Meta-heuristic Approach to Solve Mixed Vehicle Routing Problem with Backhauls in Enterprise Information System of Service Industry

Meta-heuristic Approach to Solve Mixed Vehicle Routing Problem with Backhauls in Enterprise Information System of Service Industry

DOI: 10.4018/978-1-61520-625-4.ch015
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Abstract

This chapter presents the development of simulated annealing (SA) for a health care application which is modeled as Single Depot Vehicle routing problem called Mixed Vehicle Routing Problem with Backhauls (MVRPB), an extension of Vehicle Routing Problem with Backhauls (VRPB). This variant involves both delivery and pick-up customers and sequence of visiting the customers is mixed. The entire pick-up load should be taken back to depot. The latest rapid advancement of meta-heuristics has shown that it can be applied in practice if they are personified in packaged information technology (IT) solutions along with the combination of a Supply Chain Management (SCM) application integrated with an enterprise resource planning (ERP) resulted to this decision support tool. This chapter provides empirical proof in sustain of the hypothesis, that a population extension of SA with supportive transitions leads to a major increase of efficiency and solution quality for MVRPB if and only if the globally optimal solution is located close to the center of all local optimal solutions.
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Motivation Of The Problem

In today’s highly competitive and demanding environment, the pressure on both public and private organizations is to achieve a better way to deliver values to end customers. There has been a growing recognition that the two goals, cost reduction and customer service are achieved through logistics and SCM (Houlihan, 1988; New and Payne, 1995; New, 1997; and Hines et al., 1998). Organizations have different strategies to manage various functions, based on their respective organizational circumstances. Though there are differences and changes in the strategies adopted by various organizations, major functions for any organization associated with SCM are procurement, forecasting demand, capacity planning, selecting vendors and customers, distribution, and inventory management.

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