European J. of Industrial Engineering (18 papers in press)
The impact of online sales in centralized and decentralized dual-channel supply chains
by Subrata Saha
Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
Opportunistic maintenance on the automatic switching mechanism of a two-unit multi-state system
by Vasilis Koutras, Sonia Malefaki, Agapios N. Platis
Abstract: A two-unit multi-state deteriorating system consisting of one operating and one unit in standby mode, under preventive maintenance and imperfect switch is considered. System control is switched to the standby unit upon operating unit failure or maintenance, either automatically, by an automatic switching mechanism (ASM), or manually. To avoid ASM failures, triggering opportunistic maintenance (OM) on the automatic switching mechanism is proposed upon unit maintenance. The main objective is to evaluate the effect of ASM opportunistic maintenance on systems dependability and performance. The asymptotic availability and the total expected operational cost of the system with and without automatic switching mechanism OM for various unit maintenance policies are compared, through a numerical example. The results are quite encouraging since the proposed model with OM provides higher availability and significantly reduced operational cost regardless the adopted maintenance policy.
Keywords: opportunistic maintenance; multi-state deteriorating system; imperfect switch; redundancy; asymptotic availability; total expected operational cost.
Simulation-based Assessment of IoT-Functionality in Perishable Dairy Products
by Raid Al-Aomar, Abdallah Dweekat
Abstract: This paper presents a framework for simulation-based assessment of next-generation IoT-enabled supply chains with a focus on perishable dairy products. The framework integrates real-time data capturing with supply chain modelling and dynamic performance management. The concept of complex event processing (CEP) is utilised to implement IoT functionality. The aim is to reduce waste and losses caused by outdated items, shortages, and inventory discrepancies. The approach is illustrated through a simulation of dairy products perishability in a three-echelon supply chain. Simulation experiments were used to assess the impact of enabling two IoT functionalities; adjusting quantities distributed to retailers based on shelf-life and moving dairy products amongst retailers based on the proximity of their expiration. Simulation results have shown substantial improvement in both economic and operational KPIs of dairy products perishability. Results were also used to trade-off the percentage of expired milk and the inventory fill-rate.
Keywords: simulation modelling; supply chain performance management; internet-of-things; product perishability; dairy products.
Towards a New Knowledge-based Framework for Integrated Quality Control Planning
by Fadwa Oukhay, Ahmed Badreddine, Taieb Ben Romdhane
Abstract: This paper presents a new knowledge-based framework for integrated quality control planning. The proposed approach is based on the concepts of advanced product quality planning (APQP) and employs the quality function deployment (QFD) for the selection of the features to be controlled. Accordingly, APQP/QFD related issues are addressed, namely the uncertainty in the customers voice deployment, the complexity of causal interrelationships analysis, and the difficulties of knowledge exploitation. A new QFD model based on fuzzy cognitive map (FCM) and Choquet integral is thus proposed. FCM development allows the capture and modelling of product/process causality. The FCM simulation assesses the impacts of the product, parts, and process characteristics on the customer requirements (CRs). Choquet integral is used for the aggregation of these impacts in order to deal with the interactions between CRs. The effectiveness of this approach is evaluated by the results of an experimental case study.
Keywords: product and process quality control planning; quality function deployment; QFD; fuzzy cognitive map; FCM; Choquet integral.
Hybrid of Metaheuristic Approaches and Fuzzy Logic for the Integrated Flowshop Scheduling with Predictive Maintenance Problem under Uncertainties
by Asma Ladj, Benbouzid-Sitayeb Fatima, Christophe Varnier
Abstract: Maintenance interventions must be properly integrated in the production scheduling in order to prevent failure risks. In this context, we investigate the permutation flowshop scheduling problem subjected to predictive maintenance based on prognostics and health management (PHM). To solve this problem, two integrated metaheuristics are proposed with the objective of minimising the makespan: a carefully tailored genetic algorithm (GA), and a variable neighbourhood search (VNS) incorporating well designed local search procedures. Moreover, we hybridise the two metaheuristics where the GA best solution is introduced as initial solution of VNS. The proposed metaheuristics use the fuzzy logic framework to deal with the uncertainties. To gain insight in the performance of the proposed methods, several computational experiments were conducted against Taillards benchmarks endowed with the prognostics and predictive maintenance data. The results show a clear superiority of the proposed algorithms, especially for the genetic algorithm, regarding both solution quality and computational times. [Received 10 June 2019; Accepted 27 October 2020]
Keywords: permutation flowshop scheduling problem; PFSP; predictive maintenance; post prognostic decision; PPD; variable neighbourhood search; VNS; genetic algorithm; fuzzy logic.
Supplier Selection and Order Allocation in the Presence of Suppliers with Exact Annual Capacity
by Ali Ekici, Okan Örsan Özener, Milad Elyasi
Abstract: In this paper, we focus on the supplier selection and order quantity allocation for a single retailer. The retailer orders a product from multiple suppliers with capacities, adds value to the product and fulfils the demand while meeting the minimum quality level. There is a distinct difference between our work and the prior works in the literature in that we assume the (annual) capacities of the suppliers to be exact annual capacities, i.e., the total order amount in a given calendar/fiscal year from a supplier must be less than or equal to its capacity. First, we discuss the implications of this exact annual capacity assumption on the ordering policy of the retailer. Next, to determine an ordering policy, we propose a heuristic algorithm using a novel idea of iteratively updating the annual ordering cost estimates. We demonstrate the efficacy of the proposed algorithm on randomly generated instances. [Submitted: 18 March 2019; Accepted: 22 November 2020]
Keywords: supplier selection; long-run average annual capacity; perfect rate; capacitated suppliers; exact annual capacity.
An Integrated Inventory and Distribution Problem for Alternative Fuel: a Matheuristic Approach
by Sang Jin Kweon, Seong Wook Hwang, Seokgi Lee
Abstract: Due to the limited driving range of alternative fuel (AF) vehicles and their immature refueling infrastructure, a successful transition to the era of AF vehicles necessitates ensuring stable supply and management of AF in the refueling network. This paper proposes a new mathematical framework to solve an AF inventory and distribution problem in which an AF provider manages and operates the AF refueling network to meet all AF demand in a given time horizon. As a solution method, we present a mixed-integer programming (MIP) model that minimises the sum of AF service, inventory holding, and distribution costs. Furthermore, a matheuristic algorithm hybridising an MIP model and an adaptive large neighbourhood search algorithm is designed to solve practical problems of real transportation networks. The proposed matheuristic algorithm is validated with an application to small-size instances and is applied to six states in the USA with real traffic flows. [Received 18 September 2019; Revised 29 September 2020; Accepted 23 October 2020]
Keywords: alternative fuel vehicle; refueling service; inventory routing problem; mixed-integer programming; MIP; adaptive large neighbourhood search; ALNS.
Scheduling the Capacitated Identical Parallel Machines Problem: A New Formulation with Sequence-Dependent Setup Costs and Different Due Dates
by Ahmad Sobhani, Majid Esmaelian, Hadi Shahmoradi, Milad Mohammadi
Abstract: This paper schedules capacitated parallel machines of a real production system by considering different quantities of production and processing times required to complete customer orders. A new mixed linear programming model is developed according to the concept of constrained vehicle routing problems to have a complete schedule for machines by determining the sequence of both jobs and idle times for each machine. The optimisation model minimises the total cost of the production system, including tardiness, earliness and sequence-dependent setup costs. A Constraint Programming (CP) model and a meta-heuristic hybrid algorithm are also developed to compare their results with the mixed linear programming model. The numerical findings show that the total cost estimated by the mixed integer programming model is 10
Keywords: capacitated identical parallel machines; constrained vehicle routing problem; mixed integer linear programming; constraint programming; meta-heuristic algorithm.
The effect of transfer lot size on manufacturing lead time: a stochastic analysis
by Clarissa Barco, Moacir Godinho Filho
Abstract: This paper aims to explore, in a quantitative way, the effect of production and transfer lot size on the manufacturing lead time in an environment subject to uncertainties. In order to achieve this objective, a Monte Carlo simulation model is proposed, and several scenarios are analysed, considering six shop-floor variables. The results demonstrate that transfer lot size has little effect on lead time when operating with a manufacturing lot size away from optimal lot size. In order to obtain an excellent performance concerning lead time, it is first necessary to reduce the manufacturing lot size before making efforts to reduce transfer lot size. The results also show that adopting an optimal manufacturing lot size allows the production system to be more stable, allowing shorter lead times. The effect of a supplier manufacturing lot size smaller than optimal lot size on retailer safety stock is disastrous. This result is worse when the desired cycle service level and the demand coefficient of variability are high. [Received: 9 November 2019; Accepted: 28 November 2020]
Keywords: manufacturing lead time; transfer lot; manufacturing lot; safety stocks; uncertainty; Monte Carlo simulation.
An improved Backtracking search algorithm for the flexible job shop rescheduling problem with new job insertions
by Gnanavelbabu Annamalai, Rylan Caldeira
Abstract: In real-world environments, production schedules are subject to several disruptions. Hence it is essential to account for these disruptions while constructing the production schedules. This work considers the flexible job-shop rescheduling problem (FJSRP) considering new job insertions. An improved discrete backtracking search algorithm and a slack-based inserting rescheduling strategy are proposed to address this problem considering makespan as objective. A set of heuristics is used to generate a diverse initial population. An order-preserving crossover and a mutation operator is developed to balance the exploitation and exploration. A transfer criterion is utilised to employ the information of the past population. The algorithms exploitation capability is enhanced by employing a local search technique. Extensive computational work is performed on well-known benchmark instances. Computational results demonstrate the superiority of the proposed approach as well as the rescheduling strategy.
Keywords: backtracking search algorithm; flexible job shop rescheduling problem; job insertion; local search technique; rescheduling strategy.
Solving a Stochastic Programming with Recourse Model for the Stochastic Electric Capacitated Vehicle Routing Problem using a Hybrid Genetic Algorithm
by Elhassania Messaoud
Abstract: This study considers stochastic travel times in an electric capacited vehicle routing problem (ECVRP), where the used electric vehicles may need to visit charging stations due to their battery capacities. The main goal of the present paper is to solve a two-stage stochastic programming with recourse (SPR) model for this problem using a hybrid genetic algorithm (HGA) and a Monte Carlo sampling (MCS) procedure. To show the effectiveness of the proposed approach, the computational experiments are applied to 29 instances with up to 100 customers derived from benchmarks presented in the literature. Firstly the numerical results are compared to those found by CPLEX solver for the deterministic model, thereafter a very large number of scenarios is taken into consideration to evaluate this approach in the stochastic environment using a known probability distribution.
Keywords: transport problem; electric vehicles; capacity constraint; stochastic travel times; stochastic programming with recourse model; genetic algorithm.
An extension of Systematic Layout Planning by using fuzzy AHP and fuzzy VIKOR methods: A case study
by Adolfo Rene Santa Cruz Rodriguez, Paulo Vitor De Oliveira
Abstract: Facility layout problem (FLP) is a complex task generally affected by multiple conflicting criteria, uncertainties, ambiguity, non-commensurable, inaccurate or incomplete information. This paper address these characteristics by extending the systematic layout planning (SLP) procedure with integration of SLP, fuzzy analytic hierarchy process (FAHP) and fuzzy VIKOR (FVIKOR) methods into a fuzzy multi criteria group decision making analysis. The problem is addressed in three stages: 1) feasible layout alternatives are generated using the SLP procedure; 2) the weights of the criteria are determined using FAHP; 3) FVIKOR is used to select the most appropriate layout using qualitative and quantitative criteria. We take advantage of the main characteristic of the FVIKOR method to provide a compromising solution including non-commensurable and conflicting criteria. A real-world case study on improving the layout of a production line in a suction valve industry is conducted to illustrate these approach. The results showed the applicability and effectiveness of the SLP extension to handle FLP under fuzzy environments. [Submitted 6 January 2020; Accepted 12 January 2021]
Keywords: facility layout problem; FLP; fuzzy AHP; FAHP; fuzzy VIKOR; FVIKOR; systematic layout planning; SLP.
OPTIMAL CONTROL OF A MULTI-SUPPLIER AND MULTI-BUYER SUPPLY CHAIN SYSTEM WITH JIT DELIVERY
by Pablo Biswas, Bhaba R. Sarker
Abstract: : A just-in-time centred production-facility supply chain consists of raw material suppliers, manufacturer, and retailers. This paper considers the concept where the production of finished goods follows continuous production cycles. In this scenario, it is assumed that the inventory build-up during production cycles of the concurrent cycle overlap the pure demand consumption cycle to reduce the idle time suggested by previous researchers. Considering this situation, a supply chain inventory models for raw materials, and finished goods supply are developed for multiple suppliers and multiple buyers. In addition, this paper considered that different suppliers deliver the raw materials in instantaneous replenishments supply, and the finished goods are delivered to multiple buyers in a fixed amount after a fixed interval of time (known as just-in-time delivery) according to buyers demand. The problem in this research is formulated as an integer nonlinear programming problem and heuristic solutions are developed to solve it with the help of integer approximations and divide-and-conquer technique. The solution methodologies suggested lead to estimates of optimum production quantity and minimum total system cost. The solutions are verified through numerical examples and illustrated the effectiveness of the method with sensitivity analyses. [Submitted: 27 September 2019; Accepted: 03 January2020]
Keywords: supply chain system; just-in-time delivery; multi-buyer; multi-supplier and single manufacturer.
Inventory risk pooling strategy for the food distribution network in Korea
by Seung-Chul Oh, Hokey Min, Young-Hyo Ahn
Abstract: Today's business environments are characterised by the high degree of volatility and risk due to fast changing customer behaviours and increasingly diversified product lines. Since the volatility and risk are often triggered by demand variability, growing efforts are made to control demand variability. One of such efforts includes inventory risk pooling which aims to reduce inventory variability by aggregating customer demand across products, time, and location. The success of inventory risk pooling, however, hinges on its ability to consolidate inventory at the central location of a supply chain network. To help supply chain professionals formulate a wise inventory risk pooling strategy, this paper redesigns a warehouse network in such a way that it increases inventory turnover, reduces the risk of inventory obsolescence/shortage/surplus, allocates inventory to field warehouses closer to highly concentrated customer bases, and centralises inventory stocking locations for the aggregated demand. To solve this complex distribution network redesign problem, we propose a simulation model and test its validity by applying it to an actual distribution problem encountering the consumer packaged goods manufacturer in Korea, which produces and distributes food products. [Received: 14 August 2017; Accepted: 30 June 2020]
Keywords: inventory pooling; distribution network design; processsed food distribution; a cold supply chain; simulation; case study; Korea.
A new DEA model for ranking association rules considering the risk, resilience and decongestion factors
by Majid Khedmati, Ardavan Babaei
Abstract: In this paper, a novel data envelopment analysis (DEA) model is proposed for ranking the association rules. In this regard, a mixed-integer linear programming (MILP) model is proposed to determine the most efficient association rules where, an N-person bargaining game is used to create an interactive competition between the existing N-weights to get a better ranking. In addition, the proposed model is fuzzified by setting the ambiguous threshold of the indicators' weight in each rule to improve the overall ranking of the rules. Finally, the risk, resilience and decongestion factors are also considered to increase the responsiveness of the models to different real-world conditions. The proposed model is validated by some random problems and an illustrative example of market basket analysis where, the proposed model shows better results than the competing models in the literature. In addition, the applicability of the proposed model is illustrated using a real case-study. [Received: 2 February 2020; Accepted: 5 July 2020]
Keywords: ranking association rules; data envelopment analysis; DEA; fuzzy logic; mixed-integer linear programming; MILP; game theory; risk; resilience.
Robustness, resilience: typology of definitions through a multidisciplinary structured analysis of the literature
by Antoine Clement, Liên Wioland, Virginie Govaere, Didier Gourc, Julien Cegarra, François Marmier, Daouda Kamissoko
Abstract: The concepts of robustness and resilience are used with increasing frequency from different sectors. The literature review reveals several meanings for each of these terms due probably to specific use in each of the sectors and a progressive adjustment of the definitions across time. The aims of this article are to identify these definitions and the main similarities and differences between the concepts of resilience and robustness and to propose a classification in order to avoid confusions, bad meaning and to provide a better understanding of the subtleties under these concepts. Based on a structured analysis of the literature published in journals of different sectors, this paper conceptualises and comprehensively presents a systematic review of the recent literature on the definitions of robustness and resilience. Decision makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which definitions can be used. [Received: 26 February 2020; Accepted: 20 July 2020]
Keywords: structured literature review; definitions; resilience; robustness.
Fuzzy aggregate production planning with flexible requirement profile for plan stability in uncertain environments
by Setareh Torabzadeh, Ertunga C. Ozelkan
Abstract: In this paper, a production plan stability control technique called flexible requirement profile (FRP) is combined with fuzzy aggregate production planning (APP) to not only handle the planning system uncertainties, but also to maintain the stability of the production plans when re-planning. More specifically, this paper proposes two new fuzzy aggregate planning models namely the fuzzy Max-Min FRP-APP and fuzzy ranking FRP-APP. The proposed models are tested on five industry-based cases and the results are compared to the crisp FRP-APP, and traditional fuzzy APP models with no stability considerations. The results indicate that the proposed fuzzy FRP-APP model is able to yield comparable stability and cost performance as the crisp FRP-APP model but produce noticeably more stable production plans compared to the non-FRP-APP models without significantly sacrificing the cost. [Received: 30 June 2019; Accepted: 12 August 2020]
Keywords: stability; aggregate production planning; APP; flexible requirements profile; FRP; fuzzy programming.
Buyback and risk-sharing contracts to mitigate the supply and demand disruption risks
by Rita Maria Difrancesco, Purushottam Meena, Rajendra Tibrewala
Abstract: Events like the recent COVID-19 create major disruptions in global supply chains. Companies find it difficult to manage business continuity under supply uncertainties and disruptions. This paper investigates the buyer's optimal ordering decisions under stochastic demand, supply uncertainty, and disruption risks. We consider a two-echelon supply chain consisting of a single buyer and two suppliers. The main supplier is cheaper, but exposed to the risks of random yield and disruption. The backup supplier is perfectly reliable, but relatively expensive. An analytical model is developed using contract-based mechanisms considering the risks of demand uncertainty, supply disruption, and random yield. Two typologies of contracts with suppliers are considered, namely, risks sharing contract and buyback contract. A numerical study is performed to explore the effects of different parameters on the supply chain members' profits, providing guidelines for managers regarding how the supply chain's risks and demand uncertainty influence the ordering decisions. [Received: 5 November 2019; Accepted: 22 August 2020]
Keywords: supply disruption; COVID-19; random yield; demand uncertainty; buyback contract; ordering policy; risk-sharing contracts.