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The application of the Automated Storage and Retrieval System (AS/RS) in the warehouse has been improved significantly over the last few decades. In the recent years, a new type of AS/RS, Shuttle Based Storage and Retrieval System (SBS/RS) has taken many industries interest by storm due to its flexibility and throughput performances. This paper studies the mathematical optimization of item location assignment and task scheduling in SBS/RS mainly with tier-to-tier system which allows the shuttle to transport between tiers using a lift system. Since this system is mostly applied in giant e-commerce industries, considering order data set and multiple stock keeping unit (SKU) in the mathematical model formulation will give a significant benefit in the real-life scenario. This paper also proposed a modified genetic algorithm to solved both item location assignment and task scheduling with a good computational time result for large size instances within a reasonable amount of time. [ABSTRACT FROM AUTHOR]

Because the formation or reformation of emergency logistics is a complex undertaking, this study proposes a multi-period location-routing model in the immediate aftermath of a flood natural disaster. The model can decide the temporary depot locations and make vehicle routing plans in which the amount of each relief supplies to be transported can be optimally determined. The temporary depot considered in this problem is a facility different from a typical warehouse on the fact that temporary depots are not set up to provide storage, but are created instead to facilitate transferring relief supplies from one carrier type to another carrier type at the flood boundary. The most common transport means used in the real flood problem, trucks and boats, are considered in the model formulation. We begin by explaining the proposed mixed-integer programming model which employs a dynamic approach to locate the temporary depots, after which we conduct a set of numerical experiments to test the model formulation and analyze the characteristics of the optimization problem. The experimental results indicate that, based on flood disaster characteristics, our model is capable of showing the optimal locations of temporary depots in the flood response operations. [ABSTRACT FROM AUTHOR]

Because the formation or reformation of emergency logistics is a complex undertaking, this study proposes a multi-period location-routing model in the immediate aftermath of a flood natural disaster. The model can decide the temporary depot locations and make vehicle routing plans in which the amount of each relief supplies to be transported can be optimally determined. The temporary depot considered in this problem is a facility different from a typical warehouse on the fact that temporary depots are not set up to provide storage, but are created instead to facilitate transferring relief supplies from one carrier type to another carrier type at the flood boundary. The most common transport means used in the real flood problem, trucks and boats, are considered in the model formulation. We begin by explaining the proposed mixed-integer programming model which employs a dynamic approach to locate the temporary depots, after which we conduct a set of numerical experiments to test the model formulation and analyze the characteristics of the optimization problem. The experimental results indicate that, based on flood disaster characteristics, our model is capable of showing the optimal locations of temporary depots in the flood response operations. [ABSTRACT FROM AUTHOR]

The design of a supply chain has been considered by many practitioners and researchers recently. One model that is used to optimize distribution from a single facility (depot) to a set of retailers over a given planning horizon and considering stock management decisions is known as Inventory Routing Problem (IRP). This model tries to optimize the trade-off between inventory and transportation costs. Designing IRP becomes more complex if the items are deteriorating. In this research, we develop IRP for deteriorating items where there is possibility that every vehicle has more than one route. Multi routing is suitable for deteriorating items since it minimizes delivery time for each item. We consider more than one vehicle at the depot and each vehicle has similar maximum capacity. Since the problem is an NP hard problem, we use Particle Swarm Optimization (PSO) method to solve the problem. A numerical example and sensitivity analysis are conducted to show the deteriorating rate effects at the vehicle and inventory, and also inventory and transportation cost to the total supply chain cost. The results show that the total cost/hour is more sensitive to different values inventory deteriorating rate than transportation deteriorating rate. [ABSTRACT FROM AUTHOR]

In this research, a distribution network that trucks transport various products including perishable foods from some suppliers to some stores are considered. In this distribution network, there are multiple cross docking centers. Cross docking is a logistic management strategy in which products delivered by inbound trucks from suppliers are immediately loaded to outbound trucks to stores in same day. Because products are not stored for a long term in cross docking center, cross docking center can save operation cost, reduce inventory space, shorten delivery lead time from supplier to store and avoid loss of sales opportunities due to deterioration of food etc. A distribution network that has multiple cross docking centers is called the cross docking network. This research considers effective truck transportation among cross docking centers in cross docking network. The main difference from the previous truck scheduling paper of cross docking network is that this research selects truck type considering temperature control zone (Normal, Chilled and Frozen) of the products to be transported. We propose a Mixed Integer Programming (MIP) with an objective function which is to minimize total transportation cost among cross docking centers. And this research decides truck type, truck size, destination, quantity of loaded product and departure time to cross docking center. We show numerical experiment results using real data transported among cross docking centers and discuss the difference between the current and proposed transportation. [ABSTRACT FROM AUTHOR]