Application of discrete-event simulation in health care clinics: A surveyJun, J B; Jacobson, S H; Swisher, J R
doi: 10.1057/palgrave.jors.2600669pmid: N/A
AbstractIn recent decades, health care costs have dramatically increased, while health care organisations have been under severe pressure to provide improved quality health care for their patients. Several health care administrators have used discrete-event simulation as an effective tool for allocating scarce resources to improve patient flow, while minimising health care delivery costs and increasing patient satisfaction. The rapid growth in simulation software technology has created numerous new application opportunities, including more sophisticated implementations, as well as combining optimisation and simulation for complex integrated facilities. This paper surveys the application of discrete-event simulation modeling to health care clinics and systems of clinics (for example, hospitals, outpatient clinics, emergency departments, and pharmacies). Future directions of research and applications are also discussed.
A heuristic algorithm for a production planning problem in an assembly systemPark, M-W; Kim, Y-D
doi: 10.1057/palgrave.jors.2600683pmid: N/A
AbstractThis paper focuses on a production planning problem in an assembly system operating on a make-to-order basis. Due dates are considered as constraints in the problem, that is, tardiness is not allowed. The objective of the problem is to minimise holding costs for final product inventory as well as work-in-process inventory. A non-linear mathematical model is presented and a heuristic algorithm is developed using a solution property and a network model for defining solutions of the problem. A series of computational tests were done to compare the algorithm with a commercial planning/scheduling software and backward finite-loading methods that employ various priority rules. The results showed that the suggested algorithm outperformed the others.
Phase transitions in project schedulingHerroelen, W; De Reyck, B
doi: 10.1057/palgrave.jors.2600680pmid: N/A
AbstractResearchers in the area of artificial intelligence have recently shown that many NP-complete problems exhibit phase transitions. Often, problem instances change from being easy to being hard to solve to again being easy to solve when certain of their characteristics are modified. Most often the transitions are sharp, but sometimes they are rather continuous in the order parameters that are characteristic of the system as a whole. To the best of our knowledge, no evidence has been provided so far that similar phase transitions occur in NP-hard scheduling problems. In this paper we report on the existence of phase transitions in various resource-constrained project scheduling problems. We discuss the use of network complexity measures and resource parameters as potential order parameters. We show that while the network complexity measures seem to reveal continuous easy-hard or hard-easy phase transitions, the resource parameters exhibit a relatively sharp easy-hard-easy transition behaviour.
An LP-based heuristic for two-stage capacitated facility location problemsKlose, A
doi: 10.1057/palgrave.jors.2600675pmid: N/A
AbstractIn this paper, a linear programming based heuristic is considered for a two-stage capacitated facility location problem with single source constraints. The problem is to find the optimal locations of depots from a set of possible depot sites in order to serve customers with a given demand, the optimal assignments of customers to depots and the optimal product flow from plants to depots. Good lower and upper bounds can be obtained for this problem in short computation times by adopting a linear programming approach. To this end, the LP formulation is iteratively refined using valid inequalities and facets which have been described in the literature for various relaxations of the problem. After each reoptimisation step, that is the recalculation of the LP solution after the addition of valid inequalities, feasible solutions are obtained from the current LP solution by applying simple heuristics. The results of extensive computational experiments are given.
Ant colonies for the quadratic assignment problemGambardella, L M; Taillard, É D; Dorigo, M
doi: 10.1057/palgrave.jors.2600676pmid: N/A
AbstractThis paper presents HAS–QAP, a hybrid ant colony system coupled with a local search, applied to the quadratic assignment problem. HAS–QAP uses pheromone trail information to perform modifications on QAP solutions, unlike more traditional ant systems that use pheromone trail information to construct complete solutions. HAS–QAP is analysed and compared with some of the best heuristics available for the QAP: two versions of tabu search, namely, robust and reactive tabu search, hybrid genetic algorithm, and a simulated annealing method. Experimental results show that HAS–QAP and the hybrid genetic algorithm perform best on real world, irregular and structured problems due to their ability to find the structure of good solutions, while HAS–QAP performance is less competitive on random, regular and unstructured problems.
An alternate linear algorithm for the minimum flow problemAdlakha, V G
doi: 10.1057/palgrave.jors.2600662pmid: N/A
AbstractWe present an alternate linear algorithm for finding the minimum flow in (s, t)-planar networks using a new concept of minimal removable sets developed here. The iterative nature of the algorithm facilitates the adjustment of solutions for systems in developmental stages. The minimum flow algorithm presented here requires O(|V|) time, where V denotes the set of vertices. The minimum flow problem arises in many transportation and communication systems.