In this paper we propose a simple but efficient modification of the well known Nelder Mead (NM) simplex search method for unconstrained optimization, Instead of moving all n simplex vertices at once in the direction of the best vertex, our "shrink" step moves them in the same direction but one by one until an improvenlent is obtained, In addition, for solving non convex problems, we sbnply restart the so modified NM (MNM) method by constructing an initial simplex around the solution obtained in the previous phase, We repeat restarts until there is no improvement in the objective function value, Thus, our restarted modified NM (RMNM) is a descent and deterministic method and may be seen as an extended local search for continuous optimization, In order to improve computational complexity and efficiency, we use the heap data structure for storing and updating simplex vertices, Extensive empirical analysis shows that: our modified method outperforms in average the original version as well as some other recent successful modifications; in solving global optimization problems, it is comparable with the state of-the art heuristics.

This paper considers a two-level vendor managed inventory (VMI) system comprising a distribution center (DC) and a retailer. Both the DC's and the retailer's replenishment decisions follow the order-up-to-level policy and aim at maximizing the profit of the overall system. We critically examine the potential of the DC's ability to modify delivery decisions, identify and quantify the cost factors that influence the DC's modification ability, establish a relationship between the DC's location and its modification ability, and show the trade-off between the DC's modification ability and related costs. Our analysis provides a new insight into the role of the DC and reveals the full potential of the VMI system. Our findings and their practical implications, demonstrated

This paper addresses an integrated inventory and routing problem in a three-echelon logistics system, which consists of a supplier, a central warehouse and a group of retailers. The inventory decision of each member and the routing decision among members of the system are made simultaneously, with the objective of minimizing the overall average cost of the system. A strategy named fixed partition and power-of-two (FP-POT) is proposed for the considered problem and a variable large neighborhood search (VLNS) algorithm, which is a special case of variable neighborhood search (VNS) algorithm, is developed. The efficiency of the strategy as well as the algorithm is illustrated by comparing computational results with a lower bound. The advantage of the proposed VLNS algorithm is further shown by getting better results for the problems in a two-echelon logistics system, which have been solved by a Tabu Search algorithm recently.

In this study we focus on the integration of inventory control and vehicle routing schedules for a distribution system in which the warehouse is responsible for the replenishment of a single item to the retailers with demands occurring at a specific constant (but retailer-dependent) rate, combining deliveries into efficient routes. This research proposes a fixed partition policy for this type of problem, in which the replenishment interval of each of the retailers' partition region as well as the warehouse is accorded the power of two (POT) principle. A lower bound of the long-run average cost of any feasible strategy for the considered distribution system is drawn. And a tabu search algorithm is designed to find the retailers' optimal partition regions under the fixed partition policy proposed. Computational results reveal the effectiveness of the policy as well as of the algorithm.

In this paper, we address the problem of deciding the optimal ordering quantity and frequency for a supplier–retailer logistic system in which the transportation cost as well as the multiple uses of the vehicles are considered. Based on the traditional economic order quantity (EOQ) formula, a modified EOQ model is set up and an algorithm for the model is presented. Computational results verify the proposed model as well as the efficiency of the algorithm.

A study of the vehicle transportation system for a manufacturer is presented. An algorithm based on a dynamic programming model is developed so as to find the optimal transportation arrangements referring to the composition of the vehicles as well as the routing of these vehicles. The algorithm is run under the current condition as well as under a number of different scenarios. It is shown the algorithm can solve the problem with reduced computational complexity. The findings and suggestions resulting from the study can help the department manager in reviewing current operations arrangement and determining future operations arrangements.

讨论不确定情况下的生产-分销三级物流系统的优化设计问题。我们首先提出一个生产-分销系统的确定性模型，通过引入Robust优化理论, 将该模型进一步拓展为包含不确定需求因素的Robust优化模型，最后运用Lagrangian松弛算法得到了原问题的近似最优解，并通过算例对模型和算法的性能进行了分析与评价。

本文以一对一供需模型为研究对象，将企业间的物流优化概括为三个不同发展阶段：供需独立决策期、供应商决策引导期与供需双方协作期。通过分析物流优化的不同阶段给供应链带来的增值潜力，指出供应链管理中存在目标集成、运作集成与策略集成三种优化模式，阐明了这三种优化模式在最大程度地挖掘供应链的增值潜力当中所发挥的作用。

综述集成物流管理系统中设施定位—运输车辆行程路线安排问题的主要研究进展，分析提出有关求解问题的算法的特点，最后提出该研究领域应该关注的几个重要发展方向。