Risk management in perishable food distribution operations

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.,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.,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.,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.

[1]  William A. Watkins,et al.  Aerial Observation of Feeding Behavior in Four Baleen Whales: Eubalaena glacialis, Balaenoptera borealis, Megaptera novaeangliae, and Balaenoptera physalus , 1979 .

[2]  Xuping Wang,et al.  Multi-objective optimization for delivering perishable products with mixed time windows , 2018, Advances in Production Engineering & Management.

[3]  Yu Peng,et al.  Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression , 2013, Microelectron. Reliab..

[4]  Kwok-Leung Tsui,et al.  An ensemble model for predicting the remaining useful performance of lithium-ion batteries , 2013, Microelectron. Reliab..

[5]  Wen Zhong-lin,et al.  Analyses of Mediating Effects: The Development of Methods and Models , 2014 .

[6]  Seyed Mohammad Mirjalili,et al.  A parallel numerical method for solving optimal control problems based on whale optimization algorithm , 2018, Knowl. Based Syst..

[7]  Fredrik Nilsson,et al.  Temperature performance and food shelf-life accuracy in cold food supply chains : Insights from multiple field studies , 2018 .

[8]  Hongwen He,et al.  Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries , 2018, IEEE Transactions on Vehicular Technology.

[9]  F. Kellermanns,et al.  Entrepreneurial Team Composition Characteristics and New Venture Performance: A Meta–Analysis , 2017 .

[10]  Hui-Chieh Li,et al.  Vehicle routing problem with time-windows for perishable food delivery , 2007 .

[11]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[12]  Patrick G. Maggitti,et al.  Top management attention to innovation: The role of search selection and intensity , 2009 .

[13]  David G. Sirmon,et al.  A Model of Strategic Entrepreneurship: The Construct and its Dimensions , 2003 .

[14]  Min Li,et al.  Prognostics of Lithium-Ion Batteries Based on the Verhulst Model, Particle Swarm Optimization and Particle Filter , 2014, IEEE Transactions on Instrumentation and Measurement.

[15]  Taejung Yeo,et al.  A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation , 2015 .

[16]  George B. Dantzig,et al.  The Truck Dispatching Problem , 1959 .

[17]  Padmini Ramachandran,et al.  Genomics of foodborne pathogens for microbial food safety. , 2018, Current opinion in biotechnology.

[18]  J. Edwards,et al.  Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. , 2007, Psychological methods.

[19]  Bor Yann Liaw,et al.  Inline state of health estimation of lithium-ion batteries using state of charge calculation , 2015 .

[20]  Tiziano Granata,et al.  Toxic inorganic pollutants in foods from agricultural producing areas of Southern Italy: Level and risk assessment. , 2018, Ecotoxicology and environmental safety.

[21]  Christine M. Beckman The Influence of Founding Team Company Affiliations on Firm Behavior , 2006 .

[22]  T. Wrona,et al.  Socio-cognitive processes in strategy formation – A conceptual framework , 2013 .

[23]  J. P. Eggers,et al.  Cognition and Renewal: Comparing CEO and Organizational Effects on Incumbent Adaptation to Technical Change , 2009, Organ. Sci..

[24]  A. Hayes Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach , 2013 .

[25]  James H. Moore,et al.  Mentoring Top Leadership Promotes Organizational Innovativeness through Psychological Safety and Is Moderated by Cognitive Adaptability , 2017, Front. Psychol..

[26]  C. M. Gaglio The Role of Mental Simulations and Counterfactual Thinking in the Opportunity Identification Process * , 2004 .

[27]  R. Holley,et al.  Selection of risk factors to be included in the Canadian Food Inspection Agency risk assessment inspection model for food establishments. , 2017, Food microbiology.

[28]  Barbara J. Bird The Operation of Intentions in Time: The Emergence of the New Venture , 1992 .

[29]  Gene Rowe,et al.  A working procedure for identifying emerging food safety issues at an early stage: Implications for European and international risk management practices , 2009 .

[30]  Vitor Nazário Coelho,et al.  An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints , 2016, Eur. J. Oper. Res..

[31]  Keming Zhang,et al.  A new risk assessment model for agricultural products cold chain logistics , 2017, Ind. Manag. Data Syst..

[32]  M. West Reflexivity and work group effectiveness:a conceptual integration , 1996 .

[33]  Vili Podgorelec,et al.  A survey of genetic algorithms for solving multi depot vehicle routing problem , 2015, Appl. Soft Comput..

[34]  Ali H. Diabat,et al.  Supply chain risk management and its mitigation in a food industry , 2012 .

[35]  Daniel P. Forbes The Effects of Strategic Decision Making on Entrepreneurial Self–Efficacy , 2005 .

[36]  Jack A. Goncalo,et al.  Can Confidence Come Too Soon? Collective Efficacy, Conflict and Group Performance over Time. , 2010 .

[37]  Kai Goebel,et al.  Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework , 2009 .

[38]  Allen C. Amason,et al.  Newness and novelty: Relating top management team composition to new venture performance , 2006 .

[39]  Mark Simon,et al.  Cognitive biases, risk perception, and venture formation: How individuals decide to start companies , 2000 .

[40]  R. Baron The cognitive perspective: a valuable tool for answering entrepreneurship's basic “why” questions , 2004 .

[41]  Dong Wang,et al.  Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter , 2016, IEEE Transactions on Instrumentation and Measurement.

[42]  Yongquan Zhou,et al.  A Hybrid Bat Algorithm with Path Relinking for the Capacitated Vehicle Routing Problem , 2013 .

[43]  Feng Chu,et al.  Coordinated Production Inventory Routing Planning for Perishable Food , 2017 .

[44]  D. Shepherd,et al.  Cognitive Adaptability and an Entrepreneurial Task: The Role of Metacognitive Ability and Feedback , 2012 .

[45]  David R. Rink,et al.  Risk preferences and the marketing of financial services: Segmentation by birth order , 2013 .

[46]  Kristopher J Preacher,et al.  SPSS and SAS procedures for estimating indirect effects in simple mediation models , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[47]  Carlo Meloni,et al.  A reliable decision support system for fresh food supply chain management , 2018, Int. J. Prod. Res..

[48]  Amitangshu Pal,et al.  IoT-Based Sensing and Communications Infrastructure for the Fresh Food Supply Chain , 2018, Computer.

[49]  R. E. Taylor,et al.  Optimal Redundancy for Reliability in Series Systems , 1969, Oper. Res..

[50]  Viliam Makis,et al.  Optimal swarm decomposition with whale optimization algorithm for weak feature extraction from multicomponent modulation signal , 2019, Mechanical Systems and Signal Processing.

[51]  Janet R. McColl-Kennedy,et al.  Competing through service innovation: The role of bricolage and entrepreneurship in project-oriented firms , 2013 .

[52]  Stefano Longo,et al.  A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur , 2016 .

[53]  Wei Liang,et al.  Remaining useful life prediction of lithium-ion battery with unscented particle filter technique , 2013, Microelectron. Reliab..

[54]  S. Sarasvathy Causation and Effectuation: Toward a Theoretical Shift from Economic Inevitability to Entrepreneurial Contingency , 2001 .

[55]  John G. Lynch,et al.  Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis , 2010 .

[56]  Kanchana Sethanan,et al.  A differential evolution algorithm for the capacitated VRP with flexibility of mixing pickup and delivery services and the maximum duration of a route in poultry industry , 2017, J. Intell. Manuf..

[57]  Young Dae Ko,et al.  A vehicle routing problem of both refrigerated- and general-type vehicles for perishable food products delivery , 2016 .

[58]  V. García-Morales,et al.  Entrepreneurial decision-making, external social networks and strategic flexibility: The role of CEOs' cognition , 2016 .

[59]  Guangzhong Dong,et al.  Remaining Useful Life Prediction and State of Health Diagnosis for Lithium-Ion Batteries Using Particle Filter and Support Vector Regression , 2018, IEEE Transactions on Industrial Electronics.

[60]  Christoph Lechner,et al.  To Agree or Not to Agree? A Meta-Analytical Review of Strategic Consensus and Organizational Performance , 2011 .

[61]  L. R. Anderson,et al.  Effects of task and group size upon group productivity and member satisfaction. , 1971 .

[62]  P. Shrout,et al.  Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.

[63]  Yan Li,et al.  A green vehicle routing model based on modified particle swarm optimization for cold chain logistics , 2019, Ind. Manag. Data Syst..

[64]  Yahya Saleh,et al.  Vehicle-Routing Optimization for Municipal Solid Waste Collection Using Genetic Algorithm: The Case of Southern Nablus City , 2017 .

[65]  Chen Chao,et al.  Optimization of two-stage location–routing–inventory problem with time-windows in food distribution network , 2019 .

[66]  Prakash Kumar Hota,et al.  Modified whale optimization algorithm for fractional‐order multi‐input SSSC‐based controller design , 2018, Optimal Control Applications and Methods.

[67]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[68]  Michael Osterman,et al.  Prognostics of lithium-ion batteries based on DempsterShafer theory and the Bayesian Monte Carlo me , 2011 .

[69]  Tomoki Sekiguchi,et al.  The role of empathy in entrepreneurial opportunity recognition: An experimental study in Japan and Pakistan , 2018, Journal of Business Venturing Insights.

[70]  A. Bandura Self-Efficacy: The Exercise of Control , 1997, Journal of Cognitive Psychotherapy.

[71]  Saikat Chakraborty,et al.  A Heuristic Initialized Stochastic Memetic Algorithm for MDPVRP With Interdependent Depot Operations , 2017, IEEE Transactions on Cybernetics.

[72]  Chao-chuan Chen,et al.  Does entrepreneurial self-efficacy distinguish entrepreneurs from managers? , 1998 .

[73]  Dale F. Cooper ... et al. Project risk management guidelines , 2013 .

[74]  Alan Millner,et al.  Modeling Lithium Ion battery degradation in electric vehicles , 2010, 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply.

[75]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[76]  Cristian Piras,et al.  Proteomics in food: Quality, safety, microbes, and allergens , 2016, Proteomics.

[77]  Majdi M. Mafarja,et al.  Hybrid Whale Optimization Algorithm with simulated annealing for feature selection , 2017, Neurocomputing.

[78]  Burak Eksioglu,et al.  The vehicle routing problem: A taxonomic review , 2009, Comput. Ind. Eng..

[79]  Renzo Akkerman,et al.  Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges , 2010, OR Spectr..

[80]  Eleni Likotrafiti,et al.  Food processing as a risk factor for antimicrobial resistance spread along the food chain , 2019, Current Opinion in Food Science.

[81]  Feng Chu,et al.  Recent advances and opportunities in sustainable food supply chain: a model-oriented review , 2018, Int. J. Prod. Res..

[82]  Nancy G. Boyd,et al.  The Influence of Self-Efficacy on the Development of Entrepreneurial Intentions and Actions , 1994 .

[83]  Lidija Zadnik Stirn,et al.  A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food , 2008 .

[84]  S. Khapova,et al.  Entrepreneurial Team Cognition: A Review , 2015 .

[85]  S. Kiesler,et al.  Managerial Response to Changing Environments: Perspectives on Problem Sensing from Social Cognition. , 1982 .

[86]  Bo Li,et al.  The Impact of Manufacturer’s Direct Sales and Cost Information Asymmetry in a Dual-Channel Supply Chain with a Risk-Averse Retailer , 2017, Int. J. Electron. Commer..

[87]  Xiulan Sun,et al.  Recent progress on cell-based biosensors for analysis of food safety and quality control. , 2019, Biosensors & bioelectronics.

[88]  Nubia Velasco,et al.  A hybrid metaheuristic algorithm for the vehicle routing problem with stochastic demands , 2018, Comput. Oper. Res..

[89]  Taejin Kim,et al.  A degenerated equivalent circuit model and hybrid prediction for state-of-health (SOH) of PEM fuel cell , 2014, 2014 International Conference on Prognostics and Health Management.

[90]  M H Zwietering,et al.  Application of predictive microbiology to estimate the number of Bacillus cereus in pasteurised milk at the point of consumption. , 1996, International journal of food microbiology.

[91]  Chun-Ho Wu,et al.  An Internet of Things (IoT)-based risk monitoring system for managing cold supply chain risks , 2018, Ind. Manag. Data Syst..

[92]  J. Flavell Metacognition and Cognitive Monitoring: A New Area of Cognitive-Developmental Inquiry. , 1979 .

[93]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[94]  Umesh Lilhore,et al.  A Survey: Whale Optimization Algorithm for Route Optimization Problems , 2017 .

[95]  Zhou Xue Remaining useful life prediction of the lithium-ion battery using particle filtering , 2013 .

[96]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[97]  F DEEDS,et al.  Time-temperature tolerance in frozen foods. , 1959, Journal of the American Dietetic Association.

[98]  Andrew F. Hayes,et al.  Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations , 2009, Behavior research methods.

[99]  Hasan Seyyedhasani,et al.  Routing algorithm selection for field coverage planning based on field shape and fleet size , 2019, Comput. Electron. Agric..

[100]  Michael A. West,et al.  Reflexivity, Effectiveness, and Mental Health in BBC-TV Production Teams , 1998 .

[101]  Stuart Corbridge,et al.  Challenges for development , 2000 .

[102]  Yuchun Xu,et al.  Development of a fuel consumption optimization model for the capacitated vehicle routing problem , 2012, Comput. Oper. Res..

[103]  Qiang Miao,et al.  Prognostics of lithium-ion batteries based on relevance vectors and a conditional three-parameter capacity degradation model , 2013 .

[104]  Kai Goebel,et al.  Comparison of prognostic algorithms for estimating remaining useful life of batteries , 2009 .

[105]  Michael N. Young,et al.  Corporate governance in transition economies: a case study of two Chinese airlines , 2001 .

[106]  Jeffery S. McMullen,et al.  An Opportunity for Me? The Role of Resources in Opportunity Evaluation Decisions , 2009 .

[107]  Jianqiu Li,et al.  A review on the key issues for lithium-ion battery management in electric vehicles , 2013 .

[108]  Göran Lindbergh,et al.  A support vector machine-based state-of-health estimation method for lithium-ion batteries under electric vehicle operation , 2014 .

[109]  Zetian Fu,et al.  Improved preservation process for table grapes cleaner production in cold chain , 2019, Journal of Cleaner Production.