Risk management in perishable food distribution operations

2019 ◽  
Vol 120 (2) ◽  
pp. 291-311
Author(s):  
Yingchao Wang ◽  
Chen Yang ◽  
Hanpo Hou
Keyword(s):  
Numerical Simulation ◽  
Food Safety ◽  
Vehicle Routing Problem ◽  
Routing Problem ◽  
Content Type ◽  
Distribution Costs ◽  
Risk Coefficient ◽  
Safety Risks ◽  
Whale Optimization ◽  
Food Safety Risk

Purpose The purpose of this paper is to predict or even control the food safety risks during the distribution of perishable foods. Considering the food safety risks, the distribution route of perishable foods is reasonably arranged to further improve the efficiency of cold chain distribution and reduce distribution costs. Design/methodology/approach This paper uses the microbial growth model to identify a food safety risk coefficient to describe the characteristics of food safety risks that increase over time. On this basis, with the goal of minimizing distribution costs, the authors establish a vehicle routing problem with a food safety Risk coefficient and a Time Window (VRPRTW) for perishable foods. Then, the Weight-Parameter Whale Optimization Algorithm (WPWOA) which introduces inertia weight and dynamic parameter into the native whale optimization algorithm is designed for solving this model. Moreover, benchmark functions and numerical simulation are used to test the performance of the WPWOA. Findings Based on numerical simulation, the authors obtained the distribution path of perishable foods under the restriction of food safety risks. Moreover, the WPWOA can significantly outperform other algorithms on most of the benchmark functions, and it is faster and more robust than the native WOA and avoids premature convergence. Originality/value This study indicates that the established model and the algorithm are effective to control the risk of perishable food in distribution process. Besides, it extends the existing literature and can provide a theoretical basis and practical guidance for the vehicle routing problem of perishable foods.

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.

scholarly journals Employed in the foodservice industry: likelihood of intervention with food safety threats

2020 ◽  
Vol 34 (2) ◽  
pp. 243-262
Author(s):  
Robin B. DiPietro ◽  
Kimberly Harris ◽  
Dan Jin
Keyword(s):  
Food Safety ◽  
Safety Culture ◽  
Production Equipment ◽  
Personal Hygiene ◽  
Sample Population ◽  
Content Type ◽  
Safety Risks ◽  
Restaurant Employees ◽  
Employee Behaviors ◽  
Food Safety Culture

PurposeThe purpose of this study was to investigate restaurant employee behaviors and their likelihood of intervening when witnessing food safety threats.Design/methodology/approachA mixed method was used for this study with the focus group interview and survey questionnaire. A total of eight focus groups ranging in number of participants from to 6 to 12 were asked to respond to presented scenarios that depicted restaurant employees committing food safety risk behaviors and threats in the restaurant environment that would present food safety risks such as out-of-stock bathroom supplies, dirty tables in the restaurant dining area, employee personal hygiene issues and unclean production equipment. These participants were also asked to complete a draft of the survey that would later be edited and distributed to the sample population.FindingsResults suggest that social norms and perceived severity of threats impact the likelihood that restaurant employees will intervene. Implications for academics and practitioners are discussed.Originality/valueThis study was special as it provides a synthetic viewpoint that considers how service organizations can work to do a better job of interviewing employees before starting their jobs about their beliefs and personal practices of food safety at home, their previous work in the restaurant industry and food safety culture that they may have worked in before, as well as increasing the communication in restaurants to build a food safety culture. These practices can help to lower risks to the public regarding food safety and can help to build relationship trust in the brands that we all love to indulge in when dining out.

Regional Character, Restaurant Size, and Food Safety Risk: Evidence from Food Safety Violation Data in Gansu Province, China

2020 ◽  
Vol 83 (4) ◽  
pp. 677-685 ◽  
Author(s):  
YONGZHONG SHA ◽  
XIANGRONG SONG ◽  
JIAN ZHAN ◽  
LI LU ◽  
QINGXIA ZHANG ◽  
...  
Keyword(s):  
Economic Development ◽  
Food Safety ◽  
Population Density ◽  
Negative Binomial ◽  
Gansu Province ◽  
Health Concern ◽  
Safety Risk ◽  
Safety Risks ◽  
Food Safety Risk ◽  
Regional Character

ABSTRACT Restaurants are a place where food is prepared and cooked directly for customers. Food safety in restaurants is a public health concern and a multidisciplinary issue that needs to be explored. To protect the health of consumers and identify external factors that may affect food safety risk, this study explores how economic development and population density at the local level relate to food safety inspection outcomes in restaurants of different sizes. Using food safety violation data from 2017 and 2018, we categorized restaurants in Gansu Province, China, into small and large ventures to examine the relationships among regional character, restaurant size, and food safety risk. Data were analyzed using Mann-Whitney U tests and negative binomial regression models. Our results show that large restaurants have a higher food safety risk than small restaurants. Moreover, the region with the lowest level of economic development had the highest food safety risk, while the region with the lowest population density had insufficient local inspections. By providing insight into which establishments demonstrate the highest food safety risks, our findings contribute to the development of processes that seek to effectively identifying food safety risks. HIGHLIGHTS

scholarly journals Social Co-Governance for Food Safety Risks

2018 ◽  
Vol 10 (11) ◽  
pp. 4246 ◽  
Author(s):  
Linhai Wu ◽  
Pingping Liu ◽  
Yuxin Lv ◽  
Xiujuan Chen ◽  
Fu-Sheng Tsai
Keyword(s):  
Food Safety ◽  
Social Innovation ◽  
Relevant Literature ◽  
Policy Implications ◽  
Future Research ◽  
Social Forces ◽  
Multiple Stakeholders ◽  
Safety Risks ◽  
Government Enterprise ◽  
Food Safety Risk

We review relevant literature to propose the connotation and operation logic of food safety co-governance, systematically constitute by roles, functions, as well as the boundaries of public government, enterprise, and social forces. The major thesis is that social co-governance is a kind of societal-wide innovation (i.e., social innovation) that integrates diverse resources and efforts from multiple stakeholders for better and sustainable development of an economy’s food institution and system. We then put forward a prospect of the future research on food safety risk co-governance. Theoretical, practical, and policy implications are discussed.

Risk measurement framework

2013 ◽  
Vol 115 (8) ◽  
pp. 1073-1089 ◽  
Author(s):  
Ruth M.W. Yeung ◽  
Wallace M.S. Yee
Keyword(s):  
Food Safety ◽  
Management Strategies ◽  
Principal Component ◽  
Risk Measurement ◽  
International Travel ◽  
Safety Risk ◽  
Content Type ◽  
Measurement Framework ◽  
Five Factors ◽  
Food Safety Risk

PurposeAdapting from the extant literature, this paper aims to present an empirical framework of risk measurement in the context of food safety risk in overseas destinations.Design/methodology/approachData were collected from 715 respondents visiting Macau in October 2008 by using intercept method. Principal component analysis followed by confirmatory factor analysis were utilised for data analysis.FindingsThe research yielded 12 factors, of which five factors, namely Dread, Framing effect, Controllable, Regulation and Past experience measure risk characteristics; two factors, namely Uncertainty and Consequence measure tourist risk perception, and five factors, namely Travel information, Safety assurance, Destination reputation, Marketing activities and Precaution measure risk reduction, especially related to food safety risk in international destinations.Practical implicationsThe tourist industry should understand more specifically what tourists want to know so as to devise appropriate communication management strategies at the international destination.Originality/valueThe risk measurement framework provides an insight for the development of an instrument to assess the social and economic impact on tourist perception of international travel risk.

Genetic scatter search algorithm to solve the one-commodity pickup and delivery vehicle routing problem

2017 ◽  
Vol 12 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Jalel Euchi
Keyword(s):  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Scatter Search ◽  
Pickup And Delivery ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Content Type ◽  
New Variant ◽  
Crossover And Mutation

Purpose In this paper, the author introduces a new variant of the pickup and delivery transportation problem, where one commodity is collected from many pickup locations to be delivered to many delivery locations within pre-specified time windows (one–to many–to many). The author denotes to this new variant as the 1-commodity pickup-and-delivery vehicle routing problem with soft time windows (1-PDVRPTW). Design/methodology/approach The author proposes a hybrid genetic algorithm and a scatter search to solve the 1-PDVRPTW. It proposes a new constructive heuristic to generate the initial population solution and a scatter search (SS) after the crossover and mutation operators as a local search. The hybrid genetic scatter search replaces two steps in SS with crossover and mutation, respectively. Findings So, the author proposes a greedy local search algorithm as a metaheuristic to solve the 1-PDVRPTW. Then, the author proposes to hybridize the metaheuristic to solve this variant and to make a good comparison with solutions presented in the literature. Originality/value The author considers that this is the first application in one commodity. The solution methodology based on scatter search method combines a set of diverse and high-quality candidate solutions by considering the weights and constraints of each solution.

scholarly journals Food Safety Risk Information-Seeking Intention of WeChat Users in China

2020 ◽  
Vol 17 (7) ◽  
pp. 2376 ◽  
Author(s):  
Zhaohui Yang ◽  
Krishna P. Paudel ◽  
Xiaowei Wen ◽  
Sangluo Sun ◽  
Yong Wang
Keyword(s):  
Food Safety ◽  
Risk Perception ◽  
Information Seeking ◽  
Educational Background ◽  
Risk Information ◽  
Equation Modeling ◽  
Safety Risk ◽  
Safety Risks ◽  
Food Safety Risk ◽  
The Impact

Consumers’ food safety risk information-seeking behavior plays a vital role in improving their food quality and safety awareness and preventing food safety risks. Based on the Risk Information Seeking and Processing Model (RISP), this paper empirically analyzes the food safety risk information-seeking intention of consumers in WeChat and influencing factors under the impact of food safety incidents. We use data from 774 WeChat users and apply the Structural Equation Modeling (SEM) approach. We also conduct multigroup analysis with demographic characteristics as moderating variables. The results demonstrated that: (1) Risk perception (p ≤ 0.01) has direct significant positive effects on consumers’ intention to seek food safety information. Besides, higher risk perception (p ≤ 0.01) regarding food safety risks will make people feel more anxious and threatened, and then expand the gap between the information they need and the relevant knowledge they actually have (p ≤ 0.1), which will further stimulate them to seek more information (p ≤ 0.05). (2) Informational subjective norms (p ≤ 0.01) can not only directly affect consumers’ information-seeking about food safety, but also indirectly affect consumers’ intention through information insufficiency (p ≤ 0.01). (3) The more consumers trust the relevant channels (p ≤ 0.01), the stronger their intention to search for food safety risk information. Moreover, the multiple-group analysis also shows that the effects of consumers’ gender, age, educational background, and average monthly earnings are different among different groups. Furthermore, implications are put forward for food safety risk communication efforts in China.

scholarly journals A New Hybrid Butterfly Optimization Algorithm for Green Vehicle Routing Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Dana Marsetiya Utama ◽  
Dian Setiya Widodo ◽  
Muhammad Faisal Ibrahim ◽  
Shanty Kusuma Dewi
Keyword(s):  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Vehicle Routing Problem ◽  
Computation Time ◽  
Industrial Sector ◽  
Routing Problem ◽  
Distribution Costs ◽  
Critical Problems ◽  
Distribution Cost ◽  
Fuel Costs

In the industrial sector, transportation plays an essential role in distribution. This activity impacts climate change and global warming. One of the critical problems in distribution is the green vehicle routing problem (G-VRP). This study focuses on G-VRP for a single distribution center. The objective function is to minimize the distribution costs by considering fuel costs, carbon costs, and vehicle use costs. This research aims to develop the hybrid butterfly optimization algorithm (HBOA) to minimize the distribution costs on G-VRP. It was inspired by the butterfly optimization algorithm (BOA), which was by combining the tabu search (TS) algorithm and local search swap and flip strategies. BOA is a new metaheuristic algorithm that has been successfully applied in various engineering fields. Experiments were carried out to test the parameters of the proposed algorithm and vary the speed of vehicles. The proposed algorithm was also compared with several procedures of prior study. The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms. Moreover, the computation time is also included in the analysis.

A hybrid genetic algorithm for multi-depot vehicle routing problem with considering time window repair and pick-up

2018 ◽  
Vol 13 (3) ◽  
pp. 698-717 ◽  
Author(s):  
Masoud Rabbani ◽  
Pooya Pourreza ◽  
Hamed Farrokhi-Asl ◽  
Narjes Nouri
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Time Window ◽  
Hybrid Genetic Algorithm ◽  
Variable Cost ◽  
Routing Problem ◽  
Content Type ◽  
Simple Genetic Algorithm

Purpose This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW). Design/methodology/approach The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms, namely, simple genetic algorithm (GA) and hybrid genetic algorithm (HGA) are used to find the best solution for this problem. A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA. Findings A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA. Originality/value This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW). The defined problem is a practical problem in the supply management and logistic. The repair vehicle services the customers who have goods, while the pickup vehicle visits the customer with nonrepaired goods. All the vehicles belong to an internal fleet of a company and have different capacities and fixed/variable cost. Moreover, vehicles have different limitations in their time of traveling. The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms (simple genetic algorithm and hybrid one) are used to find the best solution for this problem.

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