Multi-level reverse logistics network design under uncertainty

Localising facilities and assigning product flows in a reverse logistics environment is a crucial but difficult strategic management decision, certainly when value decay plays an important part. Despite numerous publications regarding closed-loop supply chain design, very few addressed the impact of lead times and the high level of uncertainty in reverse processes. In this article, a single product reverse logistics network design problem with multiple layers and multiple routings is considered. To this end, a new advanced strategic planning model with integrated queueing relationships is built that explicitly takes into account stochastic delays due to various processes like collection, production and transportation, as well as disturbances due to various sources of variability like uncertain supply, uncertain process times, unknown quality, breakdowns, etc. Their impact is measured by transforming these delays into work-in-process, which affects profit through inventory costs. This innovative modeling approach is difficult to solve because of both combinatorial and nonlinear continuous relationships. The differential evolution algorithm with an enhanced constraint handling method is proposed as an appropriate heuristic to solve this model close to optimality. A number of scenarios for a realistic case illustrate the power of this optimisation tool.     

Modelling of sustainable food grain supply chain distribution system: a bi-objective approach

Growing food demand, environmental degradation, post-harvest losses and the dearth of resources encourage the decision makers from developing nations to integrate the economic and environmental aspects in food supply chain network design. This paper aims to develop a bi-objective decision support model for sustainable food grain supply chain considering an entire network of procurement centres, central, state and district level warehouses, and fair price shops. The model seeks to minimise the cost and carbon dioxide emission simultaneously. The model covers several problem peculiarities such as multi-echelon, multi-period, multi-modal transportation, multiple sourcing and distribution, emission caused due to various motives, heterogeneous capacitated vehicles and limited availability, and capacitated warehouses. Multiple realistic problem instances are solved using the two Pareto based multi-objective algorithms. Sensitivity analysis results imply that the decision makers should establish a sufficient number of warehouses in each producing and consuming states by maintaining the suitable balance between the two objectives. Various policymakers like Food Corporation of India, logistics providers and state government agencies will be benefited from this research study.     

Supply chain optimisation with assembly line balancing

Supply chain management operates at three levels, strategic, tactical and operational. While the strategic approach generally pertains to the optimisation of network resources such as designing networks, location and determination of the number of facilities, etc., tactical decisions deal with the mid-term, including production levels at all plants, assembly policy, inventory levels and lot sizes, and operational decisions are related to how to make the tactical decisions happen in the short term, such as production planning and scheduling. This paper mainly discusses and explores how to realise the optimisation of strategic and tactical decisions together in the supply chain. Thus, a supply chain network (SCN) design problem is considered as a strategic decision and the assembly line balancing problem is handled as a tactical decision. The aim of this study is to optimise and design the SCN, including manufacturers, assemblers and customers, that minimises the transportation costs for determined periods while balancing the assembly lines in assemblers, which minimises the total fixed costs of stations, simultaneously. A nonlinear mixed-integer model is developed to minimise the total costs and the number of assembly stations while minimising the total fixed costs. For illustrative purposes, a numerical example is given, the results and the scenarios that are obtained under various conditions are discussed, and a sensitivity analysis is performed based on performance measures of the system, such as total cost, number of stations, cycle times and distribution amounts.     

A strategic model for exact supply chain network design and its application to a global manufacturer

This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm’s current supply chain network, as well as into the potential of the proposed approach.     

基于灰色聚类评估的配送中心选址模糊多目标优化模型

将多属性决策方法与最优化方法相集成,研究了多配送中心选址优化问题。首先采用灰色聚类决策计算各候选地定性属性的综合评估值。再以选定配送中心的评估值均值最大化、系统成本最小化,以及配送中心容量利用率最大化作为3个优化目标,建立一个考虑需求点模糊需求、供应点与候选配送中心容量限制的三级供应链系统多配送中心选址模型。该模型被描述成了一个多目标的非线性混合整数规划模型。采用机会约束规划对模糊需求进行清晰化处理,并应用目标加权的方法将问题转化为单目标问题。通过算例验证了所提模型的可行性。在实际工作中,可根据决策者权重偏好得出令人满意的结果。     

Integrated decision support framework for distribution network design

In the current business environment of competition shifting from company-to-company to supply chain against supply chain, there is an increasing need for logistics providers (LSP) to gain cost effectiveness with no compromise on service levels. One key initiative that LSP can undertake is to allocate and utilise their storage and transportation assets optimally. The current work is an attempt in that direction and provides a hands-on decision support framework that integrates MCDM, network optimisation, and discrete event simulation to address distribution network design and transport optimisation. The use case of PT Pos Indonesia in the metropolitan area of Greater Surabaya highlights the benefits of combining ICT tools with well-established best practices in supply chain management. Findings of this work highlight that the number of distribution facilities for the case at hand should be reduced from nine to four. Compared to the existing, the identified network configuration unlocks potential cost saving in transportation and warehousing of 18%–22%, reduces CO₂ emissions by nearly 30%, with no deterioration in service level. Managerial implications about transportation policies are highlighted in the conclusive part of this paper.     

Facility location and scale optimisation in closed-loop supply chain

This paper solves a strategic-level decision problem on determining the optimal location of (re)manufacturers and logistics centres with the consideration of facility scales in an integrated closed-loop supply chain network. A two-stage stochastic mixed-integer non-linear programming model is established to minimise the fixed cost and the expected operation costs under uncertain demand and return. We develop an improved tabu search heuristic algorithm to solve the model. We also design a distance-based decision rule to validate the effectiveness of the proposed model. Numerical experiments are conducted to test the performance of the proposed model and the solution method. In addition, sensitivity analysis is provided to investigate the influences of varying inspection locations and recovery rates on the final performance.     

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.     

An approach to integrate production-transportation planning and scheduling in an aluminium supply chain network

This article is based on a real-life problem of a global aluminium supply chain network driven by an aluminium smelter. At each echelon of the aluminium supply chain network, several members are involved which are scattered around the world. Producing aluminium begins with bauxite mining. Next, aluminium oxide is made from bauxite and finally aluminium is produced from aluminium oxide. A novel type of mixed-integer decision-making model, including a time-continuous representation of the planning period, is presented. The model enables coordination of production quantities and times of all supply chain members in order to minimise production and transportation costs of the whole supply chain minus bonus payments for early deliveries which are stipulated between the supply chain network and its customers. Material flows can take place with or without temporary storage of intermediate products at supplying and/or receiving sites. Furthermore, relax-and-fix heuristics are presented. A number of randomly generated scenarios are presented to demonstrate that the heuristics can find nearly optimal solutions along with drastically reduced computation times. The relax-and-fix heuristic enables iterative planning between centralised and decentralised decision makers.     

Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet

This paper investigates the resilience of inventory models using interconnected logistics services in the Physical Internet (PI). With traditional supply chain network design, companies define and optimise their own logistics networks, resulting in current logistics systems being a set of independent heterogeneous logistics networks. The concept of PI aims to integrate independent logistics networks into a global, open, interconnected system. Prior research has shown that new inventory models enabled by and applied to PI could help reduce inventory levels thanks to its high flexibility. Continuing along these lines, this paper examines how inventory models applying PI deal with disruptions at hubs and plants. To attain this, a single product inventory problem with uncertain demands and stochastic supply disruptions is studied. A simulation-based optimisation model is proposed to determine inventory control decisions. The results suggest that the PI inventory model, with greater agility and flexibility, outperforms the current classic inventory models in terms of resilience. Moreover, the difference in performance increases when the product value, penalty costs and disruption frequency increases. This paper indicates a novel approach to build a resilient supply network.     

Optimal collaborative transportation service trading in B2B e-commerce logistics

This paper investigates a less-than-truckload carrier collaboration decision-making problem in the e-commerce logistics network. E-commerce less-than-truckload carrier collaboration problem considers multiple logistics service providers (LSPs) forming a collaborative alliance in an e-commerce logistics network. They share their transportation requests and vehicle capabilities to maximise the total profit of the entire alliance, improve their vehicle utilisation and cope with fluctuations in demand. An e-commerce logistics trading system with collaborative decisions is designed. A collaborative transportation planning model is introduced to maximise the total profit without reducing the individual profit of the carriers with information sharing. A stochastic plant-pollinator algorithm is proposed for the problem and extensive computational experiments are conducted. The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm. Furthermore, the results illustrate that the higher degree of cooperation, the more benefits for carriers. Last but not least, since the increasing gasoline price leads to the decreasing margins for the small- and medium-sized LSPs. The results also show that it is critical for them to join in the alliance to survive in the competition.     

Multi-level supply chain network design with routing

Recently, the multi-level and multi-facility industrial problem in supply chain management (SCM) has been widely investigated. One of the key issues, central to this problem in the current SCM research area is the interdependence among the location of facilities, the allocation of facilities, and the vehicle routing for the supply of raw materials and products. This paper studies the supply chain network design problem, which involves the location of facilities, allocation of facilities, and routing decisions. The proposed problem has some practical applications. For example, it is necessary for third party logistics (3PL) companies to manage the design of the network and to operate vehicle transportation. The purpose of this study is to determine the optimal location, allocation, and routing with minimum cost to the supply chain network. The study proposes two mixed integer programming models, one without routing and one with routing, and a heuristic algorithm based on LP-relaxation in order to solve the model with routing. The results show that a developed heuristic algorithm is able to find a good solution in a reasonable time.     

基于物流能力约束的整车物流计划

基于时间竞争的敏捷供应链环境中,汽车整车物流必须按照客户订单对交货期、交货地点等的要求进行快速响应和准时配送.整车运输能力作为物流要素能力之一,由于其特殊性已成为整车物流的瓶颈,对物流绩效和供应链绩效形成重要影响.从压缩订单响应时间角度出发,在以整车运输能力为约束的条件下,提出了汽车整车物流准时配送计划问题,参照并行多机提前/拖期问题的研究方法,设计了一种制定整车物流配送计划的启发式算法,最后通过算例证明所提算法的可行性.     

An integrated approach to evaluating the production system in closed-loop supply chains

The increasing demands for environmental resource protection and sustainable development have been forcing enterprises to put sustainable supply chain management on their agendas in recent years. At the same time, intense global competition requires organisations to adopt practices that enable them to provide high-quality products and services. In this paper, we consider the problem of comprehensively evaluating the production system in closed-loop supply chains. We first propose an evaluation framework that consists of economic evaluation, product quality evaluation and ecological evaluation modules. Based on mathematical probability theory and the dynamic characteristics of reverse supply chain logistics, we then focus on the evolution dynamics in the quality evaluation dimension, where the concept of product quality, which builds on the reliability and the time-utility value of a product, is proposed. The basic production evaluation model is then extended to incorporate different sustainable procurement strategies, which take into consideration the trade-offs among cost, environment and quality. An outline and corresponding flow chart of corporate procurement strategy optimisation are provided which allow the proposed evaluation model to be implemented in computer-aided decision-making, further providing decision support for production system and supply chain management. Simulation and case studies are presented to promote a better understanding of the model approach and its managerial implications. Results also suggest that quality characteristics of components and sustainable procurement strategies are two important factors that determine the final production performance and should be paid special attention in closed-loop supply chain practice.     

Supply chain modelling and managing,using timed coloured Petri nets: a case study

This paper aims at developing a new methodology for designing and managing a supply chain (SC) and, at the same time, for evaluating the performance of every stakeholder involved in a production chain. The methodology proposed has been applied to a footwear supply chain and is based on coloured Petri nets (CPNs). The supply chain analysed in this paper is a complex production system consisting of a network of manufacturers and service suppliers related to logistics systems that provide transportation and storage. The model developed uses coloured, timed Petri nets to represent a supply chain and it is such that resources are the Petri Net (PN) places, the tokens are jobs, orders and/or products, while the colours represent job attributes. These colours are used to encode different data types and values that are attached to tokens. A “coloured token” represents a specific production order or a certain amount of a particular material supplied. Thus, it can be processed in different ways and it can be easily localised within the CPN model. The use of coloured Petri nets allows companies to create a compact representation of states, actions and events of the modelled system. The particular structure of this network allows the designers the easy realisation of a simulator using an “object-oriented”, dedicated programming, which is a useful tool for developing what-if analyses.     

Strategic capacity planning in supply chain design for a new market opportunity

This paper addresses the problem of supply chain design at the strategic level when production/distribution of a new market opportunity has to be launched in an existing supply chain. The new market opportunity is characterized by a deterministic forecast expected to occur per period. The product (or service) is assumed to be produced (or provided) in a three-stage capacitated supply chain where the first stage concerns suppliers, the second stage producers and the final stage customers. There could be multiple alternatives at each stage which are defined as nodes. Nodes in each stage are connected to the next stage through capacitated transportation systems. Production capacity at the second stage (i.e. producers) are also limited since they may already be involved in other existing activities. The objective is to perform strategic capacity planning in the supply chain in order to meet the demand of the new opportunity at minimal cost. A linear running cost is associated with each node. If the decision is to increase the capacity of a node, then a fixed cost applies, followed by a cost that is proportional to the additional capacity.

The overall problem can be modelled as a large-scale mixed integer linear programming problem. A solution algorithm is developed to overcome difficulties associated with the size of the problem and is tested on empirical data sets. The overall contribution is an analytical tool that can be employed by managers responding to the new market opportunity at the strategic level for supply chain design.     

跨区域物流网络优化的模型与算法的改进研究

针对跨区域物流网络存在的非优问题,综合考虑物流运输成本、过城费、出入库费、装卸费、仓储费以及物流网络流量等决策因素,建立了双目标数学模型:最小化物流总成本和最大化物流网络流量。给出了改进的最小费用最大流算法,并结合有供需需求的网络流算法和典则型网络转化法对模型进行求解。最后,通过MATLAB仿真实验,证实了模型的价值和算法的有效性。     

敏捷供应链管理决策支持系统的研究

首先介绍了敏捷供应链管理技术,然后提出了一种支持敏捷供应链管理的决策支持系统,最后以企业为背景,给出了该决策支持系统的应用。     

基于ANP方法的电子商务逆向物流研究

电子商务的成功发展需要逆向物流的支持。本文建立了电子商务的逆向物流概念模型，介绍了第三方物流的运营职能。利用ANP方法建立了第三方逆向物流的评估模型，并通过超级决策软件(SD)与AHP模型进行了对比计算。ANP模型可以帮助管理者从战略、运营水平上对供应商选择进行更为全面的决策。     

Development of a decision support framework for sustainable freight transport system evaluation using rough numbers

Among various operational decision-making tasks in a transportation system, sustainable performance evaluation has a very promising and direct influence on the community as well as environment. To prevent and reduce the negative impacts of a freight transportation system, a constant monitoring and performance measurement system has of paramount significance in the process of supply chain management. However, studies of complex transport evaluation systems are very scarce in the existing literature. This paper aims to resolve the problem of freight transport system’s performance measurement while developing a comprehensive framework with incorporation of sustainable elements and establishing a rough set-based decision-making approach. The applicability of the proposed framework is investigated to evaluate the performance of seven freight transportation companies in Spain. A decision support tool is designed by integrating rough number-based decision-making trial and evaluation laboratory (DEMATEL) and multi-attributive border approximation area comparison (MABAC) methods for their performance appraisal. Sensitivity analysis and comparison with other popular methods are also performed to validate the efficacy of the proposed approach. It is established that rough number-based methodologies have advantages over fuzzy or interval-based models.