Optimization problems in a crossdocking distribution system

Crossdocking has been catching on for the past several years as more and more third-party warehouses and distribution centers add it to their list of services since crossdocking with its many advantages, including cutting costs and trans-portation time, is expected to capture their undivided attention in short order. The application of crossdocking functions shifts focus from maintaining inven-tory storage to flow-through inventories. Crossdocking is an important concept because it can greatly decrease inventory storage and reduce the product flow line between the manufacturer, the warehouse and your customers. In a global level, how to schedule the transhipment, how to allocate the cargoes to the trucks in LTL (less-than-truckload) transportation segment, and how those crossdocks cooperate well with each other to achieve the global optimal performance in a complex crossdocking distribution system are all very important issues in daily operations. On the other hand, for a local level, how to assign the docks to the trucks is another key issue in crossdocking since good assignment can maximize the throughput of the crossdocking operations and minimize the total operation cost. This thesis is motivated to model, analyze, and provide algorithms on solving above two sets of problems. In particular, a major challenge in making supply meet demand is to coordinate transshipments across the supply chain to reduce costs and increase service levels in the face of demand fluctuations, short lead times, warehouse limitations and transportation and inventory costs. And transshipment through crossdocks, where just-in-time objectives prevail, requires precise scheduling between suppliers, crossdocks and customers. In this work, we study the transshipment problem with supplier and customer time windows where flow is constrained by transportation schedules and warehouse capacities. Transportation is provided by fixed or flexible schedules and lot-sizing is dealt with through multiple shipments. We develop polynomial-time algorithms or, otherwise, provide the complexity of the problems studied. Another two kinds of transshipment problems in LTL transportation segment, which are formulated as Integer Programming (IP) problems and proved to be strongly NP-complete, are also studied in this thesis. We develop a two-stage heuristic algorithm to obtain good solutions efficiently. For local level, we mainly study truck-dock assignment problems with two versions. The first version is to consider the over-constrained truck dock assignment problem with time windows and capacity constraint in crossdocks where the number of trucks exceed the number of docks available and the capacity of the crossdock is limited, and where the objectives are to minimize the total shipping distances. However, in the second version, the big difference is to take the operational time for cargo shipment among the docks into considera-tion, so that the problem feasibility is affected by three factors: the arrival and departure time window of each truck, the operational time for cargo shipment among the docks, and the total capacity available to the crossdock. Both of them are then formulated as IP models. We find that as the problem size grows, the IP model size quickly expands to an extent that the ILOG CPLEX Solver can hardly manage. Therefore, two meta-heuristics approaches, Tabu Search(TS) and Ge-netic algorithm(GA) , are proposed. Computational experiments are conducted, showing that meta-heuristics, especially the Tabu Search, dominate the CPLEX Solver in nearly all test cases adapted from industrial applications

Truck dock assignment problem with operational time constraint within crossdocks

In this paper, we consider a truck dock assignment problem with an operational time constraint in crossdocks where the number of trucks exceeds the number of docks available. The problem feasibility is affected by three factors: the arrival and departure time window of each truck, the operational time for cargo shipment among the docks, and the total capacity available to the crossdock. The objective is to find an optimal assignment of trucks that minimizes the operational cost of the cargo shipments and the total number of unfulfilled shipments at the same time. We combine the above two objectives into one term: the total cost, a sum of the total dock operational cost and the penalty cost for all the unfulfilled shipments. The problem is then formulated as an integer programming (IP) model. We find that as the problem size grows, the IP model size quickly expands to an extent that the ILOG CPLEX Solver can hardly manage. Therefore, two meta-heuristic approaches, Tabu Search (TS) and genetic algorithm (GA), are proposed. Computational experiments are conducted, showing that meta-heuristics, especially the Tabu search, dominate the CPLEX Solver in nearly all test cases adapted from industrial applications.Heuristics Crossdocks Dock assignment

Truck dock assignment problem with operational time constraint within crossdocks

In this paper, we consider a truck dock assignment problem with an operational time constraint in crossdocks where the number of trucks exceeds the number of docks available. The problem feasibility is affected by three factors: the arrival and departure time window of each truck, the operational time for cargo shipment among the docks, and the total capacity available to the crossdock. The objective is to find an optimal assignment of trucks that minimizes the operational cost of the cargo shipments and the total number of unfulfilled shipments at the same time. We combine the above two objectives into one term: the total cost, a sum of the total dock operational cost and the penalty cost for all the unfulfilled shipments. The problem is then formulated as an integer programming (IP) model. We find that as the problem size grows, the IP model size quickly expands to an extent that the ILOG CPLEX Solver can hardly manage. Therefore, two meta-heuristic approaches, Tabu Search (TS) and genetic algorithm (GA), are proposed. Computational experiments are conducted, showing that meta-heuristics, especially the Tabu search, dominate the CPLEX Solver in nearly all test cases adapted from industrial applications. (C) 2007 Elsevier B.V. All rights reserved

A Hybrid Genetic Algorithm for the Multiple Crossdocks Problem

We study a multiple crossdocks problem with supplier and customer time windows, where any violation of time windows will incur a penalty cost and the flows through the crossdock are constrained by fixed transportation schedules and crossdock capacities. We prove this problem to be NP-hard in the strong sense and therefore focus on developing efficient heuristics. Based on the problem structure, we propose a hybrid genetic algorithm (HGA) integrating greedy technique and variable neighborhood search method to solve the problem. Extensive experiments under different scenarios were conducted, and results show that HGA outperforms CPLEX solver, providing solutions in realistic timescales

ON PLANAR MEDIANOID COMPETITIVE LOCATION PROBLEMS WITH MANHATTAN DISTANCE

National Natural Science Foundation of China [71222105, 70701039, 70802052, 71072090]; Humanities and Social Science [09YJC630237]; National Ministry of Education; Fundamental Research Funds for the Central UniversitiesA medianoid problem is a competitive location problem that determines the locations of a number of new service facilities that are competing with existing facilities for service to customers. This paper studies the medianoid problem on the plane with Manhattan distance. For the medianoid problem with binary customer preferences, i.e., a case where customers choose the closest facility to satisfy their entire demand, we show that the general problem is NP-hard and present solution methods to solve various special cases in polynomial time. We also show that the problem with partially binary customer preferences can be solved with a similar approach we develop for the model with binary customer preferences

Crossdocking distribution networks with setup cost and time window constraint

In this work, we study a new shipment consolidation and transportation problem in crossdocking distribution networks that considers trade-offs between transportation costs, inventory and time scheduling requirements. Transportation costs include time costs, truck setup costs, and the number of trucks used. The model is formulated as an integer program, and shown to be in the strong sense. Moreover, a solution approach is provided which consists of two stages. First, a reduced problem is solved for a truckload transportation plan. This is followed by a heuristic solution approach to the remaining less-than-truckload problem. Computational experiments are conducted to test the effectiveness and efficiency of the heuristics. The various cost parameters and time window settings of the distribution network are also discussed.Transportation Integer program Heuristics Crossdocking

Study on the Influence of a Soft Soil Interlayer on Spatially Varying Ground Motions

The existence of local soft interlayer can significantly amplify or attenuate the ground motion and thus might influence the lagged spatial coherency between spatially varying earthquake ground motions. A target site with a local soft interlayer was assumed first, and then two numerical examples were set. In example 1, linear soil behavior was considered and a large amount of quasi-stationary spatially varying earthquake ground motions were generated by combining the one-dimensional wave propagation theory and the classical spectral representation method. The influence regularity of varying shear wave velocity, buried depth, and thickness of the soft interlayer on the characteristics of lagged spatial coherency was investigated. In example 2, non-linear soil behavior was taken into account and fully non-stationary spatially varying earthquake ground motions were thus generated by using time-varying transfer function and spectral representation method. An overall evaluation was carried out to shed light on the differences of characteristics of spatial coherency between non-linear soil and linear soil cases. It showed that: (i) As the shear wave velocity of interlayer declines and as the buried depth and thickness increase, remarkable reduction of spatial coherency showed up; (ii) the reduction of lagged spatial coherency caused by varying buried depth may be more inclined to concentrate in the lower frequency range; (iii) the non-linear soil behavior can cause greater further reduction of lagged spatial coherency in comparison with linear soil behavior, especially in the higher frequency range; (iv) the troughs of lagged spatial coherency curve tend to be located in the variation range of vibration frequency of time-varying spectral ratio

Exploring the antecedents of logistics social responsibility: A focus on Chinese firms

Fundamental Research Funds for the Central Universities [2010221025, 2011221016]; National Natural Science Foundation of China [70802052]; Academic Outstanding Youthful Research Talent Plan of Fujian Province [JA10001S]; National Research Foundation for Doctoral Program of Higher Education of China [20100121120013]; National Ministry of Education of China (Humanities and Social Science) [10YJC630010]; [NCET-10-0712]With globalization, especially after China's entry into the WTO, an increasing number of Chinese firms have experienced social responsibility barriers such that they lose international orders due to failure in meeting the requirements of environment, human rights or safety standard. This study attempts to shed some light on the mechanism underlying logistics social responsibility (LSR) in China. In particular, based on the five-dimensional structure of LSR framework, we propose that clan culture, business ethics, pressures from customers, suppliers, competitors and law/regulations are important antecedents of five dimensions of LSR. A mail survey was conducted in China and a total of 162 firm-level questionnaires were returned. Structural equation modeling was employed to test our theory. The results support our hypotheses that clan culture and business ethics of a firm have significant impacts on all the five dimensions of LSR. However, pressures from customers, suppliers, competitors and law/regulations only have effects on some dimensions of LSR. The contributions and implications of these findings are discussed further. (C) 2011 Elsevier B.V. All rights reserved