The Least Cost Method is another method used to obtain the initial feasible solution for the transportation problem. Here, the allocation begins with the cell which has the minimum cost.

Saji3 1 Mechanical Engineering Department, M. The vehicle route scheduling problem is concerned with the determination of routes and schedules for a fleet of vehicles to satisfy the demands of a set of customers. The goal of vehicle routing is to schedule multiple suppliers from various places.

Vehicle routing has existed since the advent of the Industrial age, when large-scale production became possible. As the complexity and scale of the manufacturing world increased, the task of optimizing vehicle routing grew. The vehicle routing problem is a combinatorial optimization and integer programming problem seeking to service a number of customers with a fleet of vehicles.

Often the context is that of delivering goods located at a central depot to customers who have placed orders for such goods or vice-versa. Implicit is the goal of minimizing the cost of distributing the goods.

Many methods have been developed for searching for good solutions to the problem, however even for the smallest problems, finding global minimum for the cost function is computationally complex. The paper presents an optimization algorithm using Particle Swarm Optimization PSO for the vehicle routing that would enable the logistic manager of a latex industry to minimize the transportation cost and maximize the collection using minimum number of vehicles.

The factory collects rubber latex from permanent collection centers located around kilometers from the factory in addition to few non-permanent Minimization of the transportation cost of. The company uses about 30 vehicles on an average per trip.

The collection capacities of these vehicles vary from 24 to 65 barrels kg ,kg. The charge per kilometer of these vehicles depends on their carrying capacity. A manual procedure of vehicle route allotment is in practice in the organization, for which the efficiency cannot be predicted. Hence a stochastic procedure for optimization is considered for vehicle route scheduling of the organization.

Genetic algorithm for solving capacitated vehicle routing problem are reported that are mainly characterized by using vehicles of the same capacity based at a central depot that will be optimally routed to supply customers with known demands.

The algorithms are used to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost [1, 2]. An iterative route construction and improvement algorithm for the vehicle routing problem with soft time windows is presented by Miguel [3]. This paper presents a problem with practical applications in distribution and logistics due to the rising importance of just-in-time procedure.

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Keeping production costs low by producing or sourcing raw goods in other countries or states allows companies to make more profit, but the logistical costs of transporting and storing products can eat into those profits. Business owners can benefit from understanding logistics, and the detailed costs involved, to maximize their margins and minimize costs. |

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A particle swarm optimization algorithm for open vehicle routing problem OVRP presented by Mir Hassani [4] reports that in OVRP a vehicle does not return to the depot after servicing the last customer on a route. Studies on solving the capacitated vehicle routing problem by Jin Ai [5] presents two solution representations and the corresponding decoding methods for solving the problem using particle swarm optimization.

In problems where the customers require not only the delivery of goods but also the simultaneous pick up of goods, a general assumption is that all delivered goods originate from the depot and all pickup goods must be transported back to the depot [6].

Literatures on solving vehicle routing problems using Ant Colony Optimization ACO algorithm constructs a complete tour for the first ant prior to the second ant starting its tour [7].

Once the vehicle capacity constraint is met, the ant will return to the depot before selecting the next customer. This selection process continues until each customer is visited and the tour is complete.

A heuristic approach for solving large scale bus transits vehicle scheduling problem with route time constraints is presented by Ali Haghani. They conducted a study of multiple depots with time window, with the constraint of restriction fuel efficiency.

Russel Eberhart, Balter and 2. Vehicle route scheduling and transportation cost minimization in a latex industry using PSO www. They examined how changes in the procedure affect the number of iteration required to meet an error criterion, and the frequency with which models interminably around a new optimum.

In the binary version, trajectories are traced in the probability that a co-ordinate will take on a zero or one value. It is proved that PSO with inertia weight will have better performance and has a bigger chance to find the global optimum within a reasonable number of iterations. A large inertia weight facilitates a more powerful global search while a small inertia weight facilitates a more powerful local search Yuhuishe, Russell and Engelbrecht AP conducted empirical studies on the performance of PSO and found that PSO converges very quickly towards the optimal positions but may slow its convergence sped when it is near a minimum [11].

Also proved that using an adaptive inertia weight, performance of PSO near optima can be improved.Transportation cost is one of the major costs incurred during operations in courier service industry.

Their profit margin depends purely on transportation cost. In the proposed model we find that the objective function Transportation cost (11) and the resulting goal programming model (30) with (25)-(29) is a function of the membership function. Both the objectives, minimization of the transportation cost and minimization of transportation time are reasonably achieved.

REQUIREMENTS OF A LINEAR PROGRAMMING PROBLEM All LP problems have four properties in common: 1. LP problems seek to maximize or minimize some quantity (usually profit or cost).

We refer to this property as the objective function of an LP problem.

Vehicle route scheduling and transportation cost minimization in a latex industry using PSO Uploaded by International Journal of Research in Engineering and Science The vehicle route scheduling problem is concerned with the determination of routes and schedules for a fleet of vehicles to satisfy the demands of a set of customers.

USING EXCEL SOLVER IN OPTIMIZATION PROBLEMS Leslie Chandrakantha through examples from different areas such as manufacturing, transportation, financial planning, and scheduling to demonstrate the use of Solver. Introduction minimizing the cost, distance, time, etc.

Figure 1 shows the split up of transportation cost on the total cost of the firm 40% of the total cost incurred by the transportation. This ultimately follows in the courier service industry too.

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TRANSPORTATION COSTS MINIMIZATION IN LOCATION BASED APPROACHES - CORE