Determinants of the intention to use Buy-Online,Pickup In-Store (BOPS): The moderating effects of situational factors and product type

Despite the wider introduction of the buy online and pick up in-store (BOPS) service by retailers, research on BOPS is still sparse, especially those from the consumer perspective. This paper employs the scenario-based factorial survey method to investigate how the perceived characteristics of innovation and the perceived risk of online shopping influence the consumers’ intention to use BOPS while also considering the moderating effects of situational factors (location convenience) and product type (involvement). Our findings indicated that the consumer perceptions of relative advantage, complexity, compatibility, and risks involved in online shopping are important antecedents to intention to use BOPS, and that these relationships were significantly moderated by locational convenience and product involvement. The implications of the findings and suggestions for future research are discussed in detail.     

Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care

This paper addresses a vehicle scheduling problem encountered in home health care logistics. It concerns the delivery of drugs and medical devices from the home care company’s pharmacy to patients’ homes, delivery of special drugs from a hospital to patients, pickup of bio samples and unused drugs and medical devices from patients. The problem can be considered as a special vehicle routing problem with simultaneous delivery and pickup and time windows, with four types of demands: delivery from depot to patient, delivery from a hospital to patient, pickup from a patient to depot and pickup from a patient to a medical lab. Each patient is visited by one vehicle and each vehicle visits each node at most once. Patients are associated with time windows and vehicles with capacity. Two mixed-integer programming models are proposed. We then propose a Genetic Algorithm (GA) and a Tabu Search (TS) method. The GA is based on a permutation chromosome, a split procedure and local search. The TS is based on route assignment attributes of patients, an augmented cost function, route re-optimization, and attribute-based aspiration levels. These approaches are tested on test instances derived from existing VRPTW benchmarks.     

A General Vehicle Routing Problem

In this paper, we study a rich vehicle routing problem incorporating various complexities found in real-life applications. The General Vehicle Routing Problem (GVRP) is a combined load acceptance and generalised vehicle routing problem. Among the real-life requirements are time window restrictions, a heterogeneous vehicle fleet with different travel times, travel costs and capacity, multi-dimensional capacity constraints, order/vehicle compatibility constraints, orders with multiple pickup, delivery and service locations, different start and end locations for vehicles, and route restrictions for vehicles. The GVRP is highly constrained and the search space is likely to contain many solutions such that it is impossible to go from one solution to another using a single neighbourhood structure. Therefore, we propose iterative improvement approaches based on the idea of changing the neighbourhood structure during the search.     

A column generation approach for location-routing problems with pickup and delivery

In this paper we formulate an integer programming model for the Location and Routing Problem with Pickup and Delivery. We propose a column generation scheme and implement, for the subproblem, a label-setting algorithm for the shortest path with pickup and delivery and time windows problem. We also propose a set of heuristics to speed up this process. To validate the model, we implement the column generation scheme and test it on different instances developed in this paper. We also provide an analysis of how the costs of opening depots and the fixed cost of routes affect the optimal solution.     

BEPCⅡ束团缺口信号的提取

 基于隧道二极管单稳态电路、高速可重触发电路、ECL技术等多种高速电路技术设计了BEPCⅡ束团缺口信号提取电路。介绍了BEPCⅡ储存环中带缺口的多束团运行模式。对Pickup电极感应信号经过长电缆传输衰减后的波形进行了研究。分析了缺口提取电路中处理快速信号的隧道二极管单稳态电路原理,该电路可以将0.3 ns的正脉冲展宽到4 ns的ECL电平脉冲。给出了标准束团注入和非标准注入情况下束团缺口判定逻辑。测试结果表明:此电路对各种束团注入情况均能正常工作,且提取出的同步信号均方根抖动值仅为80.49 ps,满足设计要求。     

Validating vehicle routing zone construction using Monte Carlo simulation

The primary purpose of this paper is to validate a clustering procedure used to construct contiguous vehicle routing zones (VRZs) in metropolitan regions. Given a set of customers with random demand for pickups and deliveries over the day, the goal of the design problem is to cluster the customers into zones that can be serviced by a single vehicle. Monte Carlo simulation is used to determine the feasibility of the zones with respect to package count and tour time. For each replication, a separate probabilistic traveling salesman problem (TSP) is solved for each zone. For the case where deliveries must precede pickups, a heuristic approach to the TSP is developed and evaluated, also using Monte Carlo simulation. In the testing, performance is measured by overall travel costs and the probability of constraint violations. Gaps in tour length, tour time and tour cost are the measure used when comparing exact and heuristic TSP solutions.     

The static bike relocation problem with multiple vehicles and visits

This paper introduces the static bike relocation problem with multiple vehicles and visits, the objective of which is to rebalance at minimum cost the stations of a bike sharing system using a fleet of vehicles. The vehicles have identical capacities and service time limits, and are allowed to visit the stations multiple times. We present an integer programming formulation, implemented under a branch-and-cut scheme, in addition to an iterated local search metaheuristic that employs efficient move evaluation procedures. Results of computational experiments on instances ranging from 10 to 200 vertices are provided and analyzed. We also examine the impact of the vehicle capacity and of the number of visits and vehicles on the performance of the proposed algorithms.     

The static bicycle relocation problem with demand intervals

This study introduces the Static Bicycle Relocation Problem with Demand Intervals (SBRP-DI), a variant of the One Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP). In the SBRP-DI, the stations are required to have an inventory of bicycles lying between given lower and upper bounds and initially have an inventory which does not necessarily lie between these bounds. The problem consists of redistributing the bicycles among the stations, using a single capacitated vehicle, so that the bounding constraints are satisfied and the repositioning cost is minimized. The real-world application of this problem arises in rebalancing operations for shared bicycle systems. The repositioning subproblem associated with a fixed route is shown to be a minimum cost network problem, even in the presence of handling costs. An integer programming formulation for the SBRP-DI are presented, together with valid inequalities adapted from constraints derived in the context of other routing problems and a Benders decomposition scheme. Computational results for instances adapted from the 1-PDTSP are provided for two branch-and-cut algorithms, the first one for the full formulation, and the second one with the Benders decomposition.     

Maritime crude oil transportation - A split pickup and split delivery problem

The maritime oil tanker routing and scheduling problem is known to the literature since before 1950. In the presented problem, oil tankers transport crude oil from supply points to demand locations around the globe. The objective is to find ship routes, load sizes, as well as port arrival and departure times, in a way that minimizes transportation costs. We introduce a path flow model where paths are ship routes. Continuous variables distribute the cargo between the different routes. Multiple products are transported by a heterogeneous fleet of tankers. Pickup and delivery requirements are not paired to cargos beforehand and arbitrary split of amounts is allowed. Small realistic test instances can be solved with route pre-generation for this model. The results indicate possible simplifications and stimulate further research.     

Multiple pickup and delivery traveling salesman problem with last-in-first-out loading and distance constraints

We extend the traveling salesman problem with pickup and delivery and LIFO loading (TSPPDL) by considering two additional factors, namely the use of multiple vehicles and a limitation on the total distance that a vehicle can travel; both of these factors occur commonly in practice. We call the resultant problem the multiple pickup and delivery traveling salesman problem with LIFO loading and distance constraints (MTSPPD-LD). This paper presents a thorough preliminary investigation of the MTSPPD-LD. We propose six new neighborhood operators for the problem that can be used in search heuristics or meta-heuristics. We also devise a two-stage approach for solving the problem, where the first stage focuses on minimizing the number of vehicles required and the second stage minimizes the total travel distance. We consider two possible approaches for the first stage (simulated annealing and ejection pool) and two for the second stage (variable neighborhood search and probabilistic tabu search). Our computational results serve as benchmarks for future researchers on the problem.