A novel mathematical model for a multi-period,multi-product optimal ordering problem considering expiry dates in a FEFO system

One of the main challenges of retail units is to determine the order quantities of different types of products, each with a specific expiry date, so that the system cost including shortage cost is minimized. We study a new multi-product multi-period replenishment problem for a First Expired-First Out (FEFO) based warehouse management system. The proposed nonlinear model is first converted to a linear one and then solved by applying two evolutionary algorithms: the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), in which design parameters are set using Taguchi method. Computational results demonstrate the applicability of the proposed model for perishable items and comparing the results shows the efficiency of the proposed metaheuristics as well.     

An integrated model for stock replenishment and shipment scheduling under common carrier dispatch costs

We examine a joint inventory replenishment and shipment scheduling problem that arises in the context of a vendor-managed inventory (VMI) arrangement. Since a temporal shipment consolidation policy is being implemented, the inventory requirements at the vendor are affected by the timing and quantity of shipment release. The vendor’s problem is to determine an integrated policy for inventory replenishment and shipment release and to set its parameters. We develop analytical models for computing such integrated policies where it is economical to use common carriage for outbound transportation. We propose algorithmic approaches to set the optimal policy parameter values.     

Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions

In urban logistics, the last-mile delivery from the warehouse to the consumer’s home has become more and more challenging with the continuous growth of E-commerce. It requires elaborate planning and scheduling to minimize the global traveling cost, but often results in unattended delivery as most consumers are away from home. In this paper, we propose an effective large-scale mobile crowd-tasking model in which a large pool of citizen workers are used to perform the last-mile delivery. To efficiently solve the model, we formulate it as a network min-cost flow problem and propose various pruning techniques that can dramatically reduce the network size. Comprehensive experiments were conducted with Singapore and Beijing datasets. The results show that our solution can support real-time delivery optimization in the large-scale mobile crowd-sourcing problem.     

A robust inventory routing policy under inventory inaccuracy and replenishment lead-time

In this paper, we study an inventory routing problem under replenishment lead-time and inventory inaccuracy, which exist extensively in distribution systems for fresh products, but are often ignored in existing research. To solve the problem, a robust inventory routing policy is developed in three steps. At first, we propose the methods of updating the probability of the current net inventory and predicting those in future periods. For each candidate route, we develop a Robust TQL Algorithm to optimize the replenishment time, replenishment quantity and replenishment stage length. Finally, a genetic algorithm-based method is developed to optimize the delivery route.     

Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits

This paper studies a practical multi-factory job allocation and scheduling problem involving inland and maritime transport limits. A new heuristic called Due-date Based Cut-off rule (DBC) is developed to improve the computational efficiency of both exact and genetic algorithms (GA). Except the application of DBC, this proposed GA is guided by a novel fuzzy controller aimed at eliminating the drawbacks other GAs have when dealing with multi-factory models. The tests of the solution quality and computational efficiency for this GA are carried out. The numerical experiments demonstrate the value of the proposed approach in this practical global supply chain.     

Design and planning for green global supply chains under periodic review replenishment policies

We quantify the impact of jointly optimizing strategic network design and tactical inventory planning on the cost and CO₂ emissions of multi-echelon logistics networks. The obtained insights indicate that longer optimized replenishment cycles reduce a node’s transportation cost and CO₂ emissions but increase its inventory costs. Moreover, under a fixed replenishment cycle, a node’s service level increases when supplied by a satellite warehouse. Finally: (i) the costs of implementing optimal green network design decisions could be misleading if inventory planning is neglected, (ii) greening of supply chains could become expensive, (iii) current legislative CO₂ ton prices hardly influence logistics networks.     

Multi-level inventory management decisions with transportation cost consideration

In this article we address specific inventory management decisions with transportation cost consideration in a multi-level environment consisting of a supplier–warehouse–retailers. We develop two models – namely, decentralized ordering model and centralized ordering model to investigate the effect of collective ordering by retailers on the total inventory cost of the system. A numerical study shows that the proposed model is robust and generates reasonable cost savings. The models have potential in several multi-level applications such as fresh or frozen food delivery to stores of different supermarkets or the supply of medicine to a number of hospitals from a wholesaler.     

Integration of inventory and transportation decisions in a logistics system

This paper addresses some of the challenges faced by a company which is responsible for delivering coal to its four subsidiaries situated along a river, through river hired or self-owned vessels. We propose to adopt a vendor managed inventory concept that involves establishment of a central warehouse at the port, and apply the Markov Decision Process (MDP) to formulate both ordering and delivery problems, considering different transportation modes, costs, and inventory issues. An efficient algorithm is developed for solving the MDP models. Our computational tests show that the proposed strategy can significantly reduce the overall system costs while maintaining smooth Just-in-Time supplies of coal to the subsidiaries.     

Coordinated inventory replenishment and outsourced transportation operations

We consider a one-warehouse N retailers supply chain with stochastic demand. Inventory is managed in-house whereas transportation is outsourced to a 3PL provider. We develop analytical expressions for the operating characteristics under both periodic and continuous joint replenishment policies. We identify the settings where a periodic review policy is comparable to a continuous review one. In our numerical test-bed, the periodic policy performed best in larger supply chains operating with larger trucks. We also observed that if the excess utilization charge is less than 25%, outsourcing becomes beneficial even if outsourcing cost is 25% more than the in-house fleet costs.     

Specification for a dynamic vehicle routing and scheduling system

In an e-commerce environment, order fulfilment is driven by customer demands and expectations. A dynamic vehicle routing and scheduling system may be specified which allows e-commerce customers to select their own delivery Time Windows and have these confirmed on-line as they place their order. The methodology is based upon demand forecasting, which leads to the generation of phantom orders and phantom routes. Subsequently, actual orders substitute for phantom orders in an on-line customer order process. The routing and scheduling method includes using both parallel tour-building and parallel insertion algorithms. Customer service levels are confirmed using GPS tracking and tracing, and a feedback loop uses expert systems or artificial intelligence as an input to the demand forecasting data to restart the whole process.     

The effects of resupply flexibility on the design of service parts supply systems

We apply simulation optimization to determine the optimal design and stock distribution for a single item supply system with a one-for-one replenishment policy. We investigate both the effect of the number of echelons and the degree of resupply flexibility, considering single-echelon and two-echelon systems with either no resupply flexibility, lateral transhipments only or both lateral transhipments and emergency deliveries. We show that the implementation of an emergency delivery option allows an augmentation of the fraction of customers served by lateral transhipments and that increased resupply flexibility enables increasingly important cost savings.     

A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty

This paper addresses an integrated model that schedules multi-item replenishment with uncertain demand to determine delivery routes and truck loads, where the actual replenishment quantity only becomes known upon arrival at a demand location. This paper departs from the conventional ant colony optimization (ACO) algorithm, which minimizes total travel length, and incorporates the attraction of pheromone values that indicate the stockout costs on nodes. The contributions of the paper to the literature are made both in terms of modeling this combined multi-item inventory management with the vehicle-routing problem and in introducing a modified ACO for the inventory routing problem.     

Reformulating Environmentally Constrained Traffic Equilibrium via a Smooth Gap Function

Various government laws have recently been enacted to alleviate the environmental deterioration of transportation systems. Environmental constraint is a valid means to explicitly reflect various environmental protection requirements imposed by the government. In this paper, we examine the environmentally constrained traffic equilibrium problem (EC-TEP), which is a fundamental tool for modeling and evaluating environmental protection requirements. Specifically, we provide an equivalent reformulation for the EC-TEP. The proposed reformulation adapts the concept of gap function to simultaneously reformulate the nonlinear complementarity conditions associated with the generalized user equilibrium conditions, environmental constraints, and conservation constraints as an equivalent unconstrained optimization problem. This gap function reformulation has two desirable features: (1) it can handle a general environmental constraint structure (linear or nonlinear; link-based or area-based) and a general link and route cost structure, enhancing the modeling adaptability and flexibility; (2) it is smooth and unconstrained, permitting a number of existing efficient algorithms for its solution. A gradient-based solution algorithm with a self-regulated averaging stepsize scheme is customized to solve the reformulated unconstrained optimization problem. Numerical examples are also provided to demonstrate the modeling flexibility of the proposed EC-TEP reformulation.     

Modeling and optimizing transportation decisions in a manufacturing supply chain

We describe a transportation problem we studied at the trucking division of a textile manufacturer that owns and operates a large number of manufacturing facilities in all stages of the manufacturing supply chain. The problem involves scheduling of pickup and delivery of daily inventory movement between plants. We develop integer programming models that are based on the current workflow of the schedulers and that capture and optimize crucial aspects of the problem. We validate the models and demonstrate their use with actual data. The results suggest that an effective computerized decision-support system can be built around these models.     

A generalized algebraic model for optimizing inventory decisions in a multi-stage complex supply chain

In this paper, we deal with more generalized inventory coordination mechanism in an n-stage, multi-customer, non-serial supply chain, where we extend and generalize pervious works that use algebraic methods to optimize this coordinated supply chain. We establish the recursive expressions for this multi-variable optimization problem. These expressions are used for the derivation of the optimal replenishment policy and the development of the solution algorithm. Further, we describe a simple procedure that can help in sharing the coordination cost benefits to induce all stages to adopt the inventory coordination mechanism. We provide a numerical example for illustrative purposes.     

The profit-maximization model for a multi-item distribution channel

This study focused on an area of emerging research: managing a multi-product and multi-echelon supply chain which produces and sells deteriorating goods in the marketplace. We formulated four profit-maximization models by considering the effects of channel coordination and a joint replenishment program on the supply-side cost control, taking into account the effect of the pricing scheme on demand and revenue increments. In addition, a profit-sharing mechanism based on channel rebates is proposed, which leads to Pareto improvements among the channel participants.     

The potential of optimization in communal routing problems: case studies from Finland

In many European countries, municipalities offer their inhabitants a wide variety of social services. In this paper we will focus on efficiently scheduling home care, transportation of the elderly, and home meal delivery. These so-called municipal or communal routing problems can be modeled as different variants of the vehicle routing problem, a well-known optimization problem from the literature. We present a focused literature review and report on case studies using Finnish data. The computational results show that there is a significant potential for cost savings for all applications considered.     

A unit-load warehouse with multiple pickup and deposit points and non-traditional aisles

We show how to configure a cross aisle in a unit-load warehouse to facilitate travel between storage locations and multiple pickup and deposit points on one side. We use our models to investigate designs having two types of cross aisles—those that form a “Flying-V” and those that form an “Inverted-V.” Our numerical results suggest that there is a benefit to using a Flying-V aisle design, but the benefit is more modest than in the case of a single P&D point. Thus, to the extent practicable, pickup and deposit points should be concentrated toward the middle of the warehouse.     

Anticipatory algorithms for same-day courier dispatching

This paper describes anticipatory algorithms for the dynamic vehicle dispatching problem with pickups and deliveries, a problem faced by local area courier companies. These algorithms evaluate alternative solutions through a short-term demand sampling and a fully sequential procedure for indifference zone selection. They also exploit an unified and integrated approach in order to address all the issues involved in real-time fleet management, namely assigning requests to vehicles, routing the vehicles, scheduling the routes and relocating idle vehicles. Computational results show that the anticipatory algorithms provide consistently better solutions than their reactive counterparts.     

Scheduling reefer mechanics at container terminals

This paper discusses the scheduling of reefer mechanics at container terminals. Reefer mechanics plug and unplug reefer containers such that due times are met. We outline the resulting scheduling problem and two simple heuristics. Subsequently, we present a simulation model to analyze the scheduling methods and the reefer-related processes in a realistic dynamic framework. Some results from the simulation experiments are also presented. They demonstrate the applicability of the heuristic and the use of the simulation model in practice. The simulation study was carried out for a real container terminal in the port of Hamburg, Germany.