Multi-item distribution network design problems under volume discount on transportation cost

This study considers the distribution network design problems of multi-echelon, multi-item supply chains under volume (weight) discounts on transportation costs. Minimising the total network cost requires determining the following: (1) the service area of distribution centres (DCs); (2) the assignment of retail stores to DCs; and (3) the inventory volume at DCs. This study compares various replenishment policies and discusses the effects of such policies on distribution network design. In general, the results show that single-cluster replenishment is superior to joint cluster replenishment. However, joint cluster replenishment may be superior to single-cluster replenishment under volume (weight) discounts on transportation costs. The results additionally show that single-item replenishment is inferior to multi-item replenishment under volume (weight) discounts on transportation costs. All the problems are formulated as piecewise non-linear programming models with multiple variables. Algorithms are proposed for solving these piecewise non-linear programming problems. Several numerical studies demonstrate the solution procedures and the effects of changing parameters on decision-making.     

Performance evaluation framework for sustainable freight transportation systems

Sustainability in freight transportation demands for a balance among economic, environmental, and social aspects in shipping commodities throughout a supply chain. The performance evaluation of sustainable freight transportation (SFT) systems is of prime importance as it facilitates perpetual and objective assessment for advancements towards sustainability targets. In this study, we propose a comprehensive framework to assess the sustainability performance of freight transportation systems. We pinpoint critical success factors (CSFs) affecting the performance of SFT by carrying out an extensive literature review and conducting a Delphi study to seek experts’ opinions from industry as well as academia. Further, a comprehensive hierarchical framework is developed to establish inter-relationships among these CSFs followed by prioritisation of these CSFs. The application of the proposed framework is illustrated through a case example. This framework would also serve as a reference for decision-makers in selecting the most sustainable freight transportation system.     

A globally convergent algorithm for transportation continuous network design problem

The continuous network design problem (CNDP) is characterized by a bilevel programming model, in which the upper level problem is generally to minimize the total system cost under limited expenditure, while at the lower level the network users make choices with regard to route conditions following the user equilibrium principle. In this paper, the bilevel programming model for CNDP is transformed into a single level convex programming problem by virtue of an optimal-value function tool and the relationship between System Optimum (SO) and User Equilibrium (UE). By exploring the inherent nature of the CNDP, the optimal-value function for the lower level user equilibrium problem is proved to be continuously differentiable and its derivative in link capacity enhancement can be obtained efficiently by implementing user equilibrium assignment subroutine. However, the reaction (or response) function between the upper and lower level problem is implicit and its gradient is difficult to obtain. Although, here we approximately express the gradient with the difference concept at each iteration, based on the method of successive averages (MSA), we propose a globally convergent algorithm to solve the single level convex programming problem. Comparing with widely used heuristic algorithms, such as sensitivity analysis based (SAB) method, the proposed algorithm needs not strong hypothesis conditions and complex computation for the inverse matrix. Finally, a numerical example is presented to compare the proposed method with some existing algorithms.     

Harmony search optimization algorithm for a novel transportation problem in a consolidation network

This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.     

A two-stage stochastic mixed-integer programming approach to physical distribution network design

In many industries, distribution activities are realised in a dynamic environment including uncertainties. Besides, adding transportation mode alternatives, inventory-stocking opportunities in wholesalers, unmet demand permission in distribution centres, etc. increase the difficulty of problem modelling and solving for large-scale networks. In this study, the problem of physical distribution network (DN) design with profit maximisation objective function is modelled to tackle with realistic cases. Two-stage stochastic mixed-integer programming method is used to handle the uncertainties and to consider the probable scenarios. The first-stage decisions of the proposed model are related with the selection of facility location in strategic level, and the second-stage decisions are related with the transported and stocked products or unmet demand quantities. Here, a multi-product, two-echelon, multi-mode and multi-period network model is applied to a hypothetically created problem, inspired from the physical DN of home appliance companies. Various scenarios including stochastic demand and price data with different realisation probabilities are used in the model. The motivation of this study is the lack of reaching a global optimum result using transportation modes as stochastic parameters, considering their own lead times and capacities. Finally, various results are obtained for different cases and analysed in detail.     

Integrated product design,shelf-space allocation and transportation decisions in green supply chains

In this paper, we examine a supply chain consisting of a manufacturer and retailer where the manufacturer undertakes greening efforts in terms of pack-size reduction and transportation cost reduction. The retailer decides on shelf-space allocation for the product. Both the players benefit from the greening efforts of the manufacturer. In such a setting, we examine strategic decisions of the players and compare and contrast the performance of the decentralised supply chain with the centralised supply chain. We also examine the effect of collaborative mechanisms by modelling two contracts in which the retailer offers a transportation cost reduction effort based contract and a two-part tariff contract. We find that the decentralised supply chain leads to lower greening efforts and shelf-space allocation decisions. We also find that the contracts improve pack-size reduction effort, transportation cost reduction effort and shelf-space allocation, while also improving the profitability of individual players. The findings demonstrate a scope for supply chain collaboration between manufacturer–retailer pairs in this setting. The paper uniquely combines three critical elements in supply chains, namely, product design, transportation and retailing decisions, and aims to provide insights into the decision making of players considering environmental waste and pollution. The paper also reflects consumer behavior and trade-offs that the supply chain players face.     

Hub relay network design for daily driver routes

Hub-based relay networks for long haul trucking offer an opportunity to improve the work–life balance of drivers while simultaneously supporting faster delivery through near-continuous flow of containers from source to destination. In this paper, we develop a model for deciding hub location and sizing along with the routing of loads. Costs of hub construction and operation, transportation and penalties for multi-day driver trips are included. Both deterministic and two-stage stochastic programming models have been formulated in this paper. The goal is to determine the optimal hub and route decisions so that overall cost is minimised. A case study on the highway network for the Western United States demonstrates the computational tractability of the approach along with the importance of considering demand uncertainty.     

Production-distribution network design of a global supply chain alliance from the key player's perspective

A key player in a supply chain (SC) is the member who overlooks and leads others. Although it can compel its autonomous members to follow the planning of a production-distribution network (PDN), the key player has to create an environment in which the partnership with suppliers can also grow accordingly. Without the effective partnership, the efforts increase in managing and integrating the information and material flow across the PDN. Hence, while designing the PDN, the key player has to consider the constraint of the autonomous suppliers also seeking maximum profits as their business goals. In addition, to alleviate the impact of uncertainty on the PDN of a global SC, the strategy of alternative design features is incorporated in the PDN design model. In this paper, the problem for key player's PDN design with alternative design features (KPDN/ADF) is formulated as a bi-level programming problem. An extended genetic algorithm is proposed to solve the KPDN/ADF problem. The experiment results showed that the proposed algorithm can solve the problem satisfactorily. Furthermore, incorporating the product design strategy of alternative design features can make the key player's PDN have better profit under the uncertainty of the currency exchange rate. An illustrative global SC of personal computers/notebooks is also provided to demonstrate the applicability of the KPDN/ADF design model.     

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 enhanced possibilistic programming approach for reliable closed-loop supply chain network design

Most of current logistics network design models in the literature typically assume that facilities are always available and absolutely reliable while in practice, they are always subject to several operational and disruption risks. This paper proposes a reliable closed-loop supply chain network design model, which accounts for both partial and complete facility disruptions as well as the uncertainty in the critical input data. The proposed model is of mixed integer possibilistic linear programming type that aims to minimise simultaneously the total cost of opening new facilities and the expected cost of disruption scenarios. An enhanced possibilistic programming approach is proposed to deal with the epistemic uncertainty in input data. Furthermore, the p-robustness criterion is used to limit the cost of disruption scenarios and protect the designed network against random facility disruptions. Several numerical experiments along with sensitivity analyses on uncertain parameters are conducted to illustrate the significance and applicability of the developed model as well as the effectiveness of the proposed solution approach. Our results demonstrate that operational and disruption risks considerably affect the whole structure of the designed network and they must be taken into account when designing a reliable closed-loop logistics network.     

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.     

Risk evaluation and mitigation of sustainable road freight transport operation: a case of trucking industry

Road freight transportation sustainability is gaining increasing importance due to an ever-increasing freight movement, globalisation and operational flexibility. The transport managers across the globe are finding it difficult to manage the increasing risks in its operation and implementation of risk-mitigation strategies under economical sustainability. However, very few literatures have examined the impact of sustainable risk management practices on road freight transportation. Our study addresses this important gap in the literature by proposing an integrated fuzzy failure mode and effects analysis (FMEA) approach in the selection of risk-mitigation strategy on the trucking industry. Our findings direct to the managers that risk-mitigation strategies must be selected considering the criticality of risks along with the limited budget. In addition, we find that considering subjective evaluations of expert’s judgment and cost benefit justification gives a convincing outcome while calculating of risk-mitigation number in FMEA approach. Proposed approach provides supportive guidelines to the manager to improve the decision-making process.     

Blood supply chain network design considering blood group compatibility under uncertainty

This paper addresses the design of a blood supply chain (SC) network considering blood group compatibility. To this aim, a bi-objective mathematical programming model is developed which minimises the total cost as well as the maximum unsatisfied demand. Due to uncertain nature of some input parameters, two novel robust possibilistic programming models are proposed based on credibility measure. The data of a real case study are then used to illustrate the applicability and performance of the proposed models as well as validating the proposed robust possibilistic programming approach. The obtained results show the superiority of the developed models and significant cost savings compared to current existed blood SC network.     

An optimal procedure for solving the hierarchical network design problem

The hierarchical network design problem consists of finding a minimum cost bilevel network that connects all the nodes in a set, created by a loopless main path and a forest. The main path is formed by primary (higher cost) arcs, providing a path between an origin node and a destination node. The forest, built using secondary (lower cost) arcs, connects all the nodes not on the main path, to the path itself. We state and prove some properties of the problem, which allow finding good upper bounds to the solution in polynomial time when the primary costs are proportional to secondary costs. We also propose an O(n⁴) procedure to improve on these bounds. In turn, these bounds are used to significantly reduce the number of nodes and arcs of the problem. Once the problem is reduced, large instances can be solved to optimality. At this stage, we use one of two linear integer optimization formulations. The first and preferred one is based on multicommodity flows, which avoids the formation of subtours. The second formulation avoids subtours by iteratively adding ad hoc constraints. We show some examples and provide computational experiments performed on networks with sizes up to 600 nodes and 14 000 arcs.     

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.     

A manufacturing network design model based on processor and worker capabilities

This paper presents an optimization methodology to design networks of manufacturing facilities producing several products under deterministic demand. The bill of materials and the operations for each product are taken into account through the use of a product-state graph. Starting from the current state of the manufacturing network, the approach considers a multi-period planning horizon. For each period it specifies the facilities to open within the set of current and potential facilities, the mission for each of the centres in the selected facilities, the equipment to be used for producing the goods, and the structure of the network. Taking human resource competencies into account, the approach selects the type of workers to use for executing the manufacturing tasks. The transfer of resources between plants is also considered. A multi-period mixed integer linear programming model is formulated, a solution method based on the addition of specialized cuts is proposed and computational results are presented.     

Particle-swarm harmony search for water network design

The optimal design of water distribution networks is a non-linear, multi-modal, and constrained problem classified as an NP-hard combinatorial problem. Because of the drawbacks of calculus-based algorithms, the problem has been tackled by assorted stochastic algorithms, such as the genetic algorithm, simulated annealing, tabu search, shuffled frog-leaping algorithm, ant colony optimization algorithm, harmony search, cross entropy, and scatter search. This study proposes a modified harmony search algorithm incorporating particle swarm concept. This algorithm was applied to the design of four bench-mark networks (two-loop, Hanoi, Balerma, and New York City networks), with good results.     

基于JITD的服务备件二级分销网络集成研究

从供应链集成的角度出发,使用双层规划建立了服务备件二级分销网络的设施选址-运输路线安排-库存控制问题(CLRIP)模型,确定了分销中心的位置、车辆的运输路线等。该模型充分考虑决策部门和顾客双方的利益,针对服务备件的价值高以及服务水平要求高的特点,将按需拉动的准时制配送策略（JITD）应用于分销网络设计中,在降低系统成本的同时,可以大幅度提高配送的准时性和稳定性。设计了该模型的启发式算法,通过算例验证了模型和算法的有效性。研究结果有助于优化服务备件分销网络结构、提高配送准时性和降低物流成本。     

Green intermodal freight transportation: bi-objective modelling and analysis

Efficient planning of freight transportation requires a comprehensive look at wide range of factors in the operation and management of any transportation mode to achieve safe, fast, and environmentally suitable movement of goods. In this regard, a combination of transportation modes offers flexible and environmentally friendly alternatives to transport high volumes of goods over long distances. In order to reflect the advantages of each transportation mode, it is the challenge to develop models and algorithms in Transport Management System software packages. This paper discusses the principles of green logistics required in designing such models and algorithms which truly represent multiple modes and their characteristics. Thus, this research provides a unique practical contribution to green logistics literature by advancing our understanding of the multi-objective planning in intermodal freight transportation. Analysis based on a case study from hinterland intermodal transportation in Europe is therefore intended to make contributions to the literature about the potential benefits from combining economic and environmental criteria in transportation planning. An insight derived from the experiments conducted shows that there is no need to greatly compromise on transportation costs in order to achieve a significant reduction in carbon-related emissions.     

A framework for designing a supply chain distribution network

Based on the analysis of the pertinent literature, we propose a framework to serve as a guide in designing a distribution network as a component of a supply chain (SC). It consists of three steps that are common to goods and services SCs: position of the decoupling point, structure of the network, and product delivery. For each step, we take into account the peculiarities of both goods and services separately in order to establish a list of available options and evaluate their suitability in relation to the relevant factors that characterise the products and the markets.