The stockpiling or storage of commodities plays a very important role in commercial and marketing services. This process by managing the time intervals between production and consumption, brings new synergy for goods and yields expected profits for producers. Such process by diminishing the wastes and increasing opportunity cost for products in different periods of time leads to credibility and incentive in market factors. It also amounts to prudent and efficient decision making in the field of production, consumption and distribution. Furthermore, this process by bringing necessary and proper adjustments in consumption and price level leads to food and economic security. The purpose of this paper is , by taking into account the special characteristics of Perishable agricultural products, to review and analyse the factors which determine the level and magnitude of storage. To accomplish the task, first the theoretical background and literature are briefly reviewed and a simple model is introduced and at the next stage the model is extended to include other concepts such as rational expectations, uncertainty and cost per unit of storage

In this paper, a supply chain model including production and distribution of Perishable crops is introduced. Echelons of the supply chain are farms, fridges and wholesales. Furthermore, the demand can be responded by imports. The planning horizon is finite. Due to the Perishable nature of the crops the harvested crops can be held no longer than pre-determined periods. The purpose of this model is to determine optimal planning for production, holding and transportation of each item in each period in order to the total cost is minimized. This model is applied for the case of potato, onion and tomato. The numerical results show that a decrease in total cost and consequently in price of each product can be made via using this model. Saving in water sources is another result of this model. Sensitivity analysis is done to investigate the effects of the key parameters on price and amount of import.

In this article, we consider a two commodity continuous review Perishable inventory system with a finite number of homogeneous sources of demands. The maximum storage capacity of Si units for the ith commodity (i=1,2). The life time of items of each commodity is assumed to be exponentially distributed with parameter gi (i=1,2). The time points of primary demand occurrences form independent quasi random distributions each with parameter li (i=1,2) A joint reordering policy is adopted with a random lead time for orders with exponential distribution. When the inventory position of both commodities are zero, any arriving primary demand enters into an orbit. The demands in the orbit send out signals to compete for their demand which is distributed as exponential. We assume that the two commodities are both way substitutable. The joint probability distribution for both commodities and number of demands in the orbit is obtained for the steady state case. Various system performance measures are derived, and the results are illustrated with numerical examples.

The carrier collaboration problem for logistic optimization is a fundamental part of the sustainable supply chain, and has increasingly been of concern in recent years. This study proposes a novel nonlinear mathematical model to address the carrier collaboration problem. It involves a set of heterogenous vehicles with specific capacities for serving Perishable products to several pickup and delivery nodes. Products are corrupted at a constant rate. The purpose is simultaneously finding routes to maximize profits in order to enhance customer satisfaction which is dependent on the freshness of delivered products. There are various applications of the proposed model in the environment which can help reducing transportation emissions, eliminating empty back hauls. Further, the proposed model uses a Hybrid Genetic Algorithm (HGA) is proposed to solve this problem due to improve the quality of initial solutions Variable Neighborhood Search (VNS) method is developed. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time.

Delivering Perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years asthe global market becoming more competitive. In this studya multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. Finally, their results are compared to each other when the optimization software becomes unable of solution representation.

Transportation conditions for Perishable goods are very important. This importance is Because of food hygiene and because of waste reduction. One of prerequisite for planning a cold chain transportation of Perishable cargo is demand estimation. For this Propose, this paper is studying behavior of transportation of Perishable goods by estimating demand model. The model which is estimated for each of the provinces use panel data. The results show that for every one person increase in province's population, one million rials increase in province's real GDP and for one ton increase in province's milk production Perishable cargo transportation demand increases by 78.5, 18.49 and 91738.8 ton-kilometer respectively. On the other side, for every one thousand ton increase in province's meat production, one thousand ton increase in province's poultry production and finally one rial increase in ton kilometer transportation real fare Perishable cargo transportation demand decreases by 604516.5, 81006.3 and 309386.3 .ton-kilometer.

In this paper we study a two-echelon inventory system with maximum profit objective for Perishable items in which inflation effects are considered. We consider random product life and deterministic demand. Shortage is not allowed. Based on the stage in which Perishable items are stocked, two models are developed. For each model, optimum order quantity is obtained and a practical example is solved. The models are evaluated through sensitivity analysis.