Incorporating location,routing and inventory decisions in supply chain network design

This paper for the first time presents a novel model to simultaneously optimize location, allocation, capacity, inventory, and routing decisions in a stochastic supply chain system. Each customer’s demand is uncertain and follows a normal distribution, and each distribution center maintains a certain amount of safety stock. To solve the model, first we present an exact solution method by casting the problem as a mixed integer convex program, and then we establish a heuristic method based on a hybridization of Tabu Search and Simulated Annealing. The results show that the proposed heuristic is considerably efficient and effective for a broad range of problem sizes.     

A three-level supply chain network design model with risk-pooling and lead times

This paper considers a single-sourcing network design problem for a three-level supply chain consisting of suppliers, distribution centers (DC’s) and retailers, where risk-pooling strategy and DC-to-supplier dependent lead times are considered. The objective is to determine the number and locations of suppliers and DC’s, the assignment of each location-fixed DC to a supplier and that of each retailer to a DC, which minimizes the system-wide location, transportation, and inventory costs. The problem is formulated as a nonlinear integer programming model, for which a two-phase heuristic solution algorithm is derived based on the Lagrangian relaxation approach. Numerical experiments show that the proposed heuristic is effective and also efficient.     

Social responsibility and supply chain relationships

We use the term purchasing social responsibility (PSR) to describe the involvement of purchasing managers in socially responsible activities. The purpose of the research is to examine the potential impact that PSR might have on supply chain relationships. Our findings suggest that PSR has a direct and positive impact on supplier performance, as well as an indirect, mediated effect through improved trust and cooperation. These findings hold important implications not only for purchasing managers but also logistics managers in the areas of customer service, distribution, and business-to-business marketing.     

Integrating the warehousing and transportation functions of the supply chain

Electronic commerce and associated business-to-business transaction capabilities have changed the way in which supply chains operate. The Internet has enabled information exchange on an unprecedented scale, often at a pace too fast for normal consumption. Companies are not equipped to make effective use of data from warehouse management systems––which contain information on supplier/customer warehouse inventory levels and key customer ordering patterns––and transportation management systems––within which information pertaining to the location of important supply chain assets such as products or vehicles is typically stored. These systems are key factors in integrating the physical flow of goods along the supply chain. The integration of these systems leads to global inventory visibility, which, in turn, leads to reduced costs and improved customer service by decreasing shipping and receiving cycle times, increasing shipment and inventory accuracy, and decreasing lead-time variability. This paper examines the total cost benefits that can be achieved by suppliers and warehouses through the increased global visibility provided by an integrated system. We develop a discrete event simulation model of a multi-product supply chain to examine the potential benefits to be gained from global inventory visibility and trailer yard dispatching and sequencing techniques. Experimental results demonstrate the potential for this integrated paradigm to improve customer service through improved efficiencies, reduced costs, and reduced lead-time variability.     

Dual sourced supply chains: the discount supplier option

In this paper, we examine the dynamics of a supply chain that has the option of using two suppliers – one reliable, and the other unreliable. We characterize the unreliable supplier with long lead-time mean and variance. Although the use of the unreliable supplier might potentially warrant higher inventory and transportation costs, it is attractive because of the willingness of the supplier to provide a discount on the purchase price. We analyze the cost economics of two suppliers in a broader inventory-logistics framework, one that includes in-transit inventories and transportation costs. In this broader perspective, we provide a simple heuristic and sample exchange curves to determine: (i) if the order should be split between the suppliers; and (ii) if the order is split, the amount of discount and the fraction ordered to the secondary supplier to make order-splitting a worth-while policy. ©     

The split delivery vehicle routing problem with minimum delivery amounts

In the vehicle routing problem, a fleet of vehicles must service the demands of customers in a least-cost way. By allowing multiple vehicles to service the same customer (i.e., splitting deliveries), substantial savings in travel costs are possible. However, split deliveries are often an inconvenience to the customer who would prefer to have demand serviced in a single visit. We consider the vehicle routing problem in which split deliveries are allowed only if a minimum fraction of a customer’s demand is serviced by a vehicle. We develop a heuristic method for solving this problem and report computational results on a wide range of problem sets.     

Diversification strategy with random yield suppliers for a mean–variance risk-sensitive manufacturer

We consider the diversification strategy for a mean–variance risk-sensitive manufacturer with unreliable suppliers. We first analyze the linear model and find that the suppliers are selected according to the descending order of their contributed marginal expected profit, and increasing the manufacturer’s risk-averseness leads to a more even allocation of demand across the suppliers. Then, we study the general newsvendor model. By approximating the leftover inventory with a normal distribution, we establish the general properties of the active supplier set and show that the supplier selection rule is similar to that under the risk-neutral setting when the demand uncertainty is large. Moreover, we conjecture that the selection rule also applies when the demand uncertainty is low, which we verify with an extensive numerical study. Our paper makes two contributions: First, we establish the properties of the optimal diversification strategy and develop corresponding insights into the trade off between cost and reliability under the mean–variance framework. Second, we perform comparative statics on the optimal solution, with a particular emphasis on investigating how changes in the supplier’s cost or reliability affect the risk-averse manufacturer’s ordering decisions and customer service level.     

Sourcing decisions under risks of catastrophic event disruptions

In this paper, a supplier selection problem is studied under risks of supplier failure due to the catastrophic events disruption. An analytical model is developed to determine the optimal number of suppliers considering different failure probability, capacity, and compensation. An algorithm is designed to find the optimal solution and numerical study is carried out to illustrate the model. Results of numerical study and sensitivity analysis provide useful guidelines for managers to select the optimal number of suppliers under the risks of supply disruption.     

Multiple sourcing under supplier failure risk and quantity discount: A genetic algorithm approach

This paper investigates an order allocation problem of a manufacturer/buyer among multiple suppliers under the risks of supply disruption. A mixed integer non-linear programming (MINLP) model is developed for order allocation considering different capacity, failure probability and quantity discounts for each supplier. We have shown that the formulated problem is NP-hard in nature and genetic algorithm (GA) approach is used to solve it. The model is illustrated through a numerical study and the result portrays that the cost of supplier has more influence on order quantity allocation rather than supplier’s failure probability.     

Reliable design of an integrated supply chain with expedited shipments under disruption risks

This paper studied the design of a two-echelon supply chain where a set of suppliers serve a set of terminals that receive uncertain customer demands. In particular, we considered probabilistic transportation disruptions that may halt product supply from certain suppliers. We formulated this problem into an integer nonlinear program to determine the optimal system design that minimizes the expected total cost. A customized solution algorithm based on Lagrangian relaxation was developed to efficiently solve this model. Several numerical examples were conducted to test the proposed model and draw managerial insights into how the key parameters affect the optimal system design.     

Integrated production and intermodal transportation planning in large scale production–distribution-networks

We present a model and solution approach for combining production and intermodal transportation planning in a supply network. A close and detailed integration of both decision fields is missing in the literature so far. The model includes relevant decisions regarding production setups and output volumes of plants, cargo consolidation at intermodal terminals, and capacity bookings for road and rail transports. A Branch-and-Cut method and heuristics are designed for solving the problem. A comprehensive case study for a chemical company identified a 6%-cost saving from the integrated planning. At the same time, companies are successfully supported in establishing eco-friendly distribution processes.     

A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph

We study a time-constrained heterogeneous vehicle routing problem on a multigraph where parallel arcs between pairs of vertices represent different travel options based on criteria such as time, cost, and distance. We formulate the problem as a mixed-integer linear programming model and develop a tabu search heuristic that efficiently addresses computational challenges due to parallel arcs. Numerical experiments show that the heuristic is highly effective and that freight operators can achieve advantages in cost and customer service by considering alternative paths, especially when route duration limits are restrictive and/or when vehicles of smaller capacity are dispatched to serve remote customers.     

The multi-period service territory design problem – An introduction,a model and a heuristic approach

In service territory design applications, a field service workforce is responsible for providing recurring services at their customers’ sites. We introduce the associated planning problem, which consists of two subproblems: In the partitioning subproblem, customers must be grouped into service territories. In the scheduling subproblem, customer visits must be scheduled throughout the multi-period planning horizon. The emphasis of this paper is put on the scheduling subproblem. We propose a mixed integer programming model for this subproblem and present a location-allocation heuristic. The results of extensive experiments on real-world instances show that the proposed heuristic produces high-quality solutions.     

Impact of decision sequence on reliability enhancement with supply disruption risks

This paper considers a supply chain that consists of a manufacturer and a supplier who faces disruption risks. We investigate the impact of decision sequence on the supplier’s endogenous reliability enhancement and the firms’ equilibrium pricing strategies. The supply chain reliability achieves a higher level under the supplier–leader game, but this does not always lead to a higher payoff for the supply chain. Each firm prefers to make the decision first, while any decision sequence can become dominant for the supply chain. We also show that the supply chain can achieve coordination via the revenue sharing contract.     

A location-inventory model for large three-level supply chains

We study the location-inventory problem in three-level supply networks. Our model integrates three decisions: the distribution centers location, flows allocation, and shipment sizes. We propose a nonlinear continuous formulation, including transportation, fixed, handling and holding costs, which decomposes into a closed-form equation and a linear program when the DC flows are fixed. We thus develop an iterative heuristic that estimates the DC flows a priori, solves the linear program, and then improves the DC flow estimations. Extensive numerical experiments show that the approach can design large supply networks both effectively and efficiently, and a case study is discussed.     

Berth scheduling by customer service differentiation: A multi-objective approach

In this paper the discrete and dynamic berth allocation problem is formulated as a multi-objective combinatorial optimization problem where vessel service is differentiated upon based on priority agreements. A genetic algorithms based heuristic is developed to solve the resulting problem. A number of numerical experiments showed that the heuristic performed well in solving large, real life instances. The heuristic provided a complete set of solutions that enable terminal operators to evaluate various berth scheduling policies and select the schedule that improves operations and customer satisfaction. The proposed algorithm outperformed a state of the art metaheuristic and provided improved results when compared to the weighted approach.     

Inventory optimization for a customer airline in a Performance Based Contract

The supply of spare parts has a crucial role in the aviation sector, mainly due to the high costs of spare parts and to the strict availability requirements. In a stand-alone scenario, an airline owns the spare parts and manages the maintenance tasks by itself. A new trend consists of not owning the spare parts and delegate the maintenance tasks to an external company, taking advantage of a specific Performance Based Contract (PBC). The PBCs aim to reduce the ownership cost for the customer airline, while ensuring a target system performance. Spare parts become a variable cost for the customer airline and a business income for the maintenance supplier, which is commonly another airline.This paper proposes an innovative model, i.e. the PBC-METRIC, which supports the customer airline manager to minimize the spare parts supply cost, in compliance with the airline availability requirements and with respect to the PBC. In detail, the PBC-METRIC models a multi-echelon, multi-item, single-indenture, multi-transportation network, by an innovative two-steps algorithm, defining the PBC specifications as modelling variables and parameters. A case study on a European airline, with the role of customer in a PBC, illustrates the outcome of the model.     

An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.     

The competitive facility location problem under disruption risks

Two players sequentially locate a fixed number of facilities, competing to capture market share. Facilities face disruption risks, and each customer patronizes the nearest operational facility, regardless of who operates it. The problem therefore combines competitive location and location with disruptions. This combination has been absent from the literature. We model the problem as a Stackelberg game in which the leader locates facilities first, followed by the follower, and formulate the leader’s decision problem as a bilevel optimization problem. A variable neighborhood decomposition search heuristic which includes variable fixing and cut generation is developed. Computational results suggest that high quality solutions can be found quickly. Interesting managerial insights are drawn.     

A Lagrangian heuristic for the real-time vehicle rescheduling problem

When a public transit vehicle breaks down on a scheduled trip, one or more vehicles need to be rescheduled to serve that trip and other service trips originally scheduled for the disabled vehicle. In this paper, the vehicle rescheduling problem (VRSP) is investiaged to consider operating costs, schedule disruption costs, and trip cancellation costs. The VRSP is proven to be NP-hard, and a Lagrangian relaxation based insertion heuristic is developed. Extensive computational experiments on randomly generated problems are reported. The results show that the Lagrangian heuristic performs very well for solving the VRSP.