Unified heuristics to solve routing problem of reverse logistics in sustainable supply chain.
ABSTRACT A reverse logistics problem, motivated by many real-life applications, is examined where bottles/cans in which products are delivered from a processing depot to customers in one period are available for return to the depot in the following period. The picked-up bottles/cans need to be adjusted in the place of delivery load. This problem is termed as simultaneous delivery and pick-up problem with constrained capacity (SDPC). We develop three unified heuristics based on extended branch and bound heuristic, genetic algorithm and simulated annealing to solve SDPC. These heuristics are also designed to solve standard travelling salesman problem (TSP) and TSP with simultaneous delivery and pick-up (TSDP). We tested the heuristics on standard, derived and randomly generated datasets of TSP, TSDP and SDPC and obtained satisfying results with high convergence in reasonable time.
- SourceAvailable from: sciencedirect.com[Show abstract] [Hide abstract]
ABSTRACT: Most of the disasters occur unexpectedly with respect to time, place and intensity. Due to these reasons, humanitarian logistics has attracted considerable research attention in the recent past. This paper reviews modeling parameters for objective functions and constraints in humanitarian logistics distribution. The objective functions that are realized in various humanitarian emergency operations aim to increase the supply of relief aid. In this paper, a classification based review methodology is employed to identify various cost functions and constraints for primary emergency operations in logistics viz. casualty transportation and relief distribution problems. Based on the classification, areas of future research are discussed that would be useful for key decision makers in planning logistics activities in emergency situations. The paper also serves to delineate the recent trends, challenges and research gaps in the area of Humanitarian Logistics.Procedia Engineering 12/2014; 97. DOI:10.1016/j.proeng.2014.12.469
- [Show abstract] [Hide abstract]
ABSTRACT: This paper discusses the design and implementation of a decision-support software system based on web services, capable of modelling the supply chain and querying the supply-chain partners to provide information, regarding the availability of parts, required for the production of a highly customisable product. Furthermore, it describes the details of a software system for the evaluation of time and financial feasibility of acquiring the necessary parts in order for the customised product to be built. The feasibility of implementing this approach is demonstrated in a typical automotive case study. The system is capable of simulating the customer's orders impact on the supply-chain operation, while it utilises the Web services technology for facilitating the supply-chain control logic.International Journal of Production Research 01/2012; DOI:10.1080/00207543.2012.701781 · 1.32 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: A multistate network is a stochastic network composed of multistate arcs in which each arc has several possible capacities and may fail due to failure, maintenance, etc. The quality of a multistate network depends on how to meet the customer's requirements and how to provide the service in time. The system reliability, the probability that a given amount of data can be transmitted through a pair of minimal paths (MPs) simultaneously under the time constraint, is a proper index to evaluate the quality of a multistate network. An efficient solution procedure is first proposed to calculate it. In order to further enhance the system reliability, the network administrator decides the routing policy in advance to indicate the first and the second priority pairs of MPs. The second priority pair of MPs takes charge of the transmission duty if the first fails. The system reliability under the routing policy can be subsequently evaluated.International Journal of Systems Science 01/2012; DOI:10.1080/00207721.2012.659684 · 1.58 Impact Factor