Brian Rodrigues

Nurse rostering problems––a bibliographic survey

Abstract Hospitals need to repeatedly produce duty rosters for its nursing staff. The good scheduling of nurses has impact on the quality of health care, the recruitment of nurses, the development of budgets and other nursing functions. The nurse rostering problem (NRP) has been the subject of much study. This paper presents a brief overview, in the form of a bibliographic survey, of the many models and methodologies available to solve the NRP.

k -Center problems with minimum coverage

In this work, we study an extension of the k-center facility location problem, where centers are required to service a minimum of clients. This problem is motivated by requirements to balance the workload of centers while allowing each center to cater to a spread of clients. We study three variants of this problem, all of which are shown to be N P-hard. In-approximation hardness and approximation algorithms with factors equal or close to the best lower bounds are provided. Generalizations, including vertex costs and vertex weights, are also studied.

Crossdocking—JIT scheduling with time windows

In this paper, we study a problem central to crossdocking that aims to eliminate or minimize storage and order picking activity using JIT scheduling. The problem is modelled naturally as a machine scheduling problem. As the problem is NP-hard, and for real-time applications, we designed and implemented two heuristics. The first uses Squeaky Wheel Optimization embedded in a Genetic Algorithm and the second uses Linear Programming within a Genetic Algorithm. Both heuristics offer good solutions in experiments where comparisons are made with the CPLEX solver.

Multiple crossdocks with inventory and time windows

Crossdocking studies have mostly been concerned with the physical layout of a crossdock or on a single crossdock. In this work, we study a network of crossdocks taking into consideration delivery and pickup time windows, warehouse capacities and inventory-handling costs. Because of the complexity of the problem, local search techniques are developed and used with simulated annealing and tabu search heuristics. Extensive experiments were conducted and results show that the heuristics outperform CPLEX, providing solutions in realistic timescales.

Metaheuristics with Local Search Techniques for Retail Shelf-Space Optimization

Efficient shelf-space allocation can provide retailers with a competitive edge. While there has been little study on this subject, there is great interest in improving product allocation in the retail industry. This paper examines a practicable linear allocation model for optimizing shelf-space allocation. It extends the model to address other requirements such as product groupings and nonlinear profit functions. Besides providing a network flow solution, we put forward a strategy that combines a strong local search with a metaheuristic approach to space allocation. This strategy is flexible and efficient, as it can address both linear and nonlinear problems of realistic size while achieving near-optimal solutions through easily implemented algorithms in reasonable timescales. It offers retailers opportunities for more efficient and profitable shelf management, as well as higher-quality planograms.

The over-constrained airport gate assignment problem

In this paper, we study the over-constrained airport gate assignment problem where the objectives are to minimize the number of ungated flights and total walking distances or connection times. We first use a greedy algorithm to minimize ungated flights. Exchange moves are employed to facilitate the use of heuristics. Simulated annealing and a hybrid of simulated annealing and tabu search are used. Experimental results are good and exceed those previously obtained.

A simulated annealing and hill-climbing algorithm for the traveling tournament problem

Abstract The Traveling Tournament Problem (TTP) [E. Easton, G. Nemhauser, M. Trick, The traveling tournament problem description and benchmarks, in: Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming, CP 2001, 2001, pp. 580–584; M. Trick, Challenge Traveling Tournament Problems, 2004] schedules a double round-robin tournament to minimize the total distance traveled by competing teams. It involves issues of feasibility and optimality and is a challenge to constraint and integer programming. In this work, we divide the search space and use simulated annealing (SA) to search a timetable space and hill-climbing to explore a team assignment space. The SA component mutates timetables using conditional local jumps to find timetables which lead to better schedules while hill-climbing is enhanced by pre-computation and dynamic cost updating to provide fast and efficient search. Computational experiments using this hybrid approach on benchmark sets give results comparable to or better than current best known solutions.

Sexual Selection for Genetic Algorithms

Genetic Algorithms (GA) have been widely used inoperations research andoptimization since first proposed. A typical GAcomprises three stages, the encoding, theselection and the recombination stages. In thiswork, we focus our attention on the selectionstage of GA, and review afew commonly employed selection schemes andtheir associated scalingfunctions. We also examine common problems andsolution methods forsuch selection schemes.We then propose a new selection scheme inspiredby sexual selectionprinciples through female choice selection, andcompare the performance of this new schemewith commonly used selection methods in solvingsome well-known problems including the Royal RoadProblem, the Open Shop Scheduling Problem andthe Job Shop Scheduling Problem.

Transshipment through crossdocks with inventory and time windows

The supply chain between manufacturers and retailers always includes transshipments through a network of locations. A major challenge in making demand meet supply has been to coordinate transshipment activities across the chain aimed at reducing costs and increasing service levels in the face of a range of factors, including demand fluctuations, short lead times, warehouse limitations and transportation and inventory costs. The success in implementing push-pull strategies, when firms change from one strategy to another in managing the chain and where time lines are crucial, is dependent on adaptive transshipment scheduling. Yet again, in transshipment through crossdocks, where just-in-time objectives prevail, precise scheduling between suppliers, crossdocks and customers is required to avoid inventory backups or delays.

Note---Pricing and Inventory Control for a Perishable Product

In this note, we study the concurrent determination of pricing and inventory replenishment decisions for a perishable product in an infinite horizon. Demands in consecutive periods are independent and influenced by prices charged in each period. In particular, we treat price as a decision variable to maximize the total discounted profit. We analyze the optimal solution-structure of a two-period lifetime problem and from insights gained in numerical experiments, develop a base-stock/list-price heuristic policy for products with arbitrary fixed lifetimes. Experiments show this policy to be effective.