Simulating less‐than‐truckload terminal operations

Abstract

Purpose -Recent surveys indicate that transportation companies are not utilizing technology in decision making despite growing complexity of transportation systems. This paper aims to present a discrete simulation approach to benchmarking performance measures of terminal operations of less-than-truckload (LTL) freight carriers. Design/methodology/approach -The methodology involves design of heuristics for the dock assignment problem and uses discrete event simulation to evaluate performance of the various heuristics. Findings -Intelligent dock assignment for incoming trailers can greatly improve performance of LTL terminals and simulation is an effective tool to determine the effects of various assignments on terminal performance. Originality/value -The paper introduces a dock assignment heuristic and integrates the tactical level decision-making process and operational aspects in LTL terminals to evaluate the performance of the system. A case study is used to demonstrate the use of the heuristic and performance improvements.

A hybrid simulation model of inbound logistics operations in regional food supply systems

“…For example, DES has been used to evaluate the performance of a supply chain for chilled food products (Van der Vorst et al 2000), as well as comparing different transport modes in terms of logistics cost, energy use, CO2 emissions, and product quality decay (Van der Vorst et al 2009). DES has also been used to study the terminal operations of a warehouse, which involves loading, unloading, and other warehouse-specific activities (Liong and Loo 2009;Deshpande et al 2007). Liong and Loo (2009) used DES to develop a strategy to optimize the residence time of delivery trucks and found that the truck drivers have to wait in long queues when there is no scheduling of arrivals.…”

Truck scheduling optimization in the logistics of crossdocking

“…Truck scheduling in this setting reduces to assigning outbound destinations to outbound doors over a predefined planning horizon and nightly scheduling inbound trucks based on a given outbound door assignment. Static door assignments are employed by the majority of papers addressing truck scheduling in less than truckload (LTL) terminals in which the operations are typical crossdocking operations [16]. There is also one variation of static door assignments practiced in "production crossdocks"…”

“…Resource unavailability is generally represented as delays in the scheduling length. Addressing a scheduling problem in a resource-constrained environment is much more complicated [8,9,[21][22][23][36][37][38][39][40][41][42][43][44][45][46][47] crossdocking exclusive [6,8,9,[16][17][18][21][22][23] [ 25-35, 38-41, 43, 47] mixed [36,37,[44][45][46] scheduling synchronous [6,8,9,17,18,[25][26][27][28][29] [ [31][32][33][34][35][36][37][38]…”

“…al [23] formulate their truck scheduling problem as a multi-objective optimization problem (MOOP) by defining two objective functions: minimization of the total crossdocking operation time and minimization of the total tardiness of outgoing trailers. For hybrid scheduling where incoming trailers arrive at the terminal at different times, the common objective is to minimize the average time a shipment spends in a terminal [16,30,51]. Another example is the work by Lim et.…”

“…where the solution is a set, or a sequence, or integers or other discrete objects [51]. The solution approaches to this sort of problems range from optimal mathematical models for benchmarking purposes to sub-optimal heuristic methods for [6,8,9,21,22,25,26,31,32,35,37,38,44,45] exact algorithms (B&B, DP) [9,17,18,21,27,34] constructive heuristics [6,9,31,[34][35][36]38] meta-heuristics [8, 21-23, 28, 29, 32, 33, 39-47] hybrid algorithms [8,9,25,26,32,33,40] simulation [16,25,30] scalability and fast response time. The common solution techniques together with the complete list of the related papers are summarized in Table 2.2(b) and described in the next few paragraphs.…”