Supply Chain Simulation Research Articles

Blueberry supply chain: Critical steps impacting fruit quality and application of a boosted regression tree model to predict weight loss

Blueberries have increased in popularity in recent years due to their nutritional benefits and sensory characteristics. However, to preserve quality and extend shelf-life, they need to be maintained at refrigerated temperatures and high relative humidity, conditions that are not routinely met along the supply chain. Poor temperature management leads to quality deterioration, increasing waste/losses along the supply chain. This study examined the impact of each step along the supply chain on the physichochemical quality and shelf-life of blueberries, identifying the most critical steps from field to consumption. The following steps were identified as critical in the blueberry supply chain: shipping to distribution centre (DC) (72 h at 5 °C), store display (48 h at 15 °C), and consumer (48 h at 20 °C). Given the economic importance of weight loss and its link to fruit quality and shelf-life, a boosted regression tree (BRT) model was built to predict weight loss using the post-harvest environmental conditions of a simulated supply chain applying different temperature-time scenarios. The model explained 84 % of the variance on the test set and highlighted the interactions of supply chain conditions on weight loss.

Research on System Dynamics Simulation of Building Materials Supply Chain

The bullwhip effect of supply chain under non-information sharing and information sharing environment is analyzed theoretically. The model of building materials supply chain in two environments is constructed, and the system dynamics flow chart is established by Vensim PLE simulation software. The correctness of the theoretical analysis is verified by an example simulation. The sensitivity analysis of transportation delay time and manufacturer’s production cycle shows that extending transportation time can reduce manufacturer’s inventory, but raw material inventory in transit will increase; Shortening the production cycle of producers under the information sharing environment is more conducive to reducing the bullwhip effect of the supply chain.

The principal-agent problem in supply chain management – the simulation based framework

Abstract This research deals with a phenomenon well-known in socio-economic studies and referred to as the Agency Theory: the principal-agent problem. The agent is designated to act on behalf of the company owner, i.e., the principal, in the domain of supply chain management in the face of a supplier’s default uncertainty. Each of the players is gain-oriented, but their objective functions and the degree of risk-bearing may significantly differ, leading to an agent’s decisions not being optimal in terms of the principal’s outcome. This article proposes a multi-period supply chain simulation model that can be used to perform a supply chain optimization and comparison between the agent and the principal. The proposed framework allows for differentiating the model parametrization depending on the industry, in particular the consequences of the inability to deliver the end product, costs of keeping safety stocks, or the uncertainty regarding the suppliers’ delivery failure. As players’ objective functions, we consider expected profit-based indicators and measures taking the inter-period variance into account. We find that the agent’s actions may diverge from the principal’s optimum if the agent’s incentive system is not selected correctly. We also propose a solution that unifies the goals of the players. The recent COVID-19 pandemic amplifies the importance of such research. Many companies had to limit production capacities due to global lockdowns and, per the JIT production strategy, the prior safety stock levels were low.

Effect of price reduction on renewable energy technology supply chain performance and contract design

Over the past ten years, fossil fuel sources, particularly coal, dominate global electricity generation. With increasing concerns of large pollution emissions from coal-fired power plants and world-wide commitment to environmental change, clean and renewable energy has begun to surge. However, while the installation of renewable energy technology such as solar photovoltaic (PV) panels has risen globally, there has been a sharp reduction in the price of solar PV panels, which has created a challenge for manufacturers and retailers due to a rapidly changing market. This unique characteristic of renewable energy technology supply chains creates inefficiencies by incentivizing manufacturers and retailers to maintain stock levels that are too low prior to a price reduction. To address this challenge, this research models a renewable energy technology supply chain with one manufacturer and one retailer (who acts as an installer) that faces stochastic consumer demand. Applying inventory models with stochastic demand, this research aims to (1) demonstrate the negative impact of a price reduction on the supply chain by comparing to a model without a price reduction; (2) characterize the renewable energy technology manufacturer’s and retailer’s optimal stock and production policies with and without a compensation fee contract when a price reduction is present; (3) conduct sensitivity analysis by simulating supply chain performance with different parameter settings; and, (4) provide guidance on supply chain contract design to enhance the efficiency of a renewable energy technology supply chain.

Education and training of manufacturing and supply chain processes using business simulation games

Various studies confirm the positive outcomes of business simulation games, which can be effectively used in the education of manufacturing and supply chain processes. The use of them in education increases business knowledge, causes better understanding of business processes, improves decision making, problem-solving, and interpersonal communication skills. General business simulation games with manufacturing functions included are described briefly. Twenty-two specialized manufacturing and supply chain simulations are discussed in detail showing their features and decision-making possibilities. The study is useful for educators, trainers, and companies looking for practical learning methods. The discussion of the games gives them an opportunity to better understand available business simulations and be able to choose the appropriate one for their expected learning outcomes.

Covid-19 Pandemic Supply Chain Disruption and Simulation of Retail Store Resilience

Covid-19 Pandemic Supply Chain Disruption and Simulation of Retail Store Resilience

Predictive Sales and Operations Planning Based on a Statistical Treatment of Demand to Increase Efficiency: A Supply Chain Simulation Case Study

Forecasting is the basis for planning. Good planning is based on a good prediction of what is going to happen to prepare a company, a department, and their environments for certain future developments and their intermediate states. In this context, resources are allocated to these future states in the most efficient way, given a certain set of resource conditions. Although market volatility demands the high adaptability of companies’ operations, dynamic planning is still not widespread. As a result, the alignment of planning processes with potential scenarios is not given, leading to a lack of solution preparation in the long term, suboptimal decision-making in the medium term, and corrective measures in the short term, with higher costs and a lower service level. Therefore, the aim of this research is to propose a predictive approach that will help managers develop sales and operations planning (S&OP) with higher accuracy and stability. For this purpose, a methodology combining demand scenarios, statistical analysis of the demand, forecasting techniques, random number generation, and system dynamics was developed. The goal of this predictive S&OP is to predict the supply chain system’s behavior to generate plans that prevent potential inefficiencies, thereby avoiding corrective measures. In addition, to assess the methodology, the model is applied in the software Vensim, for an automotive producer´s supply chain, to compare the predictive S&OP model with a classical approach. The results show that the proposed predictive approach can increase a manufacturer’s efficiency by increasing its adaptability through the identification of potential inefficiencies and can also be used to prepare solutions.

Game—The Transportation Game

This paper presents an online educational game focusing on hierarchical procurement planning in a simulated forest supply chain with multiple companies. The purpose is to provide an understanding of the importance of individual decisions and their medium- to long-term impacts on the entire supply chain. The transportation game comprises three phases, each simulating hierarchical decision making when three competing companies (i.e., the game players) are making simultaneous decisions on the available resources. Each game phase also requires concurrent collaboration and competition. The phases represent different planning levels from long-term to short-term planning, considering the collaboration concept within the supply chain. The simulated supply chain objective is to minimize resource purchasing and transportation costs. The purchasing cost will be fixed after the first phase. The chance of decreasing transportation costs, however, is available until the end of the game. We develop three optimization models for each game phase. Once the game is finished, it compares the players’ results with optimal solutions prepared upfront. Finally, we present some comments about the game experience in various classrooms.

A centralised model predictive control framework for logistics management of coordinated supply chains of perishable goods

ABSTRACT This paper proposes a centralised model predictive control framework to address logistics management of supply chains of perishable goods. Meeting customer specific requirements is decisive to gain a competitive advantage in supply chain management. This fact motivates stakeholders to address solutions that continuously improve supply chain operations. The solution proposed in this work considers the supply chain as a dynamical system in a state-space representation where different categories of commodities, namely common goods and perishable goods, are included. Additionally, the dynamical model is able to store information of the complete supply chain regarding the quantity of commodities and the due time associated to the perishable goods. A centralised controller then collects the supply chain state information and optimises the commodity flow based on the model prediction over a fixed time horizon. The model predictive control solution assigns just-in-time commodity flows, schedules production according to customer demand (pull system) and monitors work-in-progress and in-transit commodities. The success of the proposed control approach is demonstrated in a numerical simulation of a three-tier supply chain following three distinct management policies.

Inventory optimization considering the vehicle capacity and specifics of cash flows at rental storage sites

The article presents a special modification of the EOQ formula and its application to the accounting of the cargo capacity factor for the relevant procedures for optimizing deliveries when renting storage facilities. The specified development will allow managers to take into account the following process specifics in the format of a simulated supply chain when managing inventory. First of all, it will allow considering the most important factor of cargo capacity when optimizing stocks. Moreover, this formula will make it possible to find the optimal strategy for the supply of goods if, also, it is necessary to take into account the combined effect of several factors necessary for practice, which will undoubtedly affect decision-making procedures. Here we are talking about the need for additional consideration of the following essential attributes of the simulated cash flow of the supply chain: 1) time value of money; 2) deferral of payment of the cost of the order; 3) pre-agreed allowable delays in the receipt of revenue from goods sold. Developed analysis and optimization procedures have been implemented to models of this type that are interesting and important for a business. This — inventory management systems, the format of which is related to the special concept of efficient supply. We are talking about models where the presence of the specified delays for the outgoing cash flows allows you to pay for the order and the corresponding costs of the supply chain from the corresponding revenue on the re-order interval. Accordingly, the necessary and sufficient conditions are established based on which managers will be able to identify models of the specified type. The purpose of the article is to draw the attention of managers to real opportunities to improve the efficiency of inventory management systems by taking into account these factors for a simulated supply chain.

Digital transformation of the Russian construction industry

Construction is an impactful industry and like everything impactful, it has to evolve with the needs and demands of the modern day consumers. The article is devoted to the analysis of the current state and prospects of development of digital technologies in construction. The fundamental concepts of digital economy, digital production and digital technologies are introduced; a peculiar “evolution” of the design process in construction is described (transition from so-called “paper-based” technologies to computer aided design systems and further to information modeling of construction objects). Construction technologies solutions and apps for the construction industry have significant growth potential, and we can nurture a cohort of new digital technology firms by supporting the development of connections with the construction industry, the broader IT sector, incubators and sources of capital. However, the largest scale impact is likely to be realised through effective implementation of BIM with the support of digital technology. Among the very topical issues raised in the article we should also highlight BIM - a fundamentally new approach in architectural and construction design, which includes creation of a computer model of a new building (structure), which carries all the information about the future of the object and is an instrument of control over its life cycle. Given the rapid pace at which new technologies and innovations are being developed, the specialization in Digital Technologies in Construction prepares graduates for the imminent, exciting and necessary, wide-scale digital transformation of the construction industry. Courses include Digital Technologies for Civil Engineering, BIM and 5D Planning, Technology and Innovation in Road Construction, Simulation and Optimization of Construction Processes and Construction Supply Chains and Digitization.

New Approaches in Meta-heuristics to Schedule Purposeful Inspections of Workshops in Manufacturing Supply Chains

Nowadays, with the growth of technology and the industrialization of societies, work-related accidents, and consequently the threat of human capital and material resources are among the problems of the countries of the world. The most important legal solution in most countries to control occupational accidents and illnesses is to conduct periodic site visits and identify hazardous sites. To the best of our knowledge, no study from the supply chain point of view has been reported to model and address this kind of problem. Thus, this paper is to select the best route that reduces the time elapsed between the workshops and the visit time of the inspectors by using two-tier supply chain simulation coupled with the vehicle routing problem (VRP) to give them more opportunity to visit more workshops. In this study, by considering the number of workshops, the limitation of the number of the existing inspectors and the priority of inspecting the workshops, a bi-objective mathematical model is presented. The main aims are to maximize the number of visited workshops and minimize travel times and workshops visit times. In this study, three meta-heuristics (i.e., SA, SEO and RDA) and two hybrid algorithms are used to address the model. Then, the quality of the meta-heuristics and hybrid algorithms are evaluated and compared by using four metrics. The SEO algorithm provides the best performance; however, in a long time, the hybrid GASA algorithm provides the worst performance. Finally, a real-case study is used to validate the presented model.

Process simulation, techno-economic evaluation and market analysis of supply chains for torrefied wood pellets from British Columbia: Impacts of plant configuration and distance to market

Improving economic competitiveness is the key for sustainable development of the wood pellet industry. To support this development, we have carried out a comprehensive techno-economic evaluation of five possible process configurations for production of conventional (CWP) and torrefied (TWP) wood pellets in the Canadian province of British Columbia (BC), based on process simulation with multi-scale models involved as illustrated in the graphical abstract. A novel heat integration strategy is proposed for the TWP production process to avoid the use of N2 and achieve auto-thermal operation. In comparison with CWPs, producing TWPs in the operating sequence drying, torrefaction, grinding, pelletization can reduce production costs by about 10% and reduce delivered costs to both domestic and overseas markets by about 20%. It is essential that the TWP plant is located in a region with abundant and low-cost feedstock, low electricity price, low labor cost, and efficient distribution logistics. Due to the low capital cost contribution (10%), torrefaction could be implemented by either building a new plant or upgrading an existing conventional pellet plant. The market analysis reveals that the future market for TWPs from BC is expected to lie outside Canada, in the Asia Pacific region, and Europe, unless significant domestic policy measures are introduced to promote Canadian use of TWPs.

Eliciting agents’ behaviour using scenario-based questionnaire in agent-based dairy supply chain simulation

ABSTRACT A scenario-based questionnaire is a survey method that aims to identify the respondents’ decision rules using their responses to a series of scenarios. It is rarely used in agent-based modelling and simulation (ABMS) with most researchers preferring a survey with closed questions as the data collection method. This is particularly true for ABMS studies in agri-food supply chains. In our paper, we design a scenario-based questionnaire to elicit the behaviour of agents in ABMS and apply it in a dairy supply chain case. Our findings suggest that respondents respond well to a scenario-based questionnaire as it relates more closely to their actual decision-making process. Furthermore, our experiment shows that the decision rules extracted using a scenario-based questionnaire improve ABMS validity.

Vaccine Supply Chains in Resource-Limited Settings: Mitigating Rainy Season Disruptions

Immunization is widely recognized as one of the most successful and cost-effective health interventions, preventing two to three million deaths from vaccine-preventable diseases each year. Although progress has been made in recent years, substantial operational challenges persist in resource-limited settings with frequent stock-outs contributing to sub-optimal immunization coverage and inequality in vaccine access. In this paper, we investigate the role of rainy season induced supply chain disruptions on vaccination coverage and inequalities. We develop a modeling framework combining spatial modeling — to predict flood disruptions in road networks — and a discrete-event simulation of a multi-tiered vaccine supply chain (VSC). Our models are fitted and validated using data from the Malagasy VSC network. Our baseline simulation predicts the national vaccination coverage with good accuracy and suggests that 67% of regions with low reported immunization coverage are affected by rainy season disruptions or operational inefficiencies, causing significant geographical inequalities in vaccine access. We investigate various mitigation strategies to increase the resiliency of VSCs and find that by strategically placing buffer inventory at targeted facilities prior to the rainy season the proportion of children receiving all basic vaccines in these areas is increased by 7% and the geographical inequality in vaccination coverage is reduced by 11%. By also increasing the replenishment frequency from every third month to every month, the national vaccination coverage improves by 37%. Our results contribute to achieving the UN Sustainable Development Goals (SDGs) by providing actionable insights for improving vaccination coverage (SDG 3) and investigating the resiliency of the VSC to increased flooding due to climate change (SDG 13).

A Study on Various Forecasting Methods and Their Effects on the Bullwhip Effect and Inventory in the Simulated Supply Chain

A Study on Various Forecasting Methods and Their Effects on the Bullwhip Effect and Inventory in the Simulated Supply Chain

Modelling and Simulation of Fresh-Product Supply Chain Considering Random Circulation Losses

Modelling and Simulation of Fresh-Product Supply Chain Considering Random Circulation Losses

Simulation of a stochastic multi-echelon distribution supply chain under a continuous inventory control policy

Multi Echelon Distribution System (MEDS) is a multifaceted system focusing on integration of all factors involved in the entire distribution process of finished goods to customers. This paper proposes a simulation framework at the operational level of MEDS. The proposed model includes three echelons, based on discrete-event simulation approach, where the performed operations within our system are depending on several key variables that often seem to have strong interrelationships. It is necessary to simulate such complicated system, in order to understand the whole mechanism, to analyze the interactions between various components and eventually to provide information without decomposing the system. The simulation framework is used to evaluate the performance of the considered system at initial conditions and to compare it with different scenarios generated by simulation running. The study concludes with an analysis of system performance and the finding results according to each scenario.  Â

Bypassing Data Issues of a Supply Chain Simulation Model in a Big Data Context

Supply Chains (SCs) are complex and dynamic networks, where certain events may cause severe problems. To avoid them, simulation can be used, allowing the uncertainty of these systems to be considered. Furthermore, the data that is generated at increasingly high volumes, velocities and varieties by relevant data sources allow, on one hand, the simulation model to capture all the relevant elements. While developing such solution, due to the inherent use of simulation, several data issues were identified and bypassed, so that the incorporated elements comprise a coherent SC simulation model. Thus, the purpose of this paper is to present the main issues that were faced, and discuss how these were bypassed, while working on a SC simulation model in a Big Data context and using real industrial data from an automotive electronics SC. This paper highlights the role of simulation in this task, since it worked as a semantic validator of the data. Moreover, this paper also presents the results that can be obtained from the developed model.

Poor-quality antimalarials further health inequities in Uganda.

Substandard and falsified medications are a major threat to public health, directly increasing the risk of treatment failure, antimicrobial resistance, morbidity, mortality and health expenditures. While antimalarial medicines are one of the most common to be of poor quality in low- and middle-income countries, their distributional impact has not been examined. This study assessed the health equity impact of substandard and falsified antimalarials among children under five in Uganda. Using a probabilistic agent-based model of paediatric malaria infection (Substandard and Falsified Antimalarial Research Impact, SAFARI model), we examine the present day distribution of the burden of poor-quality antimalarials by socio-economic status and urban/rural settings, and simulate supply chain, policy and patient education interventions. Patients incur US$26.1 million (7.8%) of the estimated total annual economic burden of substandard and falsified antimalarials, including $2.3 million (9.1%) in direct costs and $23.8 million (7.7%) in productivity losses due to early death. Poor-quality antimalarials annually cost $2.9 million to the government. The burden of the health and economic impact of malaria and poor-quality antimalarials predominantly rests on the poor (concentration index −0.28) and rural populations (98%). The number of deaths among the poorest wealth quintile due to substandard and falsified antimalarials was 12.7 times that of the wealthiest quintile, and the poor paid 12.1 times as much per person in out-of-pocket payments. Rural populations experienced 97.9% of the deaths due to poor-quality antimalarials, and paid 10.7 times as much annually in out-of-pocket expenses compared with urban populations. Our simulations demonstrated that interventions to improve medicine quality could have the greatest impact at reducing inequities, and improving adherence to antimalarials could have the largest economic impact. Substandard and falsified antimalarials have a significant health and economic impact, with greater burden of deaths, disability and costs on poor and rural populations, contributing to health inequities in Uganda.