Regional Logistics Competitiveness Considering Multiple Reference Points and Dynamic Index Improved Analytic Hierarchy Process

The development of the regional economy cannot be separated from the support of regional logistics, as the scientific decisions of regional logistics are helpful to promote the healthy development of the regional economy. The comprehensive evaluation of regional logistics competitiveness is the premise and foundation of regional logistics scientific decision-making; the evaluation index system, evaluation data, and index weight are the key links affecting a comprehensive evaluation. In order to improve the quality of a comprehensive evaluation, the study aims at addressing problems such as the evaluation index system of regional logistics competitiveness being complex and scattered, the normalized distribution of the evaluation data being extremely asymmetric and seriously deviating from the normal distribution, and the logic of calculating index weights by the analytic hierarchy process (AHP) not being accurate. To do this, a triangle model of regional logistics competitiveness is constructed based on Porter’s diamond model, and the evaluation index system of regional logistics competitiveness is refined from the three dimensions of resource supply, logistics service, and market demand. Based on the concept of symmetry theory, a normalization method of segmental mapping with quartiles as multiple reference points is proposed, which improves the distribution rationality, symmetry, and distance discrimination of normalized data. The dynamic index scale is used to determine the scale of the analytic hierarchy process, and the evaluation matrix is constructed based on the importance level grading table; the index weights are directly solved without a consistency check, which improves the logical accuracy of a subjective evaluation. Based on the data of segment mapping, the comprehensive evaluation value of the evaluation object is calculated, and the competitiveness of regional logistics is compared and ranked, which improves the differentiation and consistency of the results. Through the comparative analysis of the calculation results, it was proven that the improvement of the data standardization method is necessary when the range is too large. The method in this paper can make the distribution of data standardization with a range too large closer to the normal distribution. It was found that the ranking of regional logistics competitiveness is highly consistent with the total social logistics, and that the total amount of regional logistics has an important reference value for the competitiveness of regional logistics. The ranking calculated by the indicators and methods in this paper has a certain reference value for regional logistics decision-making.

Data-driven decision and analytics of collection and delivery point location problems for online retailers

The location of collection and delivery points (CDPs), impacted by online customers’ demand data, plays an important role for online retailers. While previous delivery points optimization researches do not use customer behavior data, we propose new models, integrating with customer behavior data analysis, to optimize collection and delivery points for online retailers. We explore a real customer behavior data and use totally 257,685 users’ records (212,062 records for training set and 45,623 records test set). We first estimate the customer purchase probability by five data mining models. Based on the estimation results, we establish two facility location models to respectively optimize the attended and unattended CDPs locations with the objective of cost minimization. Our numerical experiments make a quantitative analysis of customer service level and location cost. Our results can further help online retailers to decide the suitable CDPs with trading off the consumer service level and the total logistics cost. We make interesting contributions: (i) we analyze real customer behavior data and find that gradient boosting trees algorithm outperform other four algorithms when estimating customers’ purchase probabilities; (ii) We propose a new data-driven method integrating data mining models and facility location models to determine CDP locations for online retailers.

Joint-optimization of a truck appointment system to alleviate queuing problems in chemical plants

Numerous studies have proposed the use of a Truck Appointment System (TAS) to alleviate traffic congestion at logistics sites. Unfortunately, the implementation of such a system was often optimised based on the interest of a single stakeholder. Meanwhile, long truck queues have been observed in many chemical plants. This study aims to evaluate the TAS performances to mitigate traffic congestion in chemical plants from the multi-stakeholder perspective. We proposed a joint-optimization model to accommodate various interests on the site. An improved fluid-flow approximation was developed to estimate the time-dependent performance of the system. The results suggest that the benefit of TAS is mostly enjoyed by the site manager through the reduction of site overtime, while the benefits for trucking companies are found to be marginal. Through numerical experiments, we show that the proposed joint-optimization model is effective in redistributing the benefits of TAS across the stakeholders, while keeping the total logistics costs to a minimum.

Total factor logistics productivity: A spatial approach to the Italian regions

Abstract The evolution of economic systems has produced a new vision of the spatial and localization models in which transport and logistics are deemed to play a major role in generating value to economic areas. Different methods of parametric and nonparametric analysis are applied to deal with the issue of the efficiency and competitiveness of territories. Using an original dataset, we set out to estimate productivity differentials between companies or industries located in different Italian regions. Unlike previous works aimed at investigating logistics productivity, this paper focuses on the main variables affecting Total Factor Productivity (TFP) in the transport and logistics sectors. The findings of this study contribute to filling the gap in transport related literature on the issue of ‘Total Factor Regional Logistics Productivity’ (TFRLP), identifying the most important elements able to improve the TFP level using an econometric estimate. In a second step, we carry out a comparison among the different Italian regions with a view to testing the relationship between the logistics and economic activities of a territory. The results of this latter analysis show that, in the different Italian regions, the logistics sector is characterised by a high resilience capacity, so innovation in the logistics industry is a strong element in driving regional exports.

A novel bi-objective model of cold chain logistics considering location-routing decision and environmental effects.

Economic, environmental, and social effects are the most dominating issues in cold chain logistics. The goal of this paper is to propose a cost-saving, energy-saving, and emission-reducing bi-objective model for the cold chain-based low-carbon location-routing problem. In the proposed model, the first objective (economic and environmental effects) is to minimize the total logistics costs consisting of costs of depots to open, renting vehicles, fuel consumption, and carbon emission, and the second one (social effect) is to reduce the damage of cargos, which could improve the client satisfaction. In the proposed model, a strategy is developed to meet the requirements of clients as to the demands on the types of cargos, that is, general cargos, refrigerated cargos, and frozen cargos. Since the proposed problem is NP-hard, we proposed a simple and efficient framework combining seven well-known multiobjective evolutionary algorithms (MOEAs). Furthermore, in the experiments, we first examined the effectiveness of the proposed framework by assessing the performance of seven MOEAs, and also verified the efficiency of the proposed model. Extensive experiments were carried out to investigate the effects of the proposed strategy and variants on depot capacity, hard time windows, and fleet composition on the performance indicators of Pareto fronts and cold chain logistics networks, such as fuel consumption, carbon emission, travel distance, travel time, and the total waiting time of vehicles.

Modelling Wholesale Company’s Supply Chain Using System Dynamics

Abstract Research is based on wholesale and distribution operations of real-life case company, and in this setting, the most critical part of company’s supply chain is the inventory replenishment to warehouse (Distribution Center) as well as fulfilling and delivering customers’ orders. Different Economic Order Quantity (EOQ)-based models have been considered (Reorder Point, Reorder Point with pipeline on order inventory, and “pulse train”). Simulation system evaluates annual total logistics costs. Results show that in an environment, where local warehouse inventory levels are rather high and replenishment order quantity is rather small, it is important have frequent shipments divided in suitable intervals. In simulation model, this could be done e.g. with the use of “pulse train” function or incorporating pipeline on order inventory in order decision. The research findings are valid for a small-scale supply chain servicing small and geographically limited markets with clients assuming high customer service levels (e.g. 24-hours lead time). For bigger markets, the cross-docking based supply chain models are worth considering in simulations.

The impact of an upstream buyer consolidation and downstream intermodal rail-based solution on logistics cost in the China-Europe container trades

In the typical structure of the supply chains associated with the Asia-Europe container trade, containers are stuffed in China, and the cargo is subsequently cross-docked at a major European logistics hub or a distribution centre closer to the customer for further distribution to the final retailing points. However, this solution may not be optimal in the perspective of total logistics cost. Upstream buyer consolidation at the origin and a downstream rail-based intermodal system at the destination has been regarded as a potential solution for reducing the costs of supply chains. The purpose of this study is to identify the benefits of this potential solution. This research is based on a case study obtained from a Swedish retailer with a chain of retailing points in Scandinavia and Poland. A comparative analysis is used to reveal the cost advantage of the alternative solution. Our findings suggest that this alternative solution may reduce monetary logistics cost from two aspects: converting LCL shipments to FCL shipments and converting almost full 20-foot FCL shipments to 40-foot FCL shipments. In addition, certain non-monetary benefits of buyer consolidation, including reduced possibility of delay, reduced complexity, reduced carbon emissions and reduced activities in the destination countries, are illustrated in this paper. Based on our calculation, the cost-saving potential of the new alternative solution illustrated in this case study is considerable, which suggests that such solutions might be desirable as an alternative to the typical arrangements in this trade.