We study a multivehicle inventory routing problem (MIRP) in which supplier delivers one type of product along a finite planning horizon, using a homogeneous fleet of vehicles. The main objective is to minimize the total cost of storage and transportation. In order to solve MIRP, we propose an algorithm based on iterated local search (ILS) metaheuristic, using a variable neighborhood descent wit...

In this paper, we develop heuristic algorithms for a complex locomotive scheduling problem in freight transport that arises at Deutsche Bahn AG. While for small instances an approach based on an ILP formulation and its solution by a commercial ILP solver was rather successful, it was found that effective heuristic algorithms are needed for providing better initial upper bounds and for tackling ...

The importance of high performance algorithms for tackling NP-hard optimization problems cannot be understated, and in many practical cases the most successful methods are metaheuristics. When designing a metaheuristic, it is preferable that it be simple, both conceptually and in practice. Naturally, it also must be effective, and if possible, general purpose. Iterated local search (ILS) is suc...

A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...

the inventory routing problem (irp) arises in the context of vendor-managed systems. this problem addresses jointly solving an inventory management problem and a vehicle routing problem. in this paper, we consider a multi-depot multi-vehicle inventory routing problem in which suppliers produce one type of product to be delivered to customers during a finite time horizon. we propose a two-phase ...

The genomic median problem is an optimization problem inspired by a biological issue: it aims to find the chromosome organization of the common ancestor to multiple living species. It is formulated as the search for a genome that minimizes a rearrangement distance measure among given genomes. Several attempts have been reported for solving this NP-hard problem. These range from simple heuristic...

This paper addresses a variation of the Traveling Salesman Problem with Pickup and Delivery in which loading and unloading operations have to be executed in a first-in-first-out fashion. It provides an integer programming formulation of the problem. It also describes five operators for improving a feasible solution, and two heuristics that utilize these operators: a probabilistic tabu search al...

In this work, we introduce the Flowshop Scheduling Problem with Delivery Dates and Cumulative Payoffs. This problem is a variation of the flowshop scheduling problem with job release dates that maximizes the total payoff with a stepwise job objective function. This paper contributes towards proposing a mathematical formulation for this new problem and an original constructive heuristic. Additio...

Many real life optimization problems are nonconvex and may have several local minima within their feasible region. Therefore, global search methods are needed. Metaheuristics are efficient global optimizers including a metastrategy that guides a heuristic search. Genetic algorithms, simulated annealing, tabu search and scatter search are the most well-know metaheuristics. In general, they do no...