A Mixed-Integer Linear Programming Model for Transportation Planning in the Full Truck Load Strategy to Supply Products with Unbalanced Demand in the Just in Time Context: A Case Study

[EN] Growing awareness in cutting transport costs and minimizing the environmental impact means that companies are increasingly interested in using the full truck load strategy in their supply tasks. This strategy consists of filling trucks completely with one product type or a mixture of products from the same supplier. This paper aims to propose a mixed-integer linear programming model and procedure to fill trucks which considers limitations of stocks, stock levels and unbalanced demand and minimization of the total number of trucks used in the full truck load strategy. The results obtained from a case study are presented and are exported in a conventional spreadsheet available for a company in the automotive industry.Maheut ., JP.; García Sabater, JP. (2013). A Mixed-Integer Linear Programming Model for Transportation Planning in the Full Truck Load Strategy to Supply Products with Unbalanced Demand in the Just in Time Context: A Case Study. IFIP Advances in Information and Communication Technology. 397:576-583. doi:10.1007/978-3-642-40361-3_73S576583397Bitran, G.R., Haas, E.A., Hax, A.C.: Hierarchical production planning: a single stage system. Operations Research 29, 717–743 (1981)Sun, H., Ding, F.Y.: Extended data envelopment models and a practical tool to analyse product complexity related to product variety for an automobile assembly plant. International Journal of Logistics Systems and Management 6, 99–112 (2010)Boysen, N., Fliedner, M.: Cross dock scheduling: Classification, literature review and research agenda. Omega 38, 413–422 (2010)Garcia-Sabater, J.P., Maheut, J., Garcia-Sabater, J.J.: A two-stage sequential planning scheme for integrated operations planning and scheduling system using MILP: the case of an engine assembler. Flexible Services and Manufacturing Journal 24, 171–209 (2012)Ben-Khedher, N., Yano, C.A.: The Multi-Item Replenishment Problem with Transportation and Container Effects. Transportation Science 28, 37–54 (1994)Cousins, P.D.: Supply base rationalisation: myth or reality? European Journal of Purchasing Supply Management 5, 143–155 (1999)Kiesmüller, G.P.: A multi-item periodic replenishment policy with full truckloads. International Journal of Production Economics 118, 275–281 (2009)Goetschalckx, M.: Transportation Systems Supply Chain Engineering, vol. 161, pp. 127–154. Springer, US (2011)Liu, R., Jiang, Z., Fung, R.Y.K., Chen, F., Liu, X.: Two-phase heuristic algorithms for full truckloads multi-depot capacitated vehicle routing problem in carrier collaboration. Computers Operations Research 37, 950–959 (2010)Arunapuram, S., Mathur, K., Solow, D.: Vehicle Routing and Scheduling with Full Truckloads. Transportation Science 37, 170–182 (2003

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite

Large-scale multiple sequence alignment and phylogeny estimation

With the advent of next generation sequencing technologies, alignment and phylogeny estimation of datasets with thousands of sequences is being attempted. To address these challenges, new algorithmic approaches have been developed that have been able to provide substantial improvements over standard methods. This paper focuses on new approaches for ultra-large tree estimation, including methods for co-estimation of alignments and trees, estimating trees without needing a full sequence alignment, and phylogenetic placement. While the main focus is on methods with empirical performance advantages, we also discuss the theoretical guarantees of methods under Markov models of evolution. Finally, we include a discussion of the future of large-scale phylogenetic analysis

Solving the master equation for Indels

Abstract Background Despite the long-anticipated possibility of putting sequence alignment on the same footing as statistical phylogenetics, theorists have struggled to develop time-dependent evolutionary models for indels that are as tractable as the analogous models for substitution events. Main text This paper discusses progress in the area of insertion-deletion models, in view of recent work by Ezawa (BMC Bioinformatics 17:304, 2016); (BMC Bioinformatics 17:397, 2016); (BMC Bioinformatics 17:457, 2016) on the calculation of time-dependent gap length distributions in pairwise alignments, and current approaches for extending these approaches from ancestor-descendant pairs to phylogenetic trees. Conclusions While approximations that use finite-state machines (Pair HMMs and transducers) currently represent the most practical approach to problems such as sequence alignment and phylogeny, more rigorous approaches that work directly with the matrix exponential of the underlying continuous-time Markov chain also show promise, especially in view of recent advances