Purpose

The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

Design/methodology/approach

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Findings

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

Research limitations/implications

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Originality/value

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

中文翻译：

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针对新的协调动态需求批量和交付计划问题的启发式

目的

这项研究的目的是提出一种新的协调的动态需求批量和交付计划问题（CDLSDP），其中将交付策略集成到协调的动态需求批量问题（CDLSP）中。

设计/方法/方法

作为非确定性多项式完全（NP-complete）问题，该CDLSDP似乎很难通过多项式时间方法求解。为了有效，高效地解决此问题，设计了一个四阶段启发式方法来平衡协调和交付阶段的设置和库存成本，以找到接近最佳的解决方案。

发现

大量的计算实验表明，提出的四阶段启发式算法是有效的。对于1800个不同规模，不同联合设置成本的实验，所提出的启发式方法的解决方案与最佳解决方案的平均差距不超过1.34％。

研究局限/意义

为了降低系统总成本，CDLSDP优化了按时间分段的补货和交货时间表，其中包括每个时期的联合设置成本，项目设置，交付和库存成本。设计了一种有效且高效的四阶段启发式方法来求解CDLSDP。

创意/价值

与传统的CDLSP相比，新的CDLSDP考虑了传递策略。此外，提出的四阶段启发式算法是解决CDLSDP的一个很好的候选者。