The technique of cross-docking, which consists in unloading trucks, sorting the items they contain and reloading them directly into outbound trucks in order to minimize temporary storage, has attracted researchers׳ attention in the past few years. The number of articles on the subject has been growing very fast, but largely detached from industry practice. In order to see whether the current state-of-the-art matches the industry practice, we propose a common framework that helps comparing the literature review regarding cross-docking operations with on-field observations and platform managers׳ interviews. Analyzing the gaps between the state-of-the-art and the industry practice helps drawing future research directions, in relation to industrial needs.

Cross-docking operations: Current research versus industry practice

This paper provides a comprehensive literature review of mathematical models in cross docking planning. From the reviews, the models are classified in three different levels regarding its decisions level which are operational, tactical, and strategic level. The researches in operational level are mainly related to develop model in scheduling, dock door assignment, transhipment problem, vehicle routing, and product allocation. For tactical and strategic level, the researches are mainly proposing model to design the layout and the network of cross docking respectively. The contribution of this paper is to realize the gaps of knowledge in strategic, tactical and operational levels and point out the future research directions in cross docking.

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A Review: Mathematical Modles for Cross Docking Planning

Cross-docking is a material handling technique in supply chain management.We consider multi-objective mathematical modeling for solving cross-docking problems.We propose genetic algorithm and particle swarm optimization to solve the problem.We minimize the make-span, transportation cost and the number of truck trips. Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This process minimizes the storage and order-picking functions in a warehouse. In this paper, we consider cross-docking in a supply chain and propose a multi-objective mathematical model for minimizing the make-span, transportation cost and the number of truck trips in the supply chain. The proposed model allows a truck to travel from a supplier to the cross-dock facility and from the supplier directly to the customers. We propose two meta-heuristic algorithms, the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective particle swarm optimization (MOPSO), to solve the multi-objective mathematical model. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example. The numerical results show the relative superiority of the NSGA-II method over the MOPSO method.

A novel multi-objective meta-heuristic model for solving cross-docking scheduling problems

Crossdocking is a distribution strategy in which distribution centers operate as transfer points to harmonize the continuous physical flow through supply chain with the least storage. The coordination of this system in a network of crossdocks with multitype and time-restricted pickups and deliveries requires a complex planning. This paper addresses the distribution planning problem of crossdocking network, considering transshipment possibility among crossdocks and tardiness permission for some pickups. The problem is formulated as a bi-objective integer-programming model minimizing total transportation and holding costs and total tardiness. An innovative heuristic procedure to construct an effective initial solution and three improving algorithms based on appropriate meta-heuristics (variable neighborhood search, tabu search, and simulated annealing) is developed to solve the problem. Experimental results demonstrate the potency of proposed algorithms achieving remarkable results.

Bi-objective heuristics for multi-item freights distribution planning problem in crossdocking networks

In this paper the authors deal with the scheduling of inbound and outbound trucks to the available inbound and outbound doors at a cross dock facility. They assume that all trucks served at the facility need to meet several deadlines for deliveries and pick-ups and thus request a departure time window from the facility, penalizing the facility operator, on a unit of time basis, if that deadline is not met. To solve the resulting problem with reasonable computational effort, a memetic algorithm is developed and a number of computational examples show the efficiency of the proposed solution algorithm and the advantages of scheduling inbound and outbound trucks simultaneously, as opposed to sequentially.

Advances in Truck Scheduling at a Cross Dock Facility

In this paper we study a cross-docking problem minimizing the total flow time of inbound and outbound jobs. Using the theories and methodologies of scheduling, we formulate the problem into a two-stage scheduling problem and propose heuristics with worst-case performance analysis under parallel, uniform and open-shop machines, respectively. For each of problems studied, some polynomially solvable special cases are also introduced.

Scheduling Problems in Cross Docking

For the problem of scheduling n-jobs on one-machine with agreeable job release dates and due dates to minimize the number of late jobs, Kise, Ibaraki and Mine (Oper. Res. 26:121–126, 1978) gave an O(n2)-time algorithm and proved its optimality by four lemmas. Li et al. (Oper. Res. 58:508–509, 2010) gave a counter-example to show that one lemma is invalid in some case and therefore the optimality is also invalid. In this paper, we revise the lemma and prove that the algorithm is still valid.

A revised proof of the optimality for the Kise–Ibaraki–Mine algorithm

In this paper, we consider the single machine scheduling problem with inventory operations The objective is to minimize makespan subject to the constraint that the total number of tardy jobs is minimum We show the problem is strongly NP-hard A polynomial $1 + \frac{1}{m-1}$-approximation scheme for the problem is presented, where m is defined as the total job's processing times ∑ pj divided by the capacity c of the storage, and an optimal algorithm for a special case of the problem, in which each job is one unit in size

Bicriteria scheduling on single-machine with inventory operations

In this paper, we consider the single machine scheduling problem with inventory operations. The objective is to minimize makespan subject to the constraint that the total number of tardy jobs is minimum. We show the problem is strongly NP-hard. A polynomial (1 + 1/(m *** 1))-approximation scheme for the problem is presented, where m is defined as the total job's processing times *** p j divided by the capacity c of the storage, and an optimal algorithm for a special case of the problem, in which each job is one unit in size, is provided.

Bicriteria Scheduling on Single-Machine with Inventory Operations

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Papers

Scheduling Problems in Cross Docking

A revised proof of the optimality for the Kise–Ibaraki–Mine algorithm

Bicriteria scheduling on single-machine with inventory operations

Bicriteria Scheduling on Single-Machine with Inventory Operations