The rapid advancements in information technologies and globalization change the way of distributing goods to customers. Many enterprises have multiple factories, warehouses, distribution centers strive for competitive efficiency operations minimize transportation costs. This study proposed mixed-integer programming (MIP) model multi-depot split-delivery vehicle routing problems (MDSDVRPs) with ...

This paper introduces the fish feed production routing problem (FFPRP) faced by Norwegian salmon producers. The FFPRP is comprised of a scheduling and rich vehicle (VRP) thus denotes variant integrated problem. We present discrete time mixed integer programming (MIP) model FFPRP. Specifically, incorporates multi-product, multi-trip, multi-depot setting, where orders are produced at lines factor...

The overall cost of companies dealing with the distribution tasks is considerably affected by the way that distributing vehicles are procured. In this paper, a more practical version of capacitated vehicle routing problem (CVRP) in which the decision of purchase or hire of vehicles is simultaneously considered is investigated. In CVRP model capacitated vehicles start from a single depot simulta...

Dynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-alloc...

In this thesis, we review and synthesize a number of algorithmic approaches for optimizing the job-shop scheduling problem (JSSP). The complexity of the JSSP leads to large and difficult combinatorial optimization models. In Chapter 1, we review first an analytical method based on Mixed Integer Programming (MIP). Second, we review an assumption-based heuristic method. In Chapter 2, the JSSP is ...

We study an incremental network design problem, where in each time period of the planning horizon an arc can be added to the network and a maximum flow problem is solved, and where the objective is to maximize the cumulative flowover the entire planning horizon. After presenting twomixed integer programming (MIP) formulations for this NP-complete problem, we describe several heuristics and prov...

This paper presents a hybrid of a general heuristic framework and a general purpose mixed-integer programming (MIP) solver. The framework is based on local search and an adaptive procedure which chooses between a set of large neighborhoods to be searched. A mixed integer programming solver and its built-in feasibility heuristics is used to search a neighborhood for improving solutions. The gene...

Mixed-Integer Programs (MIP’s) involving logical implications modelled through big-M coefficients, are notoriously among the hardest to solve. In this paper we propose and analyze computationally an automatic problem reformulation of quite general applicability, aimed at removing the model dependency on the big-M coefficients. Our solution scheme defines a master Integer Linear Problem (ILP) wi...

Mixed-Integer linear Programming (MIP) plays a central role in modeling difficult-to-solve (NP-hard) combinatorial problems. However, the exact solution of the resulting models often cannot be carried out for the problem sizes of interest in real-world applications, hence one is interested in effective heuristic methods. Although several heuristic and metaheuristic frameworks have been proposed...